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You searched for +publisher:"Virginia Tech" +contributor:("Ramakrishnan, Naren"). Showing records 1 – 30 of 162 total matches.

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Virginia Tech

1. Self, Nathan. User Interfaces for an Open Source Indicators Forecasting System.

Degree: MS, Computer Science and Applications, 2015, Virginia Tech

 Intelligence analysts today are faced with many challenges, chief among them being the need to fuse disparate streams of data and rapidly arrive at analytical… (more)

Subjects/Keywords: Visualization; Forecasting; Intelligence Analysis; Open Source Indicators

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APA (6th Edition):

Self, N. (2015). User Interfaces for an Open Source Indicators Forecasting System. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/56696

Chicago Manual of Style (16th Edition):

Self, Nathan. “User Interfaces for an Open Source Indicators Forecasting System.” 2015. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/56696.

MLA Handbook (7th Edition):

Self, Nathan. “User Interfaces for an Open Source Indicators Forecasting System.” 2015. Web. 07 Mar 2021.

Vancouver:

Self N. User Interfaces for an Open Source Indicators Forecasting System. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/56696.

Council of Science Editors:

Self N. User Interfaces for an Open Source Indicators Forecasting System. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/56696


Virginia Tech

2. Wang, Ji. Clustered Layout Word Cloud for User Generated Online Reviews.

Degree: MS, Computer Science and Applications, 2012, Virginia Tech

 User generated reviews, like those found on Yelp and Amazon, have become important refer- ence material in casual decision making, like dining, shopping and entertainment.… (more)

Subjects/Keywords: Word Cloud; Text Visualization; User Study

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APA (6th Edition):

Wang, J. (2012). Clustered Layout Word Cloud for User Generated Online Reviews. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19193

Chicago Manual of Style (16th Edition):

Wang, Ji. “Clustered Layout Word Cloud for User Generated Online Reviews.” 2012. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/19193.

MLA Handbook (7th Edition):

Wang, Ji. “Clustered Layout Word Cloud for User Generated Online Reviews.” 2012. Web. 07 Mar 2021.

Vancouver:

Wang J. Clustered Layout Word Cloud for User Generated Online Reviews. [Internet] [Masters thesis]. Virginia Tech; 2012. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/19193.

Council of Science Editors:

Wang J. Clustered Layout Word Cloud for User Generated Online Reviews. [Masters Thesis]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/19193


Virginia Tech

3. Arefiyan Khalilabad, Seyyed Mostafa. Deep Learning Models for Context-Aware Object Detection.

Degree: MS, Computer Engineering, 2017, Virginia Tech

 In this thesis, we present ContextNet, a novel general object detection framework for incorporating context cues into a detection pipeline. Current deep learning methods for… (more)

Subjects/Keywords: Context-aware Detection; Object Detection; Context Modeling; Context Extraction; Convolutional Neural Network; Computer Vision; Deep Learning; Machine Learning

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APA (6th Edition):

Arefiyan Khalilabad, S. M. (2017). Deep Learning Models for Context-Aware Object Detection. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/88387

Chicago Manual of Style (16th Edition):

Arefiyan Khalilabad, Seyyed Mostafa. “Deep Learning Models for Context-Aware Object Detection.” 2017. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/88387.

MLA Handbook (7th Edition):

Arefiyan Khalilabad, Seyyed Mostafa. “Deep Learning Models for Context-Aware Object Detection.” 2017. Web. 07 Mar 2021.

Vancouver:

Arefiyan Khalilabad SM. Deep Learning Models for Context-Aware Object Detection. [Internet] [Masters thesis]. Virginia Tech; 2017. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/88387.

Council of Science Editors:

Arefiyan Khalilabad SM. Deep Learning Models for Context-Aware Object Detection. [Masters Thesis]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/88387


Virginia Tech

4. Muthiah, Sathappan. Forecasting Protests by Detecting Future Time Mentions in News and Social Media.

Degree: MS, Computer Science and Applications, 2014, Virginia Tech

 Civil unrest (protests, strikes, and ``occupy'' events) is a common occurrence in both democracies and authoritarian regimes. The study of civil unrest is a key… (more)

Subjects/Keywords: Textmining; Information Retrieval; Social Media

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APA (6th Edition):

Muthiah, S. (2014). Forecasting Protests by Detecting Future Time Mentions in News and Social Media. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/49535

Chicago Manual of Style (16th Edition):

Muthiah, Sathappan. “Forecasting Protests by Detecting Future Time Mentions in News and Social Media.” 2014. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/49535.

