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You searched for +publisher:"Wright State University" +contributor:("Sheth, Amit"). Showing records 1 – 30 of 39 total matches.

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Wright State University

1. Kadariya, Dipesh. kBot: Knowledge-Enabled Personalized Chatbot for Self-Management of Asthma in Pediatric Population.

Degree: MS, Computer Science, 2019, Wright State University

 Asthma, chronic pulmonary disease, is one of the major health issues in the United States. Given its chronic nature, the demand for continuous monitoring of… (more)

Subjects/Keywords: Computer Science; Information Technology; Health Care Management; Virtual Assistant; Conversational Agent; Chatbot for Healthcare; Patient Generated Health Data; IoT for Personalized Health; Pediatric Asthma Management; Self Management; Personalized chatbot

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APA (6th Edition):

Kadariya, D. (2019). kBot: Knowledge-Enabled Personalized Chatbot for Self-Management of Asthma in Pediatric Population. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1565944979193573

Chicago Manual of Style (16th Edition):

Kadariya, Dipesh. “kBot: Knowledge-Enabled Personalized Chatbot for Self-Management of Asthma in Pediatric Population.” 2019. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1565944979193573.

MLA Handbook (7th Edition):

Kadariya, Dipesh. “kBot: Knowledge-Enabled Personalized Chatbot for Self-Management of Asthma in Pediatric Population.” 2019. Web. 24 Oct 2020.

Vancouver:

Kadariya D. kBot: Knowledge-Enabled Personalized Chatbot for Self-Management of Asthma in Pediatric Population. [Internet] [Masters thesis]. Wright State University; 2019. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1565944979193573.

Council of Science Editors:

Kadariya D. kBot: Knowledge-Enabled Personalized Chatbot for Self-Management of Asthma in Pediatric Population. [Masters Thesis]. Wright State University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1565944979193573


Wright State University

2. Partin, Michael. Scalable, Pluggable, and Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems.

Degree: MSCE, Computer Engineering, 2020, Wright State University

 Features and attributes that describe an event (disasters, social movements, etc.) are heterogeneous in nature. For virtually all events that impact humans, technology enables us… (more)

Subjects/Keywords: Computer Science; Computer Engineering; Web Studies; web application; docker; deployment; disaster; social media; big data; analysis; machine learning; kubernetes; software; programming; django

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APA (6th Edition):

Partin, M. (2020). Scalable, Pluggable, and Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1567073723628721

Chicago Manual of Style (16th Edition):

Partin, Michael. “Scalable, Pluggable, and Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems.” 2020. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1567073723628721.

MLA Handbook (7th Edition):

Partin, Michael. “Scalable, Pluggable, and Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems.” 2020. Web. 24 Oct 2020.

Vancouver:

Partin M. Scalable, Pluggable, and Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems. [Internet] [Masters thesis]. Wright State University; 2020. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1567073723628721.

Council of Science Editors:

Partin M. Scalable, Pluggable, and Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems. [Masters Thesis]. Wright State University; 2020. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1567073723628721


Wright State University

3. Nalamothu, Abhishek. Abusive and Hate Speech Tweets Detection with Text Generation.

Degree: MS, Computer Science, 2019, Wright State University

 According to a Pew Research study, 41% of Americans have personally experienced online harassment and two-thirds of Americans have witnessed harassment in 2017. Hence, online… (more)

Subjects/Keywords: Computer Science; Text generation; Generative adversarial network; Inverse Reinforcement Learning; Online Harassment detection

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APA (6th Edition):

Nalamothu, A. (2019). Abusive and Hate Speech Tweets Detection with Text Generation. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1567510940365305

Chicago Manual of Style (16th Edition):

Nalamothu, Abhishek. “Abusive and Hate Speech Tweets Detection with Text Generation.” 2019. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1567510940365305.

MLA Handbook (7th Edition):

Nalamothu, Abhishek. “Abusive and Hate Speech Tweets Detection with Text Generation.” 2019. Web. 24 Oct 2020.

Vancouver:

Nalamothu A. Abusive and Hate Speech Tweets Detection with Text Generation. [Internet] [Masters thesis]. Wright State University; 2019. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1567510940365305.

