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You searched for subject:(Link prediction). Showing records 1 – 30 of 61 total matches.

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University of Cincinnati

1. 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 June 17, 2019. 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 Jun 2019.

Vancouver:

Mendu PR. Link Prediction in Time-Evolving Graphs. [Internet] [Masters thesis]. University of Cincinnati; 2016. [cited 2019 Jun 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


Université Catholique de Louvain

2. 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 June 17, 2019. 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 Jun 2019.

Vancouver:

Andreotti R. Adaptive techniques for packet-oriented transmissions in future multicarrier wireless systems. [Internet] [Thesis]. Université Catholique de Louvain; 2013. [cited 2019 Jun 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


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 (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 June 17, 2019. http://hdl.handle.net/2027.42/134693.

MLA Handbook (7th Edition):

Cai, Jiarui. “Computational Approaches for Estimating Life Cycle Inventory Data.” 2016. Web. 17 Jun 2019.

Vancouver:

Cai J. Computational Approaches for Estimating Life Cycle Inventory Data. [Internet] [Masters thesis]. University of Michigan; 2016. [cited 2019 Jun 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


University of Notre Dame

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

Degree: PhD, 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>. (Doctoral Dissertation). University of Notre Dame. Retrieved from https://curate.nd.edu/show/fj23611103z

Chicago Manual of Style (16th Edition):

Lichtenwalter, Ryan N.. “Network Analysis and Link Prediction: Effective and Meaningful Modeling and Evaluation</h1>.” 2012. Doctoral Dissertation, University of Notre Dame. Accessed June 17, 2019. https://curate.nd.edu/show/fj23611103z.

MLA Handbook (7th Edition):

Lichtenwalter, Ryan N.. “Network Analysis and Link Prediction: Effective and Meaningful Modeling and Evaluation</h1>.” 2012. Web. 17 Jun 2019.

Vancouver:

Lichtenwalter RN. Network Analysis and Link Prediction: Effective and Meaningful Modeling and Evaluation</h1>. [Internet] [Doctoral dissertation]. University of Notre Dame; 2012. [cited 2019 Jun 17]. Available from: https://curate.nd.edu/show/fj23611103z.

Council of Science Editors:

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


University of Sydney

5. 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 June 17, 2019. 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 Jun 2019.

Vancouver:

Choudhury NA. Mining Time-aware Actor-level Evolution Similarity for Link Prediction in Dynamic Network . [Internet] [Thesis]. University of Sydney; 2018. [cited 2019 Jun 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


Purdue University

6. 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 (6th Edition):

Rahman, M. (2016). Graphlet based network analysis. (Doctoral Dissertation). Purdue University. Retrieved from http://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 June 17, 2019. http://docs.lib.purdue.edu/open_access_dissertations/992.

MLA Handbook (7th Edition):

Rahman, Mahmudur. “Graphlet based network analysis.” 2016. Web. 17 Jun 2019.

Vancouver:

Rahman M. Graphlet based network analysis. [Internet] [Doctoral dissertation]. Purdue University; 2016. [cited 2019 Jun 17]. Available from: http://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: http://docs.lib.purdue.edu/open_access_dissertations/992


Penn State University

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

Degree: PhD, Computer Science and Engineering, 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 · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Chen, Hung-hsuan. “Identifying Similar Objects in Social Networks and Digital Libraries.” 2013. Doctoral Dissertation, Penn State University. Accessed June 17, 2019. https://etda.libraries.psu.edu/catalog/19753.

MLA Handbook (7th Edition):

Chen, Hung-hsuan. “Identifying Similar Objects in Social Networks and Digital Libraries.” 2013. Web. 17 Jun 2019.

Vancouver:

Chen H. Identifying Similar Objects in Social Networks and Digital Libraries. [Internet] [Doctoral dissertation]. Penn State University; 2013. [cited 2019 Jun 17]. Available from: https://etda.libraries.psu.edu/catalog/19753.

Council of Science Editors:

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


Case Western Reserve University

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

Degree: PhD, EECS - Computer Engineering, 2017, Case Western Reserve University

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. 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. Accessed June 17, 2019. 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 Jun 2019.

Vancouver:

Coskun, Mustafa C. ALGEBRAIC METHODS FOR LINK PREDICTIONIN VERY LARGE NETWORKS. [Internet] [Doctoral dissertation]. Case Western Reserve University; 2017. [cited 2019 Jun 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; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1499436242956926


Indiana University

9. 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 June 17, 2019. 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 Jun 2019.

Vancouver:

Seal A. RANDOM WALK APPLIED TO HETEROGENOUS DRUG-TARGET NETWORKS FOR PREDICTING BIOLOGICAL OUTCOMES . [Internet] [Thesis]. Indiana University; 2016. [cited 2019 Jun 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


University of Cincinnati

10. 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 (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 June 17, 2019. 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 Jun 2019.

Vancouver:

Rawashdeh A. Semantic Similarity of Node Profiles in Social Networks. [Internet] [Doctoral dissertation]. University of Cincinnati; 2015. [cited 2019 Jun 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


King Abdullah University of Science and Technology

11. 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 June 17, 2019. 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 Jun 2019.

Vancouver:

Akujuobi UT. Link Label Prediction in Signed Citation Network. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2016. [cited 2019 Jun 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


Boise State University

12. Gundala, Laxmi Amulya. Uncovering New Links Through Interaction Duration.

Degree: 2017, Boise State University

Link Prediction is the problem of inferring new relationships among nodes in a network that can occur in the near future. Classical approaches mainly consider… (more)

Subjects/Keywords: social network analysis; data science; link prediction; machine learning; Computer Sciences

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APA (6th Edition):

Gundala, L. A. (2017). Uncovering New Links Through Interaction Duration. (Thesis). Boise State University. Retrieved from https://scholarworks.boisestate.edu/td/1337

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):

Gundala, Laxmi Amulya. “Uncovering New Links Through Interaction Duration.” 2017. Thesis, Boise State University. Accessed June 17, 2019. https://scholarworks.boisestate.edu/td/1337.

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

MLA Handbook (7th Edition):

Gundala, Laxmi Amulya. “Uncovering New Links Through Interaction Duration.” 2017. Web. 17 Jun 2019.

Vancouver:

Gundala LA. Uncovering New Links Through Interaction Duration. [Internet] [Thesis]. Boise State University; 2017. [cited 2019 Jun 17]. Available from: https://scholarworks.boisestate.edu/td/1337.

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

Council of Science Editors:

Gundala LA. Uncovering New Links Through Interaction Duration. [Thesis]. Boise State University; 2017. Available from: https://scholarworks.boisestate.edu/td/1337

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


Kansas State University

13. Aljandal, Waleed A. Itemset size-sensitive interestingness measures for association rule mining and link prediction.

Degree: PhD, Department of Computing and Information Sciences, 2009, Kansas State University

 Association rule learning is a data mining technique that can capture relationships between pairs of entities in different domains. The goal of this research is… (more)

Subjects/Keywords: Data Mining; Association Rule; Interestingness Measures; Link Prediction; Computer Science (0984)

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APA (6th Edition):

Aljandal, W. A. (2009). Itemset size-sensitive interestingness measures for association rule mining and link prediction. (Doctoral Dissertation). Kansas State University. Retrieved from http://hdl.handle.net/2097/1245

Chicago Manual of Style (16th Edition):

Aljandal, Waleed A. “Itemset size-sensitive interestingness measures for association rule mining and link prediction.” 2009. Doctoral Dissertation, Kansas State University. Accessed June 17, 2019. http://hdl.handle.net/2097/1245.

MLA Handbook (7th Edition):

Aljandal, Waleed A. “Itemset size-sensitive interestingness measures for association rule mining and link prediction.” 2009. Web. 17 Jun 2019.

Vancouver:

Aljandal WA. Itemset size-sensitive interestingness measures for association rule mining and link prediction. [Internet] [Doctoral dissertation]. Kansas State University; 2009. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/2097/1245.

Council of Science Editors:

Aljandal WA. Itemset size-sensitive interestingness measures for association rule mining and link prediction. [Doctoral Dissertation]. Kansas State University; 2009. Available from: http://hdl.handle.net/2097/1245


Kansas State University

14. Parimi, Rohit. LDA based approach for predicting friendship links in live journal social network.

Degree: MS, Department of Computing and Information Sciences, 2010, Kansas State University

 The idea of socializing with other people of different backgrounds and cultures excites the web surfers. Today, there are hundreds of Social Networking sites on… (more)

Subjects/Keywords: Social Network Analysis; Topic Modeling; Friendship Link Prediction; Computer Science (0984)

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APA (6th Edition):

Parimi, R. (2010). LDA based approach for predicting friendship links in live journal social network. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/4624

Chicago Manual of Style (16th Edition):

Parimi, Rohit. “LDA based approach for predicting friendship links in live journal social network.” 2010. Masters Thesis, Kansas State University. Accessed June 17, 2019. http://hdl.handle.net/2097/4624.

MLA Handbook (7th Edition):

Parimi, Rohit. “LDA based approach for predicting friendship links in live journal social network.” 2010. Web. 17 Jun 2019.

Vancouver:

Parimi R. LDA based approach for predicting friendship links in live journal social network. [Internet] [Masters thesis]. Kansas State University; 2010. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/2097/4624.

Council of Science Editors:

Parimi R. LDA based approach for predicting friendship links in live journal social network. [Masters Thesis]. Kansas State University; 2010. Available from: http://hdl.handle.net/2097/4624


University of Notre Dame

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

Degree: PhD, 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 (6th Edition):

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

Chicago Manual of Style (16th Edition):

Yang, Yang. “Network Dynamics: A Social Influence Perspective</h1>.” 2015. Doctoral Dissertation, University of Notre Dame. Accessed June 17, 2019. https://curate.nd.edu/show/z029p269s21.

MLA Handbook (7th Edition):

Yang, Yang. “Network Dynamics: A Social Influence Perspective</h1>.” 2015. Web. 17 Jun 2019.

Vancouver:

Yang Y. Network Dynamics: A Social Influence Perspective</h1>. [Internet] [Doctoral dissertation]. University of Notre Dame; 2015. [cited 2019 Jun 17]. Available from: https://curate.nd.edu/show/z029p269s21.

Council of Science Editors:

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

16. 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 (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 June 17, 2019. 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 Jun 2019.

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 2019 Jun 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


Lehigh University

17. 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 June 17, 2019. https://preserve.lehigh.edu/etd/1683.

MLA Handbook (7th Edition):

Yin, Dawei. “Prediction and Recommendation in Online Media.” 2013. Web. 17 Jun 2019.

Vancouver:

Yin D. Prediction and Recommendation in Online Media. [Internet] [Doctoral dissertation]. Lehigh University; 2013. [cited 2019 Jun 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

18. 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 (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 June 17, 2019. 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 Jun 2019.

Vancouver:

Rebaza JCV. Predição de links em redes complexas utilizando informações de estruturas de comunidades. [Internet] [Masters thesis]. University of São Paulo; 2013. [cited 2019 Jun 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

19. 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 June 17, 2019. 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 Jun 2019.

Vancouver:

Huusko J(. Communication performance prediction and link adaptation based on a statistical radio channel model. [Internet] [Doctoral dissertation]. University of Oulu; 2016. [cited 2019 Jun 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


University of Illinois – Chicago

20. Zhang, Jiawei. Fusion of Heterogeneous Social Networks for Synergistic Knowledge Discovery.

Degree: 2017, University of Illinois – Chicago

 In this thesis, we will focus on introducing the information fusion learning works done based on online social media data. To enjoy more social network… (more)

Subjects/Keywords: Network Fusion; Network Alignment; Link Prediction; Community Detection; Information Diffusion; Network Embedding; Data Mining

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APA (6th Edition):

Zhang, J. (2017). Fusion of Heterogeneous Social Networks for Synergistic Knowledge Discovery. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/22093

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):

Zhang, Jiawei. “Fusion of Heterogeneous Social Networks for Synergistic Knowledge Discovery.” 2017. Thesis, University of Illinois – Chicago. Accessed June 17, 2019. http://hdl.handle.net/10027/22093.

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

MLA Handbook (7th Edition):

Zhang, Jiawei. “Fusion of Heterogeneous Social Networks for Synergistic Knowledge Discovery.” 2017. Web. 17 Jun 2019.

Vancouver:

Zhang J. Fusion of Heterogeneous Social Networks for Synergistic Knowledge Discovery. [Internet] [Thesis]. University of Illinois – Chicago; 2017. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/10027/22093.

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

Council of Science Editors:

Zhang J. Fusion of Heterogeneous Social Networks for Synergistic Knowledge Discovery. [Thesis]. University of Illinois – Chicago; 2017. Available from: http://hdl.handle.net/10027/22093

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


University of Cincinnati

21. Zhang, Minlu. Discovery and Analysis of Patterns in Molecular Networks: Link Prediction, Network Analysis, and Applications to Novel Drug Target Discovery.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2012, University of Cincinnati

  One of the most challenging problems in the post-genomic era for computer scientists and bioinformaticians is to identify meaningful patterns from a huge amount… (more)

Subjects/Keywords: Computer Science; network analysis; link prediction; transcriptional regulation; orphan disease; rare disease; protein-protein interaction

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APA (6th Edition):

Zhang, M. (2012). Discovery and Analysis of Patterns in Molecular Networks: Link Prediction, Network Analysis, and Applications to Novel Drug Target Discovery. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1330024618

Chicago Manual of Style (16th Edition):

Zhang, Minlu. “Discovery and Analysis of Patterns in Molecular Networks: Link Prediction, Network Analysis, and Applications to Novel Drug Target Discovery.” 2012. Doctoral Dissertation, University of Cincinnati. Accessed June 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1330024618.

MLA Handbook (7th Edition):

Zhang, Minlu. “Discovery and Analysis of Patterns in Molecular Networks: Link Prediction, Network Analysis, and Applications to Novel Drug Target Discovery.” 2012. Web. 17 Jun 2019.

Vancouver:

Zhang M. Discovery and Analysis of Patterns in Molecular Networks: Link Prediction, Network Analysis, and Applications to Novel Drug Target Discovery. [Internet] [Doctoral dissertation]. University of Cincinnati; 2012. [cited 2019 Jun 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1330024618.

Council of Science Editors:

Zhang M. Discovery and Analysis of Patterns in Molecular Networks: Link Prediction, Network Analysis, and Applications to Novel Drug Target Discovery. [Doctoral Dissertation]. University of Cincinnati; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1330024618


Penn State University

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

Degree: PhD, Computer Science, 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 (6th Edition):

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

Chicago Manual of Style (16th Edition):

Qiu, Baojun. “SOCIAL NETWORK MODELING, LINK PREDICTION, AND SENTIMENT IMPACT ANALYSIS.” 2011. Doctoral Dissertation, Penn State University. Accessed June 17, 2019. https://etda.libraries.psu.edu/catalog/12409.

MLA Handbook (7th Edition):

Qiu, Baojun. “SOCIAL NETWORK MODELING, LINK PREDICTION, AND SENTIMENT IMPACT ANALYSIS.” 2011. Web. 17 Jun 2019.

Vancouver:

Qiu B. SOCIAL NETWORK MODELING, LINK PREDICTION, AND SENTIMENT IMPACT ANALYSIS. [Internet] [Doctoral dissertation]. Penn State University; 2011. [cited 2019 Jun 17]. Available from: https://etda.libraries.psu.edu/catalog/12409.

Council of Science Editors:

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


Montana Tech

23. Lyon, William. An Adaptive Hybrid Method for Link Prediction in Multi-Modal Directed Complex Networks Using the Graph Traversal Pattern.

Degree: MS, 2014, Montana Tech

  The paper examines the link prediction problem for directed multi-modal complex networks. Specically, a hybrid method combining collaborative filtering and Triadic Closeness methods is… (more)

Subjects/Keywords: recommender systems; link prediction; social networks; machine learning; graph traversal; graph database; Computer Sciences

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APA (6th Edition):

Lyon, W. (2014). An Adaptive Hybrid Method for Link Prediction in Multi-Modal Directed Complex Networks Using the Graph Traversal Pattern. (Masters Thesis). Montana Tech. Retrieved from https://scholarworks.umt.edu/etd/4358

Chicago Manual of Style (16th Edition):

Lyon, William. “An Adaptive Hybrid Method for Link Prediction in Multi-Modal Directed Complex Networks Using the Graph Traversal Pattern.” 2014. Masters Thesis, Montana Tech. Accessed June 17, 2019. https://scholarworks.umt.edu/etd/4358.

MLA Handbook (7th Edition):

Lyon, William. “An Adaptive Hybrid Method for Link Prediction in Multi-Modal Directed Complex Networks Using the Graph Traversal Pattern.” 2014. Web. 17 Jun 2019.

Vancouver:

Lyon W. An Adaptive Hybrid Method for Link Prediction in Multi-Modal Directed Complex Networks Using the Graph Traversal Pattern. [Internet] [Masters thesis]. Montana Tech; 2014. [cited 2019 Jun 17]. Available from: https://scholarworks.umt.edu/etd/4358.

Council of Science Editors:

Lyon W. An Adaptive Hybrid Method for Link Prediction in Multi-Modal Directed Complex Networks Using the Graph Traversal Pattern. [Masters Thesis]. Montana Tech; 2014. Available from: https://scholarworks.umt.edu/etd/4358

24. 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 June 17, 2019. 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 Jun 2019.

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 2019 Jun 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

25. Phanse, Shruti. Study on the performance of ontology based approaches to link prediction in social networks as the number of users increases.

Degree: MS, Department of Computing and Information Sciences, 2010, Kansas State University

 Recent advances in social network applications have resulted in millions of users joining such networks in the last few years. User data collected from social… (more)

Subjects/Keywords: Ontology; Social Networks; Link Prediction; Data Mining Problems; Large dataset; Study Performance; Computer Science (0984)

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APA (6th Edition):

Phanse, S. (2010). Study on the performance of ontology based approaches to link prediction in social networks as the number of users increases. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/6914

Chicago Manual of Style (16th Edition):

Phanse, Shruti. “Study on the performance of ontology based approaches to link prediction in social networks as the number of users increases.” 2010. Masters Thesis, Kansas State University. Accessed June 17, 2019. http://hdl.handle.net/2097/6914.

MLA Handbook (7th Edition):

Phanse, Shruti. “Study on the performance of ontology based approaches to link prediction in social networks as the number of users increases.” 2010. Web. 17 Jun 2019.

Vancouver:

Phanse S. Study on the performance of ontology based approaches to link prediction in social networks as the number of users increases. [Internet] [Masters thesis]. Kansas State University; 2010. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/2097/6914.

Council of Science Editors:

Phanse S. Study on the performance of ontology based approaches to link prediction in social networks as the number of users increases. [Masters Thesis]. Kansas State University; 2010. Available from: http://hdl.handle.net/2097/6914

26. Narasimha, Shiva Sai Sri Harsha Vardhan Kamisetty Jananni. Forecasting Trajectory Data : A study by Experimentation.

Degree: 2017, , Department of Communication Systems

  Context. The advances in location-acquisition and mobile computing techniques have generated massive spatial trajectory data. Such spatial trajectory data accumulated by telecommunication operators is… (more)

Subjects/Keywords: Collapsed weighted tensor method; periodic temporal link prediction; Trajectory data.; Telecommunications; Telekommunikation

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APA (6th Edition):

Narasimha, S. S. S. H. V. K. J. (2017). Forecasting Trajectory Data : A study by Experimentation. (Thesis). , Department of Communication Systems. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13976

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):

Narasimha, Shiva Sai Sri Harsha Vardhan Kamisetty Jananni. “Forecasting Trajectory Data : A study by Experimentation.” 2017. Thesis, , Department of Communication Systems. Accessed June 17, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13976.

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

MLA Handbook (7th Edition):

Narasimha, Shiva Sai Sri Harsha Vardhan Kamisetty Jananni. “Forecasting Trajectory Data : A study by Experimentation.” 2017. Web. 17 Jun 2019.

Vancouver:

Narasimha SSSHVKJ. Forecasting Trajectory Data : A study by Experimentation. [Internet] [Thesis]. , Department of Communication Systems; 2017. [cited 2019 Jun 17]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13976.

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

Council of Science Editors:

Narasimha SSSHVKJ. Forecasting Trajectory Data : A study by Experimentation. [Thesis]. , Department of Communication Systems; 2017. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13976

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


University of Texas – Austin

27. Cho, Tae Won, 1978-. Enabling information-centric networking : architecture, protocols, and applications.

Degree: Computer Sciences, 2010, University of Texas – Austin

 As the Internet is becoming information-centric, network services increasingly demand scalable and efficient communication of information between a multitude of information producers and large groups… (more)

Subjects/Keywords: Information-centric networking; Network protocols; Social networks; Multicast; Networks; Proximity measures; Link prediction

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APA (6th Edition):

Cho, Tae Won, 1. (2010). Enabling information-centric networking : architecture, protocols, and applications. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-1765

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):

Cho, Tae Won, 1978-. “Enabling information-centric networking : architecture, protocols, and applications.” 2010. Thesis, University of Texas – Austin. Accessed June 17, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-1765.

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

MLA Handbook (7th Edition):

Cho, Tae Won, 1978-. “Enabling information-centric networking : architecture, protocols, and applications.” 2010. Web. 17 Jun 2019.

Vancouver:

Cho, Tae Won 1. Enabling information-centric networking : architecture, protocols, and applications. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1765.

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

Council of Science Editors:

Cho, Tae Won 1. Enabling information-centric networking : architecture, protocols, and applications. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1765

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


Washington State University

28. [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 June 17, 2019. 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 Jun 2019.