MLA Handbook (7th Edition):

Muthiah, Sathappan. “Forecasting Protests by Detecting Future Time Mentions in News and Social Media.” 2014. Web. 07 Mar 2021.

Vancouver:

Muthiah S. Forecasting Protests by Detecting Future Time Mentions in News and Social Media. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/49535.

Council of Science Editors:

Muthiah S. Forecasting Protests by Detecting Future Time Mentions in News and Social Media. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/49535


Virginia Tech

5. Choudhry, Arjun. Narrative Generation to Support Causal Exploration of Directed Graphs.

Degree: MS, Computer Science and Applications, 2020, Virginia Tech

 Narrative generation is the art of creating coherent snippets of text that cumulatively describe a succession of events, played across a period of time. These… (more)

Subjects/Keywords: Narrative Generation; Causal Exploration; Natural Language Processing; Graph Inference

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APA (6th Edition):

Choudhry, A. (2020). Narrative Generation to Support Causal Exploration of Directed Graphs. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/98670

Chicago Manual of Style (16th Edition):

Choudhry, Arjun. “Narrative Generation to Support Causal Exploration of Directed Graphs.” 2020. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/98670.

MLA Handbook (7th Edition):

Choudhry, Arjun. “Narrative Generation to Support Causal Exploration of Directed Graphs.” 2020. Web. 07 Mar 2021.

Vancouver:

Choudhry A. Narrative Generation to Support Causal Exploration of Directed Graphs. [Internet] [Masters thesis]. Virginia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/98670.

Council of Science Editors:

Choudhry A. Narrative Generation to Support Causal Exploration of Directed Graphs. [Masters Thesis]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/98670


Virginia Tech

6. Fiaux, Patrick O. Solving Intelligence Analysis Problems using Biclusters.

Degree: MS, Computer Science and Applications, 2012, Virginia Tech

 Analysts must filter through an ever-growing amount of data to obtain information relevant to their investigations. Looking at every piece of information individually is in… (more)

Subjects/Keywords: Visual Analytics; Biclustering

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APA (6th Edition):

Fiaux, P. O. (2012). Solving Intelligence Analysis Problems using Biclusters. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/31293

Chicago Manual of Style (16th Edition):

Fiaux, Patrick O. “Solving Intelligence Analysis Problems using Biclusters.” 2012. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/31293.

MLA Handbook (7th Edition):

Fiaux, Patrick O. “Solving Intelligence Analysis Problems using Biclusters.” 2012. Web. 07 Mar 2021.

Vancouver:

Fiaux PO. Solving Intelligence Analysis Problems using Biclusters. [Internet] [Masters thesis]. Virginia Tech; 2012. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/31293.

Council of Science Editors:

Fiaux PO. Solving Intelligence Analysis Problems using Biclusters. [Masters Thesis]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/31293


Virginia Tech

7. Sethi, Iccha. Clinician Decision Support Dashboard: Extracting value from Electronic Medical Records.

Degree: MS, Computer Science, 2012, Virginia Tech

 Medical records are rapidly being digitized to electronic medical records. Although Electronic Medical Records (EMRs) improve administration, billing, and logistics, an open research problem remains… (more)

Subjects/Keywords: electronic medical records; clinical decision support systems; text data mining; medical informatics

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APA (6th Edition):

Sethi, I. (2012). Clinician Decision Support Dashboard: Extracting value from Electronic Medical Records. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/41894

Chicago Manual of Style (16th Edition):

Sethi, Iccha. “Clinician Decision Support Dashboard: Extracting value from Electronic Medical Records.” 2012. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/41894.

MLA Handbook (7th Edition):

Sethi, Iccha. “Clinician Decision Support Dashboard: Extracting value from Electronic Medical Records.” 2012. Web. 07 Mar 2021.

Vancouver:

Sethi I. Clinician Decision Support Dashboard: Extracting value from Electronic Medical Records. [Internet] [Masters thesis]. Virginia Tech; 2012. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/41894.