Council of Science Editors:

Nalamothu A. Abusive and Hate Speech Tweets Detection with Text Generation. [Masters Thesis]. Wright State University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1567510940365305


Wright State University

4. Manjunatha, Ashwin Kumar. A Domain Specific Language Based Approach for Developing Complex Cloud Computing Applications.

Degree: MSCE, Computer Engineering, 2011, Wright State University

  Computing has changed. Lately, a slew of cheap, ubiquitous, connected mobile devices as well as seemingly unlimited, utility style, pay as you go computing… (more)

Subjects/Keywords: Computer Engineering; Computer Science; Cloud Computing; Mobile Computing; Domain Specific Language; DSL; Cloud Mobile Hybrid Application; Metabolomics; Mobicloud; Mobicloud Toolkit; mobi-cloud; Metabolink; SCALE toolkit

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APA (6th Edition):

Manjunatha, A. K. (2011). A Domain Specific Language Based Approach for Developing Complex Cloud Computing Applications. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1309236898

Chicago Manual of Style (16th Edition):

Manjunatha, Ashwin Kumar. “A Domain Specific Language Based Approach for Developing Complex Cloud Computing Applications.” 2011. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1309236898.

MLA Handbook (7th Edition):

Manjunatha, Ashwin Kumar. “A Domain Specific Language Based Approach for Developing Complex Cloud Computing Applications.” 2011. Web. 24 Oct 2020.

Vancouver:

Manjunatha AK. A Domain Specific Language Based Approach for Developing Complex Cloud Computing Applications. [Internet] [Masters thesis]. Wright State University; 2011. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1309236898.

Council of Science Editors:

Manjunatha AK. A Domain Specific Language Based Approach for Developing Complex Cloud Computing Applications. [Masters Thesis]. Wright State University; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1309236898


Wright State University

5. Patni, Harshal Kamlesh. Real Time Semantic Analysis of Streaming Sensor Data.

Degree: MS, Computer Science, 2011, Wright State University

 The emergence of dynamic information sources - like social, mobile and sensors, has led to ginormous streams of real time data on the web also… (more)

Subjects/Keywords: Computer Science; Geographic Information Science; Semantic Web; Semantic Sensor Web; Real-Time Sensor Web; RDF; SPARQL; SSN Ontology; Open Geospatial Consortium; Sensor Web Enablement; Observation and Meausrements

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APA (6th Edition):

Patni, H. K. (2011). Real Time Semantic Analysis of Streaming Sensor Data. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1324181415

Chicago Manual of Style (16th Edition):

Patni, Harshal Kamlesh. “Real Time Semantic Analysis of Streaming Sensor Data.” 2011. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1324181415.

MLA Handbook (7th Edition):

Patni, Harshal Kamlesh. “Real Time Semantic Analysis of Streaming Sensor Data.” 2011. Web. 24 Oct 2020.

Vancouver:

Patni HK. Real Time Semantic Analysis of Streaming Sensor Data. [Internet] [Masters thesis]. Wright State University; 2011. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1324181415.

Council of Science Editors:

Patni HK. Real Time Semantic Analysis of Streaming Sensor Data. [Masters Thesis]. Wright State University; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1324181415

6. Purohit, Hemant. Mining Behavior of Citizen Sensor Communities to Improve Cooperation with Organizational Actors.

Degree: PhD, Computer Science and Engineering PhD, 2015, Wright State University

 Web 2.0 (social media) provides a natural platform for dynamic emergence of citizen (as) sensor communities, where the citizens generate content for sharing information and… (more)

Subjects/Keywords: Computer Science; Information Systems; Cooperative System; Social Media; Citizen Sensor Community; Coordination; Cooperation; Organization; Information System; Intent Classification; User Engagement; Knowledge Enhanced Learning; People-Content-Network Analysis; Crisis Informatics; Emergency

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APA (6th Edition):

Purohit, H. (2015). Mining Behavior of Citizen Sensor Communities to Improve Cooperation with Organizational Actors. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1441036899

Chicago Manual of Style (16th Edition):

Purohit, Hemant. “Mining Behavior of Citizen Sensor Communities to Improve Cooperation with Organizational Actors.” 2015. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1441036899.