Vancouver:

author] [. Link Prediction in Dynamic Networks . [Internet] [Thesis]. Washington State University; 2015. [cited 2019 Jun 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

29. Raad, Elie. Découverte des relations dans les réseaux sociaux : Relationship discovery in social networks.

Degree: Docteur es, Informatique, 2011, Université de Bourgogne

Les réseaux sociaux occupent une place de plus en plus importante dans notre vie quotidienne et représentent une part considérable des activités sur le web.… (more)

Subjects/Keywords: Pas de mot clé en français; Relationship discovery; Social networks; Rule-based relationship identification; Coreferent users; Link mining; Link type prediction; Entity resolution; Classification; Crowdsourcing; User profiles; Photos; Metadata; 004.678

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APA (6th Edition):

Raad, E. (2011). Découverte des relations dans les réseaux sociaux : Relationship discovery in social networks. (Doctoral Dissertation). Université de Bourgogne. Retrieved from http://www.theses.fr/2011DIJOS061

Chicago Manual of Style (16th Edition):

Raad, Elie. “Découverte des relations dans les réseaux sociaux : Relationship discovery in social networks.” 2011. Doctoral Dissertation, Université de Bourgogne. Accessed June 17, 2019. http://www.theses.fr/2011DIJOS061.

MLA Handbook (7th Edition):

Raad, Elie. “Découverte des relations dans les réseaux sociaux : Relationship discovery in social networks.” 2011. Web. 17 Jun 2019.

Vancouver:

Raad E. Découverte des relations dans les réseaux sociaux : Relationship discovery in social networks. [Internet] [Doctoral dissertation]. Université de Bourgogne; 2011. [cited 2019 Jun 17]. Available from: http://www.theses.fr/2011DIJOS061.

Council of Science Editors:

Raad E. Découverte des relations dans les réseaux sociaux : Relationship discovery in social networks. [Doctoral Dissertation]. Université de Bourgogne; 2011. Available from: http://www.theses.fr/2011DIJOS061


University of Notre Dame

30. Ryan Nicholas Lichtenwalter. Beyond Static Data: Tackling Class Imbalance and Concept Drift in Data Streams, Link Persistence and Prediction in Dynamic Networks, and Autonomous Composition in Computer Music</h1>.

Degree: MSin Computer Science and Engineering, Computer Science and Engineering, 2009, University of Notre Dame

  This thesis tackles the fundamental issues of streaming data in different challenging scenarios. First, the confounding problem of class imbalance and concept drift is… (more)

Subjects/Keywords: stream mining; class imbalance; link prediction; link persistence; data streams; ensembles; schenkerian analysis; concept drift; classification; autonomous composition; social networks; computer music

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APA (6th Edition):

Lichtenwalter, R. N. (2009). Beyond Static Data: Tackling Class Imbalance and Concept Drift in Data Streams, Link Persistence and Prediction in Dynamic Networks, and Autonomous Composition in Computer Music</h1>. (Masters Thesis). University of Notre Dame. Retrieved from https://curate.nd.edu/show/ws859c70f89

Chicago Manual of Style (16th Edition):

Lichtenwalter, Ryan Nicholas. “Beyond Static Data: Tackling Class Imbalance and Concept Drift in Data Streams, Link Persistence and Prediction in Dynamic Networks, and Autonomous Composition in Computer Music</h1>.” 2009. Masters Thesis, University of Notre Dame. Accessed June 17, 2019. https://curate.nd.edu/show/ws859c70f89.

MLA Handbook (7th Edition):

Lichtenwalter, Ryan Nicholas. “Beyond Static Data: Tackling Class Imbalance and Concept Drift in Data Streams, Link Persistence and Prediction in Dynamic Networks, and Autonomous Composition in Computer Music</h1>.” 2009. Web. 17 Jun 2019.

Vancouver:

Lichtenwalter RN. Beyond Static Data: Tackling Class Imbalance and Concept Drift in Data Streams, Link Persistence and Prediction in Dynamic Networks, and Autonomous Composition in Computer Music</h1>. [Internet] [Masters thesis]. University of Notre Dame; 2009. [cited 2019 Jun 17]. Available from: https://curate.nd.edu/show/ws859c70f89.

Council of Science Editors:

Lichtenwalter RN. Beyond Static Data: Tackling Class Imbalance and Concept Drift in Data Streams, Link Persistence and Prediction in Dynamic Networks, and Autonomous Composition in Computer Music</h1>. [Masters Thesis]. University of Notre Dame; 2009. Available from: https://curate.nd.edu/show/ws859c70f89

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