Council of Science Editors:

Sethi I. Clinician Decision Support Dashboard: Extracting value from Electronic Medical Records. [Masters Thesis]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/41894


Virginia Tech

8. Mahendiran, Aravindan. Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics.

Degree: MS, Computer Science and Applications, 2014, Virginia Tech

 Twitter has become a popular data source in the recent decade and garnered a significant amount of attention as a surrogate data source for many… (more)

Subjects/Keywords: Election Forecasting; Twitter; Query Expansion; Social Group Modeling; Probabilistic Soft Logic

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APA (6th Edition):

Mahendiran, A. (2014). Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/25430

Chicago Manual of Style (16th Edition):

Mahendiran, Aravindan. “Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics.” 2014. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/25430.

MLA Handbook (7th Edition):

Mahendiran, Aravindan. “Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics.” 2014. Web. 07 Mar 2021.

Vancouver:

Mahendiran A. Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/25430.

Council of Science Editors:

Mahendiran A. Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/25430


Virginia Tech

9. Sundareisan, Shashidhar. Making diffusion work for you: Classification sans text, finding culprits and filling missing values.

Degree: MS, Computer Science and Applications, 2014, Virginia Tech

 Can we find people infected with the flu virus even though they did not visit a doctor? Can the temporal features of a trending hashtag… (more)

Subjects/Keywords: Data Mining; Social Networks; Epidemiology; Culprits; Missing nodes; Diffusion; Protests; Classification

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APA (6th Edition):

Sundareisan, S. (2014). Making diffusion work for you: Classification sans text, finding culprits and filling missing values. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/49678

Chicago Manual of Style (16th Edition):

Sundareisan, Shashidhar. “Making diffusion work for you: Classification sans text, finding culprits and filling missing values.” 2014. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/49678.

MLA Handbook (7th Edition):

Sundareisan, Shashidhar. “Making diffusion work for you: Classification sans text, finding culprits and filling missing values.” 2014. Web. 07 Mar 2021.

Vancouver:

Sundareisan S. Making diffusion work for you: Classification sans text, finding culprits and filling missing values. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/49678.

Council of Science Editors:

Sundareisan S. Making diffusion work for you: Classification sans text, finding culprits and filling missing values. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/49678

10. Lokegaonkar, Sanket Avinash. Continual Learning for Deep Dense Prediction.

Degree: MS, Computer Science and Applications, 2018, Virginia Tech

 Transferring a deep learning model from old tasks to a new one is known to suffer from the catastrophic forgetting effects. Such forgetting mechanism is… (more)

Subjects/Keywords: Computer Vision; Continual Learning; Image Segmentation; Dense Prediction

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APA (6th Edition):

Lokegaonkar, S. A. (2018). Continual Learning for Deep Dense Prediction. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83513

Chicago Manual of Style (16th Edition):

Lokegaonkar, Sanket Avinash. “Continual Learning for Deep Dense Prediction.” 2018. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/83513.

MLA Handbook (7th Edition):

Lokegaonkar, Sanket Avinash. “Continual Learning for Deep Dense Prediction.” 2018. Web. 07 Mar 2021.

Vancouver:

Lokegaonkar SA. Continual Learning for Deep Dense Prediction. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/83513.

Council of Science Editors:

Lokegaonkar SA. Continual Learning for Deep Dense Prediction. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83513


Virginia Tech

11. Cho, Yong Ju. Algorithms for Reconstructing and Reasoning about Chemical Reaction Networks.

Degree: PhD, Computer Science and Applications, 2013, Virginia Tech

 Recent advances in systems biology have uncovered detailed mechanisms of  biological processes such as the cell cycle, circadian rhythms,  and signaling pathways.  These mechanisms are… (more)

Subjects/Keywords: Chemical reaction networks; bistability; data mining; time series modeling

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APA (6th Edition):

Cho, Y. J. (2013). Algorithms for Reconstructing and Reasoning about Chemical Reaction Networks. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19244

Chicago Manual of Style (16th Edition):

Cho, Yong Ju. “Algorithms for Reconstructing and Reasoning about Chemical Reaction Networks.” 2013. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/19244.

MLA Handbook (7th Edition):

Cho, Yong Ju. “Algorithms for Reconstructing and Reasoning about Chemical Reaction Networks.” 2013. Web. 07 Mar 2021.

Vancouver:

Cho YJ. Algorithms for Reconstructing and Reasoning about Chemical Reaction Networks. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/19244.