MLA Handbook (7th Edition):

Purohit, Hemant. “Mining Behavior of Citizen Sensor Communities to Improve Cooperation with Organizational Actors.” 2015. Web. 24 Oct 2020.

Vancouver:

Purohit H. Mining Behavior of Citizen Sensor Communities to Improve Cooperation with Organizational Actors. [Internet] [Doctoral dissertation]. Wright State University; 2015. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1441036899.

Council of Science Editors:

Purohit H. Mining Behavior of Citizen Sensor Communities to Improve Cooperation with Organizational Actors. [Doctoral Dissertation]. Wright State University; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1441036899


Wright State University

7. Sridharan, Vaikunth. Sensor Data Streams Correlation Platform for Asthma Management.

Degree: MS, Computer Science, 2018, Wright State University

 Asthma is a high-burden chronic inflammatory disease with prevalence in children with twice the rate compared to adults. It can be improved by continuously monitoring… (more)

Subjects/Keywords: Computer Science; Health; asthma; asthma management; sensor data streams; Internet of Things; IoT

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APA (6th Edition):

Sridharan, V. (2018). Sensor Data Streams Correlation Platform for Asthma Management. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1527546937956439

Chicago Manual of Style (16th Edition):

Sridharan, Vaikunth. “Sensor Data Streams Correlation Platform for Asthma Management.” 2018. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1527546937956439.

MLA Handbook (7th Edition):

Sridharan, Vaikunth. “Sensor Data Streams Correlation Platform for Asthma Management.” 2018. Web. 24 Oct 2020.

Vancouver:

Sridharan V. Sensor Data Streams Correlation Platform for Asthma Management. [Internet] [Masters thesis]. Wright State University; 2018. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1527546937956439.

Council of Science Editors:

Sridharan V. Sensor Data Streams Correlation Platform for Asthma Management. [Masters Thesis]. Wright State University; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1527546937956439


Wright State University

8. Bhatt, Shreyansh. Data-driven and Knowledge-Based Strategies for Realizing Crowd Wisdom on Social Media.

Degree: PhD, Computer Science and Engineering PhD, 2019, Wright State University

 The wisdom of the crowd is a well-known example of collective intelligence wherein an aggregated judgment of a group of individuals is superior to that… (more)

Subjects/Keywords: Computer Science; crowd wisdom; collective intelligence; aggregated judgment; crowd selection; participant diversity; diverse crowd; social media

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APA (6th Edition):

Bhatt, S. (2019). Data-driven and Knowledge-Based Strategies for Realizing Crowd Wisdom on Social Media. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1578920003779943

Chicago Manual of Style (16th Edition):

Bhatt, Shreyansh. “Data-driven and Knowledge-Based Strategies for Realizing Crowd Wisdom on Social Media.” 2019. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1578920003779943.

MLA Handbook (7th Edition):

Bhatt, Shreyansh. “Data-driven and Knowledge-Based Strategies for Realizing Crowd Wisdom on Social Media.” 2019. Web. 24 Oct 2020.

Vancouver:

Bhatt S. Data-driven and Knowledge-Based Strategies for Realizing Crowd Wisdom on Social Media. [Internet] [Doctoral dissertation]. Wright State University; 2019. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1578920003779943.

Council of Science Editors:

Bhatt S. Data-driven and Knowledge-Based Strategies for Realizing Crowd Wisdom on Social Media. [Doctoral Dissertation]. Wright State University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1578920003779943


Wright State University

9. Henson, Cory Andrew. A Semantics-based Approach to Machine Perception.

Degree: PhD, Computer Science and Engineering PhD, 2013, Wright State University

 Machine perception can be formalized using semantic web technologies in order to derive abstractions from sensor data using background knowledge on the Web, and efficiently… (more)

Subjects/Keywords: Artificial Intelligence; Computer Science; Information Science; Semantic Web; Semantic Sensor Web; Semantic Sensor Networks; Semantic Perception; Machine Perception

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APA (6th Edition):

Henson, C. A. (2013). A Semantics-based Approach to Machine Perception. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1387645909

Chicago Manual of Style (16th Edition):

Henson, Cory Andrew. “A Semantics-based Approach to Machine Perception.” 2013. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1387645909.

MLA Handbook (7th Edition):

Henson, Cory Andrew. “A Semantics-based Approach to Machine Perception.” 2013. Web. 24 Oct 2020.

Vancouver:

Henson CA. A Semantics-based Approach to Machine Perception. [Internet] [Doctoral dissertation]. Wright State University; 2013. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1387645909.

Council of Science Editors:

Henson CA. A Semantics-based Approach to Machine Perception. [Doctoral Dissertation]. Wright State University; 2013. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1387645909


Wright State University

10. Kapanipathi, Pavan. Personalized and Adaptive Semantic Information Filtering for Social Media.

Degree: PhD, Computer Science and Engineering PhD, 2016, Wright State University

 Social media has experienced immense growth in recent times. These platforms are becoming increasingly common for information seeking and consumption, and as part of its… (more)

Subjects/Keywords: Computer Science; Technology; Personalization, Recommendation, Information Filtering, User Modeling, Semantic Web, Wikipedia, Social Media, Twitter

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APA (6th Edition):

Kapanipathi, P. (2016). Personalized and Adaptive Semantic Information Filtering for Social Media. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1464541093

Chicago Manual of Style (16th Edition):

Kapanipathi, Pavan. “Personalized and Adaptive Semantic Information Filtering for Social Media.” 2016. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1464541093.

MLA Handbook (7th Edition):

Kapanipathi, Pavan. “Personalized and Adaptive Semantic Information Filtering for Social Media.” 2016. Web. 24 Oct 2020.

Vancouver:

Kapanipathi P. Personalized and Adaptive Semantic Information Filtering for Social Media. [Internet] [Doctoral dissertation]. Wright State University; 2016. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1464541093.

Council of Science Editors:

Kapanipathi P. Personalized and Adaptive Semantic Information Filtering for Social Media. [Doctoral Dissertation]. Wright State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1464541093


Wright State University

11. Jadhav, Ashutosh. Knowledge Driven Search Intent Mining.

Degree: PhD, Computer Science and Engineering PhD, 2016, Wright State University

 Understanding users’ latent intents behind search queries is essential for satisfying a user’s search needs. Search intent mining can help search engines to enhance its… (more)

Subjects/Keywords: Computer Science; Search Intent Mining; Semantic Search; Health Informatics; Text Analytics; Semantic Web; Search Log Analysis; Social Media Analytics

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APA (6th Edition):

Jadhav, A. (2016). Knowledge Driven Search Intent Mining. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1464464707

Chicago Manual of Style (16th Edition):

Jadhav, Ashutosh. “Knowledge Driven Search Intent Mining.” 2016. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1464464707.

MLA Handbook (7th Edition):

Jadhav, Ashutosh. “Knowledge Driven Search Intent Mining.” 2016. Web. 24 Oct 2020.

Vancouver:

Jadhav A. Knowledge Driven Search Intent Mining. [Internet] [Doctoral dissertation]. Wright State University; 2016. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1464464707.

Council of Science Editors:

Jadhav A. Knowledge Driven Search Intent Mining. [Doctoral Dissertation]. Wright State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1464464707


Wright State University

12. Chen, Lu. Mining and Analyzing Subjective Experiences in User Generated Content.

Degree: PhD, Computer Science and Engineering PhD, 2016, Wright State University

 Web 2.0 and social media enable people to create, share and discover information instantly anywhere, anytime. A great amount of this information is subjective information… (more)

Subjects/Keywords: Computer Science; Information Science; Information Technology; subjective experience, subjective information, sentiment analysis, opinion mining, context-dependency, user generated content, social media

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APA (6th Edition):

Chen, L. (2016). Mining and Analyzing Subjective Experiences in User Generated Content. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1472164969

Chicago Manual of Style (16th Edition):

Chen, Lu. “Mining and Analyzing Subjective Experiences in User Generated Content.” 2016. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1472164969.

MLA Handbook (7th Edition):

Chen, Lu. “Mining and Analyzing Subjective Experiences in User Generated Content.” 2016. Web. 24 Oct 2020.

Vancouver:

Chen L. Mining and Analyzing Subjective Experiences in User Generated Content. [Internet] [Doctoral dissertation]. Wright State University; 2016. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1472164969.

Council of Science Editors:

Chen L. Mining and Analyzing Subjective Experiences in User Generated Content. [Doctoral Dissertation]. Wright State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1472164969


Wright State University

13. Alex, Adarsh Koruthu. Identifying Tweets with Implicit Entity Mentions.

Degree: MS, Computer Science, 2016, Wright State University

  Social networking sites like Twitter and Facebook have become a significant source of user-generated content in the past decade. Mining of this user-generated content… (more)

Subjects/Keywords: Computer Science; computer science

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APA (6th Edition):

Alex, A. K. (2016). Identifying Tweets with Implicit Entity Mentions. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1472495677

Chicago Manual of Style (16th Edition):

Alex, Adarsh Koruthu. “Identifying Tweets with Implicit Entity Mentions.” 2016. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1472495677.

MLA Handbook (7th Edition):

Alex, Adarsh Koruthu. “Identifying Tweets with Implicit Entity Mentions.” 2016. Web. 24 Oct 2020.

Vancouver:

Alex AK. Identifying Tweets with Implicit Entity Mentions. [Internet] [Masters thesis]. Wright State University; 2016. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1472495677.

Council of Science Editors:

Alex AK. Identifying Tweets with Implicit Entity Mentions. [Masters Thesis]. Wright State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1472495677


Wright State University

14. Marupudi, Surendra Brahma. Framework for Semantic Integration and Scalable Processing of City Traffic Events.

Degree: MS, Computer Science, 2016, Wright State University

 Intelligent traffic management requires analysis of a large volume of multimodal data from diverse domains. For the development of intelligent traffic applications, we need to… (more)

Subjects/Keywords: Computer Science; Lambda Architecture, Traffic data, Semantic Web, Scalable processing

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APA (6th Edition):

Marupudi, S. B. (2016). Framework for Semantic Integration and Scalable Processing of City Traffic Events. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1472505847

Chicago Manual of Style (16th Edition):

Marupudi, Surendra Brahma. “Framework for Semantic Integration and Scalable Processing of City Traffic Events.” 2016. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1472505847.

MLA Handbook (7th Edition):

Marupudi, Surendra Brahma. “Framework for Semantic Integration and Scalable Processing of City Traffic Events.” 2016. Web. 24 Oct 2020.

Vancouver:

Marupudi SB. Framework for Semantic Integration and Scalable Processing of City Traffic Events. [Internet] [Masters thesis]. Wright State University; 2016. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1472505847.

Council of Science Editors:

Marupudi SB. Framework for Semantic Integration and Scalable Processing of City Traffic Events. [Masters Thesis]. Wright State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1472505847


Wright State University

15. Perera, Pathirage Dinindu Sujan Udayanga. Knowledge-driven Implicit Information Extraction.

Degree: PhD, Computer Science and Engineering PhD, 2016, Wright State University

 Natural language is a powerful tool developed by humans over hundreds of thousands of years. The extensive usage, flexibility of the language, creativity of the… (more)

Subjects/Keywords: Computer Science; implicit entities; implicit relationships; information extraction; knowledge base

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APA (6th Edition):

Perera, P. D. S. U. (2016). Knowledge-driven Implicit Information Extraction. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1472474558

Chicago Manual of Style (16th Edition):

Perera, Pathirage Dinindu Sujan Udayanga. “Knowledge-driven Implicit Information Extraction.” 2016. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1472474558.

MLA Handbook (7th Edition):

Perera, Pathirage Dinindu Sujan Udayanga. “Knowledge-driven Implicit Information Extraction.” 2016. Web. 24 Oct 2020.

Vancouver:

Perera PