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You searched for subject:(link prediction). Showing records 1 – 30 of 82 total matches.

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University of Windsor

1. Sanghvi, Shikhar. A Feature Based Model for Negative Sign Prediction in Signed Social Networks.

Degree: MS, Computer Science, 2020, University of Windsor

 People hold all kinds of positive and negative feelings for one another. Social networking online serves as a platform for showcasing such relationships, whether friendly… (more)

Subjects/Keywords: Link prediction; Sign prediction; Signed social networks

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APA (6th Edition):

Sanghvi, S. (2020). A Feature Based Model for Negative Sign Prediction in Signed Social Networks. (Masters Thesis). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/8480

Chicago Manual of Style (16th Edition):

Sanghvi, Shikhar. “A Feature Based Model for Negative Sign Prediction in Signed Social Networks.” 2020. Masters Thesis, University of Windsor. Accessed January 17, 2021. https://scholar.uwindsor.ca/etd/8480.

MLA Handbook (7th Edition):

Sanghvi, Shikhar. “A Feature Based Model for Negative Sign Prediction in Signed Social Networks.” 2020. Web. 17 Jan 2021.

Vancouver:

Sanghvi S. A Feature Based Model for Negative Sign Prediction in Signed Social Networks. [Internet] [Masters thesis]. University of Windsor; 2020. [cited 2021 Jan 17]. Available from: https://scholar.uwindsor.ca/etd/8480.

Council of Science Editors:

Sanghvi S. A Feature Based Model for Negative Sign Prediction in Signed Social Networks. [Masters Thesis]. University of Windsor; 2020. Available from: https://scholar.uwindsor.ca/etd/8480


University of Notre Dame

2. Ryan N. Lichtenwalter. Network Analysis and Link Prediction: Effective and Meaningful Modeling and Evaluation</h1>.

Degree: Computer Science and Engineering, 2012, University of Notre Dame

Link prediction is succinctly stated as identifying unobserved links in a network. It has important applications ranging from recommending beneficial relationships in social networks… (more)

Subjects/Keywords: link analysis; data mining; link prediction; networks; graph theory; classification

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APA (6th Edition):

Lichtenwalter, R. N. (2012). Network Analysis and Link Prediction: Effective and Meaningful Modeling and Evaluation</h1>. (Thesis). University of Notre Dame. Retrieved from https://curate.nd.edu/show/fj23611103z

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lichtenwalter, Ryan N.. “Network Analysis and Link Prediction: Effective and Meaningful Modeling and Evaluation</h1>.” 2012. Thesis, University of Notre Dame. Accessed January 17, 2021. https://curate.nd.edu/show/fj23611103z.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lichtenwalter, Ryan N.. “Network Analysis and Link Prediction: Effective and Meaningful Modeling and Evaluation</h1>.” 2012. Web. 17 Jan 2021.

Vancouver:

Lichtenwalter RN. Network Analysis and Link Prediction: Effective and Meaningful Modeling and Evaluation</h1>. [Internet] [Thesis]. University of Notre Dame; 2012. [cited 2021 Jan 17]. Available from: https://curate.nd.edu/show/fj23611103z.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lichtenwalter RN. Network Analysis and Link Prediction: Effective and Meaningful Modeling and Evaluation</h1>. [Thesis]. University of Notre Dame; 2012. Available from: https://curate.nd.edu/show/fj23611103z

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Michigan

3. Cai, Jiarui. Computational Approaches for Estimating Life Cycle Inventory Data.

Degree: MS, Natural Resources and Environment, 2016, University of Michigan

 Data gaps in life cycle inventory (LCI) are stumbling blocks for investigating the life cycle performance and impact of emerging technologies. It can be tedious,… (more)

Subjects/Keywords: life cycle assessment; link prediction; data estimation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Cai, J. (2016). Computational Approaches for Estimating Life Cycle Inventory Data. (Masters Thesis). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/134693

Chicago Manual of Style (16th Edition):

Cai, Jiarui. “Computational Approaches for Estimating Life Cycle Inventory Data.” 2016. Masters Thesis, University of Michigan. Accessed January 17, 2021. http://hdl.handle.net/2027.42/134693.

MLA Handbook (7th Edition):

Cai, Jiarui. “Computational Approaches for Estimating Life Cycle Inventory Data.” 2016. Web. 17 Jan 2021.

Vancouver:

Cai J. Computational Approaches for Estimating Life Cycle Inventory Data. [Internet] [Masters thesis]. University of Michigan; 2016. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/2027.42/134693.

Council of Science Editors:

Cai J. Computational Approaches for Estimating Life Cycle Inventory Data. [Masters Thesis]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/134693


Université Catholique de Louvain

4. Andreotti, Riccardo. Adaptive techniques for packet-oriented transmissions in future multicarrier wireless systems.

Degree: 2013, Université Catholique de Louvain

Future wireless systems are expected to provide even more high data rates and reliable communications to support the ever increasing demand of heterogeneous applications and… (more)

Subjects/Keywords: Resource allocation; OFDMA; Link performance prediction

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APA (6th Edition):

Andreotti, R. (2013). Adaptive techniques for packet-oriented transmissions in future multicarrier wireless systems. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/132583

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Andreotti, Riccardo. “Adaptive techniques for packet-oriented transmissions in future multicarrier wireless systems.” 2013. Thesis, Université Catholique de Louvain. Accessed January 17, 2021. http://hdl.handle.net/2078.1/132583.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Andreotti, Riccardo. “Adaptive techniques for packet-oriented transmissions in future multicarrier wireless systems.” 2013. Web. 17 Jan 2021.

Vancouver:

Andreotti R. Adaptive techniques for packet-oriented transmissions in future multicarrier wireless systems. [Internet] [Thesis]. Université Catholique de Louvain; 2013. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/2078.1/132583.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Andreotti R. Adaptive techniques for packet-oriented transmissions in future multicarrier wireless systems. [Thesis]. Université Catholique de Louvain; 2013. Available from: http://hdl.handle.net/2078.1/132583

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

5. Nikolopoulos, Dionysis (author). Link Prediction using Temporal Information in Multilayer Networks.

Degree: 2019, Delft University of Technology

There is an increasing attention towards link prediction in complex networks both in physical and computer science communities. Particularly Online Social Networks (OSNs) are becoming… (more)

Subjects/Keywords: link prediction; temporal networks; Machine Learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Nikolopoulos, D. (. (2019). Link Prediction using Temporal Information in Multilayer Networks. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:a0dbb6da-9a53-4de1-92a0-9cd955486b94

Chicago Manual of Style (16th Edition):

Nikolopoulos, Dionysis (author). “Link Prediction using Temporal Information in Multilayer Networks.” 2019. Masters Thesis, Delft University of Technology. Accessed January 17, 2021. http://resolver.tudelft.nl/uuid:a0dbb6da-9a53-4de1-92a0-9cd955486b94.

MLA Handbook (7th Edition):

Nikolopoulos, Dionysis (author). “Link Prediction using Temporal Information in Multilayer Networks.” 2019. Web. 17 Jan 2021.

Vancouver:

Nikolopoulos D(. Link Prediction using Temporal Information in Multilayer Networks. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Jan 17]. Available from: http://resolver.tudelft.nl/uuid:a0dbb6da-9a53-4de1-92a0-9cd955486b94.

Council of Science Editors:

Nikolopoulos D(. Link Prediction using Temporal Information in Multilayer Networks. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:a0dbb6da-9a53-4de1-92a0-9cd955486b94


University of Cincinnati

6. Mendu, Prasad Reddy. Link Prediction in Time-Evolving Graphs.

Degree: MS, Engineering and Applied Science: Computer Science, 2016, University of Cincinnati

 With the increase in number of social networks and technological advancements in the last two decades, there is vast amount of digital communication happening between… (more)

Subjects/Keywords: Computer Science; link prediction; graphs; time-evolving

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mendu, P. R. (2016). Link Prediction in Time-Evolving Graphs. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1470757663

Chicago Manual of Style (16th Edition):

Mendu, Prasad Reddy. “Link Prediction in Time-Evolving Graphs.” 2016. Masters Thesis, University of Cincinnati. Accessed January 17, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1470757663.

MLA Handbook (7th Edition):

Mendu, Prasad Reddy. “Link Prediction in Time-Evolving Graphs.” 2016. Web. 17 Jan 2021.

Vancouver:

Mendu PR. Link Prediction in Time-Evolving Graphs. [Internet] [Masters thesis]. University of Cincinnati; 2016. [cited 2021 Jan 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1470757663.

Council of Science Editors:

Mendu PR. Link Prediction in Time-Evolving Graphs. [Masters Thesis]. University of Cincinnati; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1470757663


University of Sydney

7. Choudhury, Nazim Ahmed. Mining Time-aware Actor-level Evolution Similarity for Link Prediction in Dynamic Network .

Degree: 2018, University of Sydney

 Topological evolution over time in a dynamic network triggers both the addition and deletion of actors and the links among them. A dynamic network can… (more)

Subjects/Keywords: dynamic similarity metrics; link prediction; dynamic networks; optimal sampling; supervised dynamic link prediction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Choudhury, N. A. (2018). Mining Time-aware Actor-level Evolution Similarity for Link Prediction in Dynamic Network . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/18640

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Choudhury, Nazim Ahmed. “Mining Time-aware Actor-level Evolution Similarity for Link Prediction in Dynamic Network .” 2018. Thesis, University of Sydney. Accessed January 17, 2021. http://hdl.handle.net/2123/18640.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Choudhury, Nazim Ahmed. “Mining Time-aware Actor-level Evolution Similarity for Link Prediction in Dynamic Network .” 2018. Web. 17 Jan 2021.

Vancouver:

Choudhury NA. Mining Time-aware Actor-level Evolution Similarity for Link Prediction in Dynamic Network . [Internet] [Thesis]. University of Sydney; 2018. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/2123/18640.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Choudhury NA. Mining Time-aware Actor-level Evolution Similarity for Link Prediction in Dynamic Network . [Thesis]. University of Sydney; 2018. Available from: http://hdl.handle.net/2123/18640

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


San Jose State University

8. Chavan, Neeraj. Higher-order Link Prediction Using Graph Embeddings.

Degree: MS, Computer Science, 2020, San Jose State University

Link prediction is an emerging field that predicts if two nodes in a network are likely to be connected or not in the near… (more)

Subjects/Keywords: link prediction; triangle prediction; node2vec; graph2vec; graph neural networks; Other Computer Sciences; Theory and Algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chavan, N. (2020). Higher-order Link Prediction Using Graph Embeddings. (Masters Thesis). San Jose State University. Retrieved from https://scholarworks.sjsu.edu/etd_projects/934

Chicago Manual of Style (16th Edition):

Chavan, Neeraj. “Higher-order Link Prediction Using Graph Embeddings.” 2020. Masters Thesis, San Jose State University. Accessed January 17, 2021. https://scholarworks.sjsu.edu/etd_projects/934.

MLA Handbook (7th Edition):

Chavan, Neeraj. “Higher-order Link Prediction Using Graph Embeddings.” 2020. Web. 17 Jan 2021.

Vancouver:

Chavan N. Higher-order Link Prediction Using Graph Embeddings. [Internet] [Masters thesis]. San Jose State University; 2020. [cited 2021 Jan 17]. Available from: https://scholarworks.sjsu.edu/etd_projects/934.

Council of Science Editors:

Chavan N. Higher-order Link Prediction Using Graph Embeddings. [Masters Thesis]. San Jose State University; 2020. Available from: https://scholarworks.sjsu.edu/etd_projects/934


Penn State University

9. Akcay, Samet. link age: a factor in link prediction in a social network.

Degree: 2015, Penn State University

 This work extends a previous one that investigated link age and its effect on network evolu- tion. Whether aging adversely influences prediction power of links… (more)

Subjects/Keywords: Social Network; Link Prediction; Prediction Power; Network Theory; Mixture Model; Logistic Regression

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Akcay, S. (2015). link age: a factor in link prediction in a social network. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/25789

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Akcay, Samet. “link age: a factor in link prediction in a social network.” 2015. Thesis, Penn State University. Accessed January 17, 2021. https://submit-etda.libraries.psu.edu/catalog/25789.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Akcay, Samet. “link age: a factor in link prediction in a social network.” 2015. Web. 17 Jan 2021.

Vancouver:

Akcay S. link age: a factor in link prediction in a social network. [Internet] [Thesis]. Penn State University; 2015. [cited 2021 Jan 17]. Available from: https://submit-etda.libraries.psu.edu/catalog/25789.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Akcay S. link age: a factor in link prediction in a social network. [Thesis]. Penn State University; 2015. Available from: https://submit-etda.libraries.psu.edu/catalog/25789

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

10. Huo, Zepeng. Link Prediction with Personalized Social Influence.

Degree: MS, Computer Engineering, 2017, Texas A&M University

Link prediction in social networks is to infer the new links likely to be formed next or to reconstruct the links that are currently missing.… (more)

Subjects/Keywords: Social Networks; Link Prediction; Social Influence; Time-series; Social Activity

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APA (6th Edition):

Huo, Z. (2017). Link Prediction with Personalized Social Influence. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173155

Chicago Manual of Style (16th Edition):

Huo, Zepeng. “Link Prediction with Personalized Social Influence.” 2017. Masters Thesis, Texas A&M University. Accessed January 17, 2021. http://hdl.handle.net/1969.1/173155.

MLA Handbook (7th Edition):

Huo, Zepeng. “Link Prediction with Personalized Social Influence.” 2017. Web. 17 Jan 2021.

Vancouver:

Huo Z. Link Prediction with Personalized Social Influence. [Internet] [Masters thesis]. Texas A&M University; 2017. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/1969.1/173155.

Council of Science Editors:

Huo Z. Link Prediction with Personalized Social Influence. [Masters Thesis]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/173155


Penn State University

11. Chen, Hung-hsuan. Identifying Similar Objects in Social Networks and Digital Libraries.

Degree: 2013, Penn State University

 With the rise of the computer age, various kinds of information can be easily accessed in digital format. However, the objects found within this information,… (more)

Subjects/Keywords: link prediction; vertex similarity; expert search; social network

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APA (6th Edition):

Chen, H. (2013). Identifying Similar Objects in Social Networks and Digital Libraries. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/19753

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chen, Hung-hsuan. “Identifying Similar Objects in Social Networks and Digital Libraries.” 2013. Thesis, Penn State University. Accessed January 17, 2021. https://submit-etda.libraries.psu.edu/catalog/19753.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chen, Hung-hsuan. “Identifying Similar Objects in Social Networks and Digital Libraries.” 2013. Web. 17 Jan 2021.

Vancouver:

Chen H. Identifying Similar Objects in Social Networks and Digital Libraries. [Internet] [Thesis]. Penn State University; 2013. [cited 2021 Jan 17]. Available from: https://submit-etda.libraries.psu.edu/catalog/19753.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chen H. Identifying Similar Objects in Social Networks and Digital Libraries. [Thesis]. Penn State University; 2013. Available from: https://submit-etda.libraries.psu.edu/catalog/19753

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


King Abdullah University of Science and Technology

12. Akujuobi, Uchenna Thankgod. Link Label Prediction in Signed Citation Network.

Degree: 2016, King Abdullah University of Science and Technology

Link label prediction is the problem of predicting the missing labels or signs of all the unlabeled edges in a network. For signed networks, these… (more)

Subjects/Keywords: link label prediction; citation network; signed network; label propagation; pageRank; SVM

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APA (6th Edition):

Akujuobi, U. T. (2016). Link Label Prediction in Signed Citation Network. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/607760

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Akujuobi, Uchenna Thankgod. “Link Label Prediction in Signed Citation Network.” 2016. Thesis, King Abdullah University of Science and Technology. Accessed January 17, 2021. http://hdl.handle.net/10754/607760.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Akujuobi, Uchenna Thankgod. “Link Label Prediction in Signed Citation Network.” 2016. Web. 17 Jan 2021.

Vancouver:

Akujuobi UT. Link Label Prediction in Signed Citation Network. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2016. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10754/607760.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Akujuobi UT. Link Label Prediction in Signed Citation Network. [Thesis]. King Abdullah University of Science and Technology; 2016. Available from: http://hdl.handle.net/10754/607760

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

13. Brouard, Céline. Inférence de réseaux d'interaction protéine-protéine par apprentissage statistique : Protein-protein interaction network inference using statistical learning.

Degree: Docteur es, Bioinformatique, 2013, Evry-Val d'Essonne

L'objectif de cette thèse est de développer des outils de prédiction d'interactions entre protéines qui puissent être appliqués en particulier sur le réseau d’interaction autour… (more)

Subjects/Keywords: Prédiction de liens; Link prediction; Kernel methods; Protein-protein interaction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Brouard, C. (2013). Inférence de réseaux d'interaction protéine-protéine par apprentissage statistique : Protein-protein interaction network inference using statistical learning. (Doctoral Dissertation). Evry-Val d'Essonne. Retrieved from http://www.theses.fr/2013EVRY0006

Chicago Manual of Style (16th Edition):

Brouard, Céline. “Inférence de réseaux d'interaction protéine-protéine par apprentissage statistique : Protein-protein interaction network inference using statistical learning.” 2013. Doctoral Dissertation, Evry-Val d'Essonne. Accessed January 17, 2021. http://www.theses.fr/2013EVRY0006.

MLA Handbook (7th Edition):

Brouard, Céline. “Inférence de réseaux d'interaction protéine-protéine par apprentissage statistique : Protein-protein interaction network inference using statistical learning.” 2013. Web. 17 Jan 2021.

Vancouver:

Brouard C. Inférence de réseaux d'interaction protéine-protéine par apprentissage statistique : Protein-protein interaction network inference using statistical learning. [Internet] [Doctoral dissertation]. Evry-Val d'Essonne; 2013. [cited 2021 Jan 17]. Available from: http://www.theses.fr/2013EVRY0006.

Council of Science Editors:

Brouard C. Inférence de réseaux d'interaction protéine-protéine par apprentissage statistique : Protein-protein interaction network inference using statistical learning. [Doctoral Dissertation]. Evry-Val d'Essonne; 2013. Available from: http://www.theses.fr/2013EVRY0006


Indiana University

14. Seal, Abhik. RANDOM WALK APPLIED TO HETEROGENOUS DRUG-TARGET NETWORKS FOR PREDICTING BIOLOGICAL OUTCOMES .

Degree: 2016, Indiana University

Prediction of unknown drug target interactions from bioassay data is critical not only for the understanding of various interactions but also crucial for the development… (more)

Subjects/Keywords: Random walk; drug target; link prediction; disease; metabolic pathway; R; Shiny

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APA (6th Edition):

Seal, A. (2016). RANDOM WALK APPLIED TO HETEROGENOUS DRUG-TARGET NETWORKS FOR PREDICTING BIOLOGICAL OUTCOMES . (Thesis). Indiana University. Retrieved from http://hdl.handle.net/2022/20765

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Seal, Abhik. “RANDOM WALK APPLIED TO HETEROGENOUS DRUG-TARGET NETWORKS FOR PREDICTING BIOLOGICAL OUTCOMES .” 2016. Thesis, Indiana University. Accessed January 17, 2021. http://hdl.handle.net/2022/20765.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Seal, Abhik. “RANDOM WALK APPLIED TO HETEROGENOUS DRUG-TARGET NETWORKS FOR PREDICTING BIOLOGICAL OUTCOMES .” 2016. Web. 17 Jan 2021.

Vancouver:

Seal A. RANDOM WALK APPLIED TO HETEROGENOUS DRUG-TARGET NETWORKS FOR PREDICTING BIOLOGICAL OUTCOMES . [Internet] [Thesis]. Indiana University; 2016. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/2022/20765.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Seal A. RANDOM WALK APPLIED TO HETEROGENOUS DRUG-TARGET NETWORKS FOR PREDICTING BIOLOGICAL OUTCOMES . [Thesis]. Indiana University; 2016. Available from: http://hdl.handle.net/2022/20765

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

15. Száva, Antal (author). Quantum network routing via link prediction.

Degree: 2019, Delft University of Technology

 A network of devices capable of transmitting quantum information called a quantum network has promising applications with vast benefits. One of the most near term… (more)

Subjects/Keywords: quantum network routing; link prediction; temporal networks; information propagation

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APA (6th Edition):

Száva, A. (. (2019). Quantum network routing via link prediction. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:d5836f9d-820a-428e-9ed7-cc8e7c3cbcbb

Chicago Manual of Style (16th Edition):

Száva, Antal (author). “Quantum network routing via link prediction.” 2019. Masters Thesis, Delft University of Technology. Accessed January 17, 2021. http://resolver.tudelft.nl/uuid:d5836f9d-820a-428e-9ed7-cc8e7c3cbcbb.

MLA Handbook (7th Edition):

Száva, Antal (author). “Quantum network routing via link prediction.” 2019. Web. 17 Jan 2021.

Vancouver:

Száva A(. Quantum network routing via link prediction. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Jan 17]. Available from: http://resolver.tudelft.nl/uuid:d5836f9d-820a-428e-9ed7-cc8e7c3cbcbb.

Council of Science Editors:

Száva A(. Quantum network routing via link prediction. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:d5836f9d-820a-428e-9ed7-cc8e7c3cbcbb


University of Notre Dame

16. Yang Yang. Network Dynamics: A Social Influence Perspective</h1>.

Degree: Computer Science and Engineering, 2015, University of Notre Dame

  What drives the propensity for the social network dynamics? Social influence is believed to drive both off-line and on-line human behavior, however it has… (more)

Subjects/Keywords: link prediction; social network analysis; social influence; social network evolution

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yang, Y. (2015). Network Dynamics: A Social Influence Perspective</h1>. (Thesis). University of Notre Dame. Retrieved from https://curate.nd.edu/show/z029p269s21

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Yang, Yang. “Network Dynamics: A Social Influence Perspective</h1>.” 2015. Thesis, University of Notre Dame. Accessed January 17, 2021. https://curate.nd.edu/show/z029p269s21.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Yang, Yang. “Network Dynamics: A Social Influence Perspective</h1>.” 2015. Web. 17 Jan 2021.

Vancouver:

Yang Y. Network Dynamics: A Social Influence Perspective</h1>. [Internet] [Thesis]. University of Notre Dame; 2015. [cited 2021 Jan 17]. Available from: https://curate.nd.edu/show/z029p269s21.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yang Y. Network Dynamics: A Social Influence Perspective</h1>. [Thesis]. University of Notre Dame; 2015. Available from: https://curate.nd.edu/show/z029p269s21

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Windsor

17. Ragunathan, Kumaran. Convolutional Neural Network for Link Prediction Based on Subgraphs in Social Networks.

Degree: MS, Computer Science, 2020, University of Windsor

Link Prediction (LP) in social networks (SN) is referred to as predicting the likelihood of a link formation in SNs in the near future. There… (more)

Subjects/Keywords: Convolutional Neural Network; Link Prediction; Machine Learning; PLACN; Social Network Analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ragunathan, K. (2020). Convolutional Neural Network for Link Prediction Based on Subgraphs in Social Networks. (Masters Thesis). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/8308

Chicago Manual of Style (16th Edition):

Ragunathan, Kumaran. “Convolutional Neural Network for Link Prediction Based on Subgraphs in Social Networks.” 2020. Masters Thesis, University of Windsor. Accessed January 17, 2021. https://scholar.uwindsor.ca/etd/8308.

MLA Handbook (7th Edition):

Ragunathan, Kumaran. “Convolutional Neural Network for Link Prediction Based on Subgraphs in Social Networks.” 2020. Web. 17 Jan 2021.

Vancouver:

Ragunathan K. Convolutional Neural Network for Link Prediction Based on Subgraphs in Social Networks. [Internet] [Masters thesis]. University of Windsor; 2020. [cited 2021 Jan 17]. Available from: https://scholar.uwindsor.ca/etd/8308.

Council of Science Editors:

Ragunathan K. Convolutional Neural Network for Link Prediction Based on Subgraphs in Social Networks. [Masters Thesis]. University of Windsor; 2020. Available from: https://scholar.uwindsor.ca/etd/8308


University of Maryland

18. Skaggs, Bradley Alan. Topic Modeling for Wikipedia Link Disambiguation.

Degree: Computer Science, 2011, University of Maryland

 Many articles in the online encyclopedia Wikipedia have hyperlinks to ambiguous article titles. To improve the reader experience, any link to an ambiguous title should… (more)

Subjects/Keywords: Computer science; disambiguation; link prediction; topic modeling; wikipedia

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Skaggs, B. A. (2011). Topic Modeling for Wikipedia Link Disambiguation. (Thesis). University of Maryland. Retrieved from http://hdl.handle.net/1903/12383

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Skaggs, Bradley Alan. “Topic Modeling for Wikipedia Link Disambiguation.” 2011. Thesis, University of Maryland. Accessed January 17, 2021. http://hdl.handle.net/1903/12383.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Skaggs, Bradley Alan. “Topic Modeling for Wikipedia Link Disambiguation.” 2011. Web. 17 Jan 2021.

Vancouver:

Skaggs BA. Topic Modeling for Wikipedia Link Disambiguation. [Internet] [Thesis]. University of Maryland; 2011. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/1903/12383.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Skaggs BA. Topic Modeling for Wikipedia Link Disambiguation. [Thesis]. University of Maryland; 2011. Available from: http://hdl.handle.net/1903/12383

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

19. Coskun, Mustafa, Coskun. ALGEBRAIC METHODS FOR LINK PREDICTIONIN VERY LARGE NETWORKS.

Degree: PhD, EECS - Computer Engineering, 2017, Case Western Reserve University School of Graduate Studies

Link prediction is at the heart of a large class of network analytics and information retrieval techniques, including recommendation systems, threat detection, and disease gene… (more)

Subjects/Keywords: Computer Science; Random Walk with Restarts, Link Prediction, Network Proximity Queries

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Coskun, Mustafa, C. (2017). ALGEBRAIC METHODS FOR LINK PREDICTIONIN VERY LARGE NETWORKS. (Doctoral Dissertation). Case Western Reserve University School of Graduate Studies. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1499436242956926

Chicago Manual of Style (16th Edition):

Coskun, Mustafa, Coskun. “ALGEBRAIC METHODS FOR LINK PREDICTIONIN VERY LARGE NETWORKS.” 2017. Doctoral Dissertation, Case Western Reserve University School of Graduate Studies. Accessed January 17, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1499436242956926.

MLA Handbook (7th Edition):

Coskun, Mustafa, Coskun. “ALGEBRAIC METHODS FOR LINK PREDICTIONIN VERY LARGE NETWORKS.” 2017. Web. 17 Jan 2021.

Vancouver:

Coskun, Mustafa C. ALGEBRAIC METHODS FOR LINK PREDICTIONIN VERY LARGE NETWORKS. [Internet] [Doctoral dissertation]. Case Western Reserve University School of Graduate Studies; 2017. [cited 2021 Jan 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1499436242956926.

Council of Science Editors:

Coskun, Mustafa C. ALGEBRAIC METHODS FOR LINK PREDICTIONIN VERY LARGE NETWORKS. [Doctoral Dissertation]. Case Western Reserve University School of Graduate Studies; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1499436242956926


University of Cincinnati

20. Rawashdeh, Ahmad. Semantic Similarity of Node Profiles in Social Networks.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2015, University of Cincinnati

 It can be said, without exaggeration, that social networks have taken a large segment of populationby a storm. Regardless of the actual geographical location, of… (more)

Subjects/Keywords: Computer Science; Social Networks; Wordnet; Semantic; Machine Learning; Link Prediction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Rawashdeh, A. (2015). Semantic Similarity of Node Profiles in Social Networks. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439279922

Chicago Manual of Style (16th Edition):

Rawashdeh, Ahmad. “Semantic Similarity of Node Profiles in Social Networks.” 2015. Doctoral Dissertation, University of Cincinnati. Accessed January 17, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439279922.

MLA Handbook (7th Edition):

Rawashdeh, Ahmad. “Semantic Similarity of Node Profiles in Social Networks.” 2015. Web. 17 Jan 2021.

Vancouver:

Rawashdeh A. Semantic Similarity of Node Profiles in Social Networks. [Internet] [Doctoral dissertation]. University of Cincinnati; 2015. [cited 2021 Jan 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439279922.

Council of Science Editors:

Rawashdeh A. Semantic Similarity of Node Profiles in Social Networks. [Doctoral Dissertation]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439279922


Purdue University

21. Rahman, Mahmudur. Graphlet based network analysis.

Degree: PhD, Computer Science, 2016, Purdue University

  The majority of the existing works on network analysis, study properties that are related to the global topology of a network. Examples of such… (more)

Subjects/Keywords: Applied sciences; Graphlet; Graphs; Link prediction; Network; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Rahman, M. (2016). Graphlet based network analysis. (Doctoral Dissertation). Purdue University. Retrieved from https://docs.lib.purdue.edu/open_access_dissertations/992

Chicago Manual of Style (16th Edition):

Rahman, Mahmudur. “Graphlet based network analysis.” 2016. Doctoral Dissertation, Purdue University. Accessed January 17, 2021. https://docs.lib.purdue.edu/open_access_dissertations/992.

MLA Handbook (7th Edition):

Rahman, Mahmudur. “Graphlet based network analysis.” 2016. Web. 17 Jan 2021.

Vancouver:

Rahman M. Graphlet based network analysis. [Internet] [Doctoral dissertation]. Purdue University; 2016. [cited 2021 Jan 17]. Available from: https://docs.lib.purdue.edu/open_access_dissertations/992.

Council of Science Editors:

Rahman M. Graphlet based network analysis. [Doctoral Dissertation]. Purdue University; 2016. Available from: https://docs.lib.purdue.edu/open_access_dissertations/992


Delft University of Technology

22. Li, Ziyu (author). Diffusion based temporal network embedding for link prediction.

Degree: 2019, Delft University of Technology

Link prediction in complex networks has attracted increasing attention. The link prediction algorithms can be used to retrieve missing information, identify spurious interactions, capturing net-… (more)

Subjects/Keywords: Temporal Network Embedding; Link Prediction; Complex Network Analysis; Information Spreading

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Li, Z. (. (2019). Diffusion based temporal network embedding for link prediction. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:5efbbf13-76b0-4fcf-848c-a7971c92e499

Chicago Manual of Style (16th Edition):

Li, Ziyu (author). “Diffusion based temporal network embedding for link prediction.” 2019. Masters Thesis, Delft University of Technology. Accessed January 17, 2021. http://resolver.tudelft.nl/uuid:5efbbf13-76b0-4fcf-848c-a7971c92e499.

MLA Handbook (7th Edition):

Li, Ziyu (author). “Diffusion based temporal network embedding for link prediction.” 2019. Web. 17 Jan 2021.

Vancouver:

Li Z(. Diffusion based temporal network embedding for link prediction. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Jan 17]. Available from: http://resolver.tudelft.nl/uuid:5efbbf13-76b0-4fcf-848c-a7971c92e499.

Council of Science Editors:

Li Z(. Diffusion based temporal network embedding for link prediction. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:5efbbf13-76b0-4fcf-848c-a7971c92e499


Lehigh University

23. Yin, Dawei. Prediction and Recommendation in Online Media.

Degree: PhD, Computer Science, 2013, Lehigh University

 With billions of internet users, online media services have become commonplace. Prediction and recommendation for online media are fundamental problems in various applications, including recommender… (more)

Subjects/Keywords: link prediction; prediction; recommendation; sponsored search; tag prediction; user online behaviors; Computer Sciences; Physical Sciences and Mathematics

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APA (6th Edition):

Yin, D. (2013). Prediction and Recommendation in Online Media. (Doctoral Dissertation). Lehigh University. Retrieved from https://preserve.lehigh.edu/etd/1683

Chicago Manual of Style (16th Edition):

Yin, Dawei. “Prediction and Recommendation in Online Media.” 2013. Doctoral Dissertation, Lehigh University. Accessed January 17, 2021. https://preserve.lehigh.edu/etd/1683.

MLA Handbook (7th Edition):

Yin, Dawei. “Prediction and Recommendation in Online Media.” 2013. Web. 17 Jan 2021.

Vancouver:

Yin D. Prediction and Recommendation in Online Media. [Internet] [Doctoral dissertation]. Lehigh University; 2013. [cited 2021 Jan 17]. Available from: https://preserve.lehigh.edu/etd/1683.

Council of Science Editors:

Yin D. Prediction and Recommendation in Online Media. [Doctoral Dissertation]. Lehigh University; 2013. Available from: https://preserve.lehigh.edu/etd/1683


University of Colorado

24. Ghasemian, Amir. Limits of Model Selection, Link Prediction, and Community Detection.

Degree: PhD, 2019, University of Colorado

  Relational data has become increasingly ubiquitous nowadays. Networks are very rich tools in graph theory, which represent real world interactions through a simple abstract… (more)

Subjects/Keywords: community detection; link description; link prediction; model selection; overfitting; underfitting; Artificial Intelligence and Robotics; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ghasemian, A. (2019). Limits of Model Selection, Link Prediction, and Community Detection. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/csci_gradetds/206

Chicago Manual of Style (16th Edition):

Ghasemian, Amir. “Limits of Model Selection, Link Prediction, and Community Detection.” 2019. Doctoral Dissertation, University of Colorado. Accessed January 17, 2021. https://scholar.colorado.edu/csci_gradetds/206.

MLA Handbook (7th Edition):

Ghasemian, Amir. “Limits of Model Selection, Link Prediction, and Community Detection.” 2019. Web. 17 Jan 2021.

Vancouver:

Ghasemian A. Limits of Model Selection, Link Prediction, and Community Detection. [Internet] [Doctoral dissertation]. University of Colorado; 2019. [cited 2021 Jan 17]. Available from: https://scholar.colorado.edu/csci_gradetds/206.

Council of Science Editors:

Ghasemian A. Limits of Model Selection, Link Prediction, and Community Detection. [Doctoral Dissertation]. University of Colorado; 2019. Available from: https://scholar.colorado.edu/csci_gradetds/206

25. Arnoux, Thibaud. Prédiction d'interactions dans les flots de liens. Combiner les caractéristiques structurelles et temporelles : Predicting interactions in link streams : combining structural and temporal features.

Degree: Docteur es, Informatique, 2018, Sorbonne université

Le formalisme des flots de liens représente une approche permettant de conserver la dynamique du système tout en fournissant un cadre d'étude solide pour appréhender… (more)

Subjects/Keywords: Prédiction de liens; Flot de liens; Prédiction de séries temporelles; Réseaux sociaux; Systèmes complexes; Graphes; Link prediction; Link stream; Time series prediction; Social networks; Complex networks; Graphs; 006.754

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APA (6th Edition):

Arnoux, T. (2018). Prédiction d'interactions dans les flots de liens. Combiner les caractéristiques structurelles et temporelles : Predicting interactions in link streams : combining structural and temporal features. (Doctoral Dissertation). Sorbonne université. Retrieved from http://www.theses.fr/2018SORUS229

Chicago Manual of Style (16th Edition):

Arnoux, Thibaud. “Prédiction d'interactions dans les flots de liens. Combiner les caractéristiques structurelles et temporelles : Predicting interactions in link streams : combining structural and temporal features.” 2018. Doctoral Dissertation, Sorbonne université. Accessed January 17, 2021. http://www.theses.fr/2018SORUS229.

MLA Handbook (7th Edition):

Arnoux, Thibaud. “Prédiction d'interactions dans les flots de liens. Combiner les caractéristiques structurelles et temporelles : Predicting interactions in link streams : combining structural and temporal features.” 2018. Web. 17 Jan 2021.

Vancouver:

Arnoux T. Prédiction d'interactions dans les flots de liens. Combiner les caractéristiques structurelles et temporelles : Predicting interactions in link streams : combining structural and temporal features. [Internet] [Doctoral dissertation]. Sorbonne université; 2018. [cited 2021 Jan 17]. Available from: http://www.theses.fr/2018SORUS229.

Council of Science Editors:

Arnoux T. Prédiction d'interactions dans les flots de liens. Combiner les caractéristiques structurelles et temporelles : Predicting interactions in link streams : combining structural and temporal features. [Doctoral Dissertation]. Sorbonne université; 2018. Available from: http://www.theses.fr/2018SORUS229

26. Rebaza, Jorge Carlos Valverde. Predição de links em redes complexas utilizando informações de estruturas de comunidades.

Degree: Mestrado, Ciências de Computação e Matemática Computacional, 2013, University of São Paulo

Diferentes sistemas do mundo real podem ser representados por redes. As redes são estruturas nas quais seus vértices (nós) representam entidades e links representam relações… (more)

Subjects/Keywords: Community detection; Complex netwoprks; Detecção de comunidades; Link prediction; Predição de links; Redes complexas

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Rebaza, J. C. V. (2013). Predição de links em redes complexas utilizando informações de estruturas de comunidades. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-05062013-104308/ ;

Chicago Manual of Style (16th Edition):

Rebaza, Jorge Carlos Valverde. “Predição de links em redes complexas utilizando informações de estruturas de comunidades.” 2013. Masters Thesis, University of São Paulo. Accessed January 17, 2021. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-05062013-104308/ ;.

MLA Handbook (7th Edition):

Rebaza, Jorge Carlos Valverde. “Predição de links em redes complexas utilizando informações de estruturas de comunidades.” 2013. Web. 17 Jan 2021.

Vancouver:

Rebaza JCV. Predição de links em redes complexas utilizando informações de estruturas de comunidades. [Internet] [Masters thesis]. University of São Paulo; 2013. [cited 2021 Jan 17]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-05062013-104308/ ;.

Council of Science Editors:

Rebaza JCV. Predição de links em redes complexas utilizando informações de estruturas de comunidades. [Masters Thesis]. University of São Paulo; 2013. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-05062013-104308/ ;


University of Oulu

27. Huusko, J. (Jarkko). Communication performance prediction and link adaptation based on a statistical radio channel model.

Degree: 2016, University of Oulu

Abstract This thesis seeks to develop a robust semi-analytical performance prediction method for an advanced iterative receiver that processes spatially multiplexed signals that have propagated… (more)

Subjects/Keywords: EXIT charts; link adaptation; performance prediction; EXIT-kartat; lähetyksen mukauttaminen; suorituskyvyn ennustaminen; HARQ; MIMO

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APA (6th Edition):

Huusko, J. (. (2016). Communication performance prediction and link adaptation based on a statistical radio channel model. (Doctoral Dissertation). University of Oulu. Retrieved from http://urn.fi/urn:isbn:9789526211473

Chicago Manual of Style (16th Edition):

Huusko, J (Jarkko). “Communication performance prediction and link adaptation based on a statistical radio channel model.” 2016. Doctoral Dissertation, University of Oulu. Accessed January 17, 2021. http://urn.fi/urn:isbn:9789526211473.

MLA Handbook (7th Edition):

Huusko, J (Jarkko). “Communication performance prediction and link adaptation based on a statistical radio channel model.” 2016. Web. 17 Jan 2021.

Vancouver:

Huusko J(. Communication performance prediction and link adaptation based on a statistical radio channel model. [Internet] [Doctoral dissertation]. University of Oulu; 2016. [cited 2021 Jan 17]. Available from: http://urn.fi/urn:isbn:9789526211473.

Council of Science Editors:

Huusko J(. Communication performance prediction and link adaptation based on a statistical radio channel model. [Doctoral Dissertation]. University of Oulu; 2016. Available from: http://urn.fi/urn:isbn:9789526211473


Penn State University

28. Qiu, Baojun. SOCIAL NETWORK MODELING, LINK PREDICTION, AND SENTIMENT IMPACT ANALYSIS .

Degree: 2011, Penn State University

 Social network dynamics analysis is one of the most important fields in social network analysis. It studies the temporal network structure and impacts on actors… (more)

Subjects/Keywords: temporal data mining; machine learning; Social network analysis; text mining; sentiment analysis; link prediction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Qiu, B. (2011). SOCIAL NETWORK MODELING, LINK PREDICTION, AND SENTIMENT IMPACT ANALYSIS . (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/12409

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Qiu, Baojun. “SOCIAL NETWORK MODELING, LINK PREDICTION, AND SENTIMENT IMPACT ANALYSIS .” 2011. Thesis, Penn State University. Accessed January 17, 2021. https://submit-etda.libraries.psu.edu/catalog/12409.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Qiu, Baojun. “SOCIAL NETWORK MODELING, LINK PREDICTION, AND SENTIMENT IMPACT ANALYSIS .” 2011. Web. 17 Jan 2021.

Vancouver:

Qiu B. SOCIAL NETWORK MODELING, LINK PREDICTION, AND SENTIMENT IMPACT ANALYSIS . [Internet] [Thesis]. Penn State University; 2011. [cited 2021 Jan 17]. Available from: https://submit-etda.libraries.psu.edu/catalog/12409.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Qiu B. SOCIAL NETWORK MODELING, LINK PREDICTION, AND SENTIMENT IMPACT ANALYSIS . [Thesis]. Penn State University; 2011. Available from: https://submit-etda.libraries.psu.edu/catalog/12409

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

29. Richard, Émile. Regularization methods for prediction in dynamic graphs and e-marketing applications : Méthodes régularisées pour la prédiction dans les graphes dynamiques et applications au e-marketing.

Degree: Docteur es, Mathématiques, 2012, Cachan, Ecole normale supérieure

La prédiction de connexions entre objets, basée soit sur une observation bruitée, soit sur une suite d'observations est un problème d'intérêt pour un nombre d'applications… (more)

Subjects/Keywords: Apprentissage statistique; Prédiction de lien; Méthodes régularisées; Machine learning; Link prediction; Regularization methods

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APA (6th Edition):

Richard, . (2012). Regularization methods for prediction in dynamic graphs and e-marketing applications : Méthodes régularisées pour la prédiction dans les graphes dynamiques et applications au e-marketing. (Doctoral Dissertation). Cachan, Ecole normale supérieure. Retrieved from http://www.theses.fr/2012DENS0064

Chicago Manual of Style (16th Edition):

Richard, Émile. “Regularization methods for prediction in dynamic graphs and e-marketing applications : Méthodes régularisées pour la prédiction dans les graphes dynamiques et applications au e-marketing.” 2012. Doctoral Dissertation, Cachan, Ecole normale supérieure. Accessed January 17, 2021. http://www.theses.fr/2012DENS0064.

MLA Handbook (7th Edition):

Richard, Émile. “Regularization methods for prediction in dynamic graphs and e-marketing applications : Méthodes régularisées pour la prédiction dans les graphes dynamiques et applications au e-marketing.” 2012. Web. 17 Jan 2021.

Vancouver:

Richard . Regularization methods for prediction in dynamic graphs and e-marketing applications : Méthodes régularisées pour la prédiction dans les graphes dynamiques et applications au e-marketing. [Internet] [Doctoral dissertation]. Cachan, Ecole normale supérieure; 2012. [cited 2021 Jan 17]. Available from: http://www.theses.fr/2012DENS0064.

Council of Science Editors:

Richard . Regularization methods for prediction in dynamic graphs and e-marketing applications : Méthodes régularisées pour la prédiction dans les graphes dynamiques et applications au e-marketing. [Doctoral Dissertation]. Cachan, Ecole normale supérieure; 2012. Available from: http://www.theses.fr/2012DENS0064


Washington State University

30. [No author]. Link Prediction in Dynamic Networks .

Degree: 2015, Washington State University

Link Prediction in dynamic networks aims to model the patterns of relationship formation between any two agents in a multi-agent network for predicting the future… (more)

Subjects/Keywords: Computer science; Dynamic networks; Feature engineering; Graph mining; Link prediction; Novelty detection; Supervised learning

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APA (6th Edition):

author], [. (2015). Link Prediction in Dynamic Networks . (Thesis). Washington State University. Retrieved from http://hdl.handle.net/2376/6214

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

author], [No. “Link Prediction in Dynamic Networks .” 2015. Thesis, Washington State University. Accessed January 17, 2021. http://hdl.handle.net/2376/6214.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

author], [No. “Link Prediction in Dynamic Networks .” 2015. Web. 17 Jan 2021.

Vancouver:

author] [. Link Prediction in Dynamic Networks . [Internet] [Thesis]. Washington State University; 2015. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/2376/6214.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

author] [. Link Prediction in Dynamic Networks . [Thesis]. Washington State University; 2015. Available from: http://hdl.handle.net/2376/6214

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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