Council of Science Editors:

Cho YJ. Algorithms for Reconstructing and Reasoning about Chemical Reaction Networks. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/19244


Virginia Tech

12. Zhao, Liang. Spatio-temporal Event Detection and Forecasting in Social Media.

Degree: PhD, Computer Science and Applications, 2016, Virginia Tech

 Nowadays, knowledge discovery on social media is attracting growing interest. Social media has become more than a communication tool, effectively functioning as a social sensor… (more)

Subjects/Keywords: event detection; event forecasting; social media

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APA (6th Edition):

Zhao, L. (2016). Spatio-temporal Event Detection and Forecasting in Social Media. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81904

Chicago Manual of Style (16th Edition):

Zhao, Liang. “Spatio-temporal Event Detection and Forecasting in Social Media.” 2016. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/81904.

MLA Handbook (7th Edition):

Zhao, Liang. “Spatio-temporal Event Detection and Forecasting in Social Media.” 2016. Web. 07 Mar 2021.

Vancouver:

Zhao L. Spatio-temporal Event Detection and Forecasting in Social Media. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/81904.

Council of Science Editors:

Zhao L. Spatio-temporal Event Detection and Forecasting in Social Media. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/81904


Virginia Tech

13. Ramesh, Bharath. Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems.

Degree: PhD, Computer Science and Applications, 2013, Virginia Tech

 Among the key challenges of computing today are the emergence of many-core architectures and the resulting need to effectively exploit explicit parallelism. Indeed, programmers are… (more)

Subjects/Keywords: Distributed Shared Memory; Virtual Shared Memory; Memory Consistency

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APA (6th Edition):

Ramesh, B. (2013). Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/23687

Chicago Manual of Style (16th Edition):

Ramesh, Bharath. “Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems.” 2013. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/23687.

MLA Handbook (7th Edition):

Ramesh, Bharath. “Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems.” 2013. Web. 07 Mar 2021.

Vancouver:

Ramesh B. Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/23687.

Council of Science Editors:

Ramesh B. Samhita: Virtual Shared Memory for Non-Cache-Coherent Systems. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/23687


Virginia Tech

14. Cadena, Jose Eduardo. Finding Interesting Subgraphs with Guarantees.

Degree: PhD, Computer Science and Applications, 2018, Virginia Tech

 Networks are a mathematical abstraction of the interactions between a set of entities, with extensive applications in social science, epidemiology, bioinformatics, and cybersecurity, among others.… (more)

Subjects/Keywords: Graph Mining; Data Mining; Graph Algorithms; Anomaly Detection; Finding Subgraphs; Parameterized Complexity; Distributed Algorithms

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APA (6th Edition):

Cadena, J. E. (2018). Finding Interesting Subgraphs with Guarantees. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81960

Chicago Manual of Style (16th Edition):

Cadena, Jose Eduardo. “Finding Interesting Subgraphs with Guarantees.” 2018. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/81960.

MLA Handbook (7th Edition):

Cadena, Jose Eduardo. “Finding Interesting Subgraphs with Guarantees.” 2018. Web. 07 Mar 2021.

Vancouver:

Cadena JE. Finding Interesting Subgraphs with Guarantees. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/81960.

Council of Science Editors:

Cadena JE. Finding Interesting Subgraphs with Guarantees. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/81960


Virginia Tech

15. Shukla, Manu. Algorithmic Distribution of Applied Learning on Big Data.

Degree: PhD, Computer Science and Applications, 2020, Virginia Tech

 Distribution of Machine Learning and Graph algorithms is commonly performed by modeling the core algorithm in the same way as the sequential technique except implemented… (more)

Subjects/Keywords: Big Data; Distributed Machine Learning; In-Memory Distribution; Graph Distribution

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APA (6th Edition):

Shukla, M. (2020). Algorithmic Distribution of Applied Learning on Big Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/100603

Chicago Manual of Style (16th Edition):

Shukla, Manu. “Algorithmic Distribution of Applied Learning on Big Data.” 2020. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/100603.

MLA Handbook (7th Edition):

Shukla, Manu. “Algorithmic Distribution of Applied Learning on Big Data.” 2020. Web. 07 Mar 2021.

Vancouver:

Shukla M. Algorithmic Distribution of Applied Learning on Big Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/100603.

Council of Science Editors:

Shukla M. Algorithmic Distribution of Applied Learning on Big Data. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/100603


Virginia Tech

16. Gad, Samah Hossam Aldin. Expressive Forms of Topic Modeling to Support Digital Humanities.

Degree: PhD, Computer Science and Applications, 2014, Virginia Tech

 Unstructured textual data is rapidly growing and practitioners from diverse disciplines are expe- riencing a need to structure this massive amount of data. Topic modeling… (more)

Subjects/Keywords: Topic Modeling; LDA; Segmentation

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APA (6th Edition):

Gad, S. H. A. (2014). Expressive Forms of Topic Modeling to Support Digital Humanities. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/65145

Chicago Manual of Style (16th Edition):

Gad, Samah Hossam Aldin. “Expressive Forms of Topic Modeling to Support Digital Humanities.” 2014. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/65145.

MLA Handbook (7th Edition):

Gad, Samah Hossam Aldin. “Expressive Forms of Topic Modeling to Support Digital Humanities.” 2014. Web. 07 Mar 2021.

Vancouver:

Gad SHA. Expressive Forms of Topic Modeling to Support Digital Humanities. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/65145.

Council of Science Editors:

Gad SHA. Expressive Forms of Topic Modeling to Support Digital Humanities. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/65145

17. Ning, Yue. Modeling Information Precursors for Event Forecasting.

Degree: PhD, Computer Science and Applications, 2018, Virginia Tech

 This dissertation is focused on the design and evaluation of machine learning algorithms for modeling information precursors for use in event modeling and forecasting. Given… (more)

Subjects/Keywords: Information Reciprocity; Precursor Learning; Event Modeling; Event Forecasting

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APA (6th Edition):

Ning, Y. (2018). Modeling Information Precursors for Event Forecasting. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/84486

Chicago Manual of Style (16th Edition):

Ning, Yue. “Modeling Information Precursors for Event Forecasting.” 2018. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/84486.

MLA Handbook (7th Edition):

Ning, Yue. “Modeling Information Precursors for Event Forecasting.” 2018. Web. 07 Mar 2021.

Vancouver:

Ning Y. Modeling Information Precursors for Event Forecasting. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/84486.

Council of Science Editors:

Ning Y. Modeling Information Precursors for Event Forecasting. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/84486


Virginia Tech

18. Afzalan, Milad. Data-driven customer energy behavior characterization for distributed energy management.

Degree: PhD, Civil Engineering, 2020, Virginia Tech

 Buildings account for more than 70% of electricity consumption in the U.S., in which more than 40% is associated with the residential sector. During recent… (more)

Subjects/Keywords: Distributed energy management; Smart grid; Machine learning; Human-building interaction; Segmentation.

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APA (6th Edition):

Afzalan, M. (2020). Data-driven customer energy behavior characterization for distributed energy management. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99210

Chicago Manual of Style (16th Edition):

Afzalan, Milad. “Data-driven customer energy behavior characterization for distributed energy management.” 2020. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/99210.

MLA Handbook (7th Edition):

Afzalan, Milad. “Data-driven customer energy behavior characterization for distributed energy management.” 2020. Web. 07 Mar 2021.

Vancouver:

Afzalan M. Data-driven customer energy behavior characterization for distributed energy management. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/99210.

Council of Science Editors:

Afzalan M. Data-driven customer energy behavior characterization for distributed energy management. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99210


Virginia Tech

19. Chen, Zhiqian. Graph Neural Networks: Techniques and Applications.

Degree: PhD, Computer Science and Applications, 2020, Virginia Tech

 Graph data is pervasive throughout most fields, including pandemic spread network, social network, transportation roads, internet, and chemical structure. Therefore, the applications modeled by graph… (more)

Subjects/Keywords: graph neural network; graph mining; approximation theory; spectral graph; circuit deobfuscation

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

APA (6th Edition):

Chen, Z. (2020). Graph Neural Networks: Techniques and Applications. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99848

Chicago Manual of Style (16th Edition):

Chen, Zhiqian. “Graph Neural Networks: Techniques and Applications.” 2020. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/99848.

MLA Handbook (7th Edition):

Chen, Zhiqian. “Graph Neural Networks: Techniques and Applications.” 2020. Web. 07 Mar 2021.

Vancouver:

Chen Z. Graph Neural Networks: Techniques and Applications. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/99848.

Council of Science Editors:

Chen Z. Graph Neural Networks: Techniques and Applications. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99848


Virginia Tech

20. Chhabra, Meenal. Studies in the Algorithmic Pricing of Information Goods and Services.

Degree: PhD, Computer Science and Applications, 2014, Virginia Tech

 This thesis makes a contribution to the algorithmic pricing literature by proposing and analyzing techniques for automatically pricing digital and information goods in order to… (more)

Subjects/Keywords: Non-linear pricing; Sequential Search; Algorithm pricing; Information goods; Dynamic pricing; Revenue maximization; Reinforcement learning; Search markets

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APA (6th Edition):

Chhabra, M. (2014). Studies in the Algorithmic Pricing of Information Goods and Services. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/25874

Chicago Manual of Style (16th Edition):

Chhabra, Meenal. “Studies in the Algorithmic Pricing of Information Goods and Services.” 2014. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/25874.

MLA Handbook (7th Edition):

Chhabra, Meenal. “Studies in the Algorithmic Pricing of Information Goods and Services.” 2014. Web. 07 Mar 2021.

Vancouver:

Chhabra M. Studies in the Algorithmic Pricing of Information Goods and Services. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/25874.

Council of Science Editors:

Chhabra M. Studies in the Algorithmic Pricing of Information Goods and Services. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/25874


Virginia Tech

21. Khandpur, Rupinder Paul. Augmenting Dynamic Query Expansion in Microblog Texts.

Degree: PhD, Computer Science and Applications, 2018, Virginia Tech

 Dynamic query expansion is a method of automatically identifying terms relevant to a target domain based on an incomplete query input. With the explosive growth… (more)

Subjects/Keywords: Dynamic Query Expansion; Microblog Event Retrieval; Social Media Analytics; Visual Knowledge Discovery

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

APA (6th Edition):

Khandpur, R. P. (2018). Augmenting Dynamic Query Expansion in Microblog Texts. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/84852

Chicago Manual of Style (16th Edition):

Khandpur, Rupinder Paul. “Augmenting Dynamic Query Expansion in Microblog Texts.” 2018. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/84852.

MLA Handbook (7th Edition):

Khandpur, Rupinder Paul. “Augmenting Dynamic Query Expansion in Microblog Texts.” 2018. Web. 07 Mar 2021.

Vancouver:

Khandpur RP. Augmenting Dynamic Query Expansion in Microblog Texts. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/84852.

Council of Science Editors:

Khandpur RP. Augmenting Dynamic Query Expansion in Microblog Texts. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/84852


Virginia Tech

22. Chen, Feng. Efficient Algorithms for Mining Large Spatio-Temporal Data.

Degree: PhD, Computer Science and Applications, 2013, Virginia Tech

 Knowledge discovery on spatio-temporal datasets has attracted growing interests. Recent advances on remote sensing technology mean that massive amounts of spatio-temporal data are being collected,… (more)

Subjects/Keywords: Spatio-Temporal Analysis; Outlier Detection; Robust Prediction; Energy Disaggregation

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APA (6th Edition):

Chen, F. (2013). Efficient Algorithms for Mining Large Spatio-Temporal Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19220

Chicago Manual of Style (16th Edition):

Chen, Feng. “Efficient Algorithms for Mining Large Spatio-Temporal Data.” 2013. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/19220.

MLA Handbook (7th Edition):

Chen, Feng. “Efficient Algorithms for Mining Large Spatio-Temporal Data.” 2013. Web. 07 Mar 2021.

Vancouver:

Chen F. Efficient Algorithms for Mining Large Spatio-Temporal Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/19220.

Council of Science Editors:

Chen F. Efficient Algorithms for Mining Large Spatio-Temporal Data. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/19220

23. Zhang, Xuchao. Scalable Robust Models Under Adversarial Data Corruption.

Degree: PhD, Computer Science and Applications, 2019, Virginia Tech

 Social media has experienced a rapid growth during the past decade. Millions of users of sites such as Twitter have been generating and sharing a… (more)

Subjects/Keywords: Robust Model; Adversarial Data Corruption; Scalability

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APA (6th Edition):

Zhang, X. (2019). Scalable Robust Models Under Adversarial Data Corruption. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/88833

Chicago Manual of Style (16th Edition):

Zhang, Xuchao. “Scalable Robust Models Under Adversarial Data Corruption.” 2019. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/88833.

MLA Handbook (7th Edition):

Zhang, Xuchao. “Scalable Robust Models Under Adversarial Data Corruption.” 2019. Web. 07 Mar 2021.

Vancouver:

Zhang X. Scalable Robust Models Under Adversarial Data Corruption. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/88833.

Council of Science Editors:

Zhang X. Scalable Robust Models Under Adversarial Data Corruption. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/88833

24. Akupatni, Vivek Bharath. My4Sight: A Human Computation Platform for Improving Flu Predictions.

Degree: MS, Computer Science and Applications, 2015, Virginia Tech

 While many human computation (human-in-the-loop) systems exist in the field of Artificial Intelligence (AI) to solve problems that can't be solved by computers alone, comparatively… (more)

Subjects/Keywords: human computation; human-in-the-loop; crowd sourcing; my4sight; influenza forecasting

Page 1 Page 2

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APA (6th Edition):

Akupatni, V. B. (2015). My4Sight: A Human Computation Platform for Improving Flu Predictions. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/56579

Chicago Manual of Style (16th Edition):

Akupatni, Vivek Bharath. “My4Sight: A Human Computation Platform for Improving Flu Predictions.” 2015. Masters Thesis, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/56579.

MLA Handbook (7th Edition):

Akupatni, Vivek Bharath. “My4Sight: A Human Computation Platform for Improving Flu Predictions.” 2015. Web. 07 Mar 2021.

Vancouver:

Akupatni VB. My4Sight: A Human Computation Platform for Improving Flu Predictions. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/56579.

Council of Science Editors:

Akupatni VB. My4Sight: A Human Computation Platform for Improving Flu Predictions. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/56579


Virginia Tech

25. Poirel, Christopher L. Bridging Methodological Gaps in Network-Based Systems Biology.

Degree: PhD, Computer Science and Applications, 2013, Virginia Tech

 Functioning of the living cell is controlled by a complex network of interactions among genes, proteins, and other molecules. A major goal of systems biology… (more)

Subjects/Keywords: Computational Biology; Functional Enrichment; Graph Theory; Network; Random Walk; Signaling Pathways; Top-Down Analysis

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APA (6th Edition):

Poirel, C. L. (2013). Bridging Methodological Gaps in Network-Based Systems Biology. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/23899

Chicago Manual of Style (16th Edition):

Poirel, Christopher L. “Bridging Methodological Gaps in Network-Based Systems Biology.” 2013. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/23899.

MLA Handbook (7th Edition):

Poirel, Christopher L. “Bridging Methodological Gaps in Network-Based Systems Biology.” 2013. Web. 07 Mar 2021.

Vancouver:

Poirel CL. Bridging Methodological Gaps in Network-Based Systems Biology. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/23899.

Council of Science Editors:

Poirel CL. Bridging Methodological Gaps in Network-Based Systems Biology. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/23899

26. Parikh, Nidhi Kiranbhai. Behavior Modeling and Analytics for Urban Computing: A Synthetic Information-based Approach.

Degree: PhD, Computer Science and Applications, 2017, Virginia Tech

 The rapid increase in urbanization poses challenges in diverse areas such as energy, transportation, pandemic planning, and disaster response. Planning for urbanization is a big… (more)

Subjects/Keywords: Behavior Modeling; Simulation Analytics; Social Simulations; Synthetic Information; Transient Population; Urban Computing

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APA (6th Edition):

Parikh, N. K. (2017). Behavior Modeling and Analytics for Urban Computing: A Synthetic Information-based Approach. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/84967

Chicago Manual of Style (16th Edition):

Parikh, Nidhi Kiranbhai. “Behavior Modeling and Analytics for Urban Computing: A Synthetic Information-based Approach.” 2017. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/84967.

MLA Handbook (7th Edition):

Parikh, Nidhi Kiranbhai. “Behavior Modeling and Analytics for Urban Computing: A Synthetic Information-based Approach.” 2017. Web. 07 Mar 2021.

Vancouver:

Parikh NK. Behavior Modeling and Analytics for Urban Computing: A Synthetic Information-based Approach. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/84967.

Council of Science Editors:

Parikh NK. Behavior Modeling and Analytics for Urban Computing: A Synthetic Information-based Approach. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/84967

27. Fan, Shuangfei. Deep Representation Learning on Labeled Graphs.

Degree: PhD, Computer Science and Applications, 2020, Virginia Tech

 Graphs are one of the most important and powerful data structures for conveying the complex and correlated information among data points. In this research, we… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Fan, S. (2020). Deep Representation Learning on Labeled Graphs. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/96596

Chicago Manual of Style (16th Edition):

Fan, Shuangfei. “Deep Representation Learning on Labeled Graphs.” 2020. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/96596.

MLA Handbook (7th Edition):

Fan, Shuangfei. “Deep Representation Learning on Labeled Graphs.” 2020. Web. 07 Mar 2021.

Vancouver:

Fan S. Deep Representation Learning on Labeled Graphs. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/96596.

Council of Science Editors:

Fan S. Deep Representation Learning on Labeled Graphs. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/96596


Virginia Tech

28. Semaan, Marie. A Novel Approach to Communal Rainwater Harvesting for Single-Family Housing: A Study of Tank Size, Reliability, and Costs.

Degree: PhD, Environmental Design and Planning, 2020, Virginia Tech

 An emerging field in rainwater harvesting (RWH) is the application of communal rainwater harvesting system. This system's main advantage compared to individual RWH is the… (more)

Subjects/Keywords: rainwater harvesting; communal; simulation; modeling distributed rainwater

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APA (6th Edition):

Semaan, M. (2020). A Novel Approach to Communal Rainwater Harvesting for Single-Family Housing: A Study of Tank Size, Reliability, and Costs. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/97580

Chicago Manual of Style (16th Edition):

Semaan, Marie. “A Novel Approach to Communal Rainwater Harvesting for Single-Family Housing: A Study of Tank Size, Reliability, and Costs.” 2020. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/97580.

MLA Handbook (7th Edition):

Semaan, Marie. “A Novel Approach to Communal Rainwater Harvesting for Single-Family Housing: A Study of Tank Size, Reliability, and Costs.” 2020. Web. 07 Mar 2021.

Vancouver:

Semaan M. A Novel Approach to Communal Rainwater Harvesting for Single-Family Housing: A Study of Tank Size, Reliability, and Costs. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/97580.

Council of Science Editors:

Semaan M. A Novel Approach to Communal Rainwater Harvesting for Single-Family Housing: A Study of Tank Size, Reliability, and Costs. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/97580


Virginia Tech

29. Liu, Xiaomo. Online Knowledge Community Mining and Modeling for  Effective Knowledge Management.

Degree: PhD, Computer Science and Applications, 2013, Virginia Tech

 More and more in recent years, activities that people once did in the real world they now do in virtual space. In particular, online communities… (more)

Subjects/Keywords: Online Communities; Knowledge Management; Expertise Profiling; Knowledge Helpfulness Prediction; Knowledge Sharing & Diffusion

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

APA (6th Edition):

Liu, X. (2013). Online Knowledge Community Mining and Modeling for  Effective Knowledge Management. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/50646

Chicago Manual of Style (16th Edition):

Liu, Xiaomo. “Online Knowledge Community Mining and Modeling for  Effective Knowledge Management.” 2013. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/50646.

MLA Handbook (7th Edition):

Liu, Xiaomo. “Online Knowledge Community Mining and Modeling for  Effective Knowledge Management.” 2013. Web. 07 Mar 2021.

Vancouver:

Liu X. Online Knowledge Community Mining and Modeling for  Effective Knowledge Management. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/50646.

Council of Science Editors:

Liu X. Online Knowledge Community Mining and Modeling for  Effective Knowledge Management. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/50646


Virginia Tech

30. Yang, Seungwon. Automatic Identification of Topic Tags from Texts Based on Expansion-Extraction Approach.

Degree: PhD, Computer Science and Applications, 2014, Virginia Tech

 Identifying topics of a textual document is useful for many purposes. We can organize the documents by topics in digital libraries. Then, we could browse… (more)

Subjects/Keywords: topic identification; tagging; cognitive informatics; vector space model; knowledge sources; natural language processing; digital libraries; usability study

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

APA (6th Edition):

Yang, S. (2014). Automatic Identification of Topic Tags from Texts Based on Expansion-Extraction Approach. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/25111

Chicago Manual of Style (16th Edition):

Yang, Seungwon. “Automatic Identification of Topic Tags from Texts Based on Expansion-Extraction Approach.” 2014. Doctoral Dissertation, Virginia Tech. Accessed March 07, 2021. http://hdl.handle.net/10919/25111.

MLA Handbook (7th Edition):

Yang, Seungwon. “Automatic Identification of Topic Tags from Texts Based on Expansion-Extraction Approach.” 2014. Web. 07 Mar 2021.

Vancouver:

Yang S. Automatic Identification of Topic Tags from Texts Based on Expansion-Extraction Approach. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10919/25111.

Council of Science Editors:

Yang S. Automatic Identification of Topic Tags from Texts Based on Expansion-Extraction Approach. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/25111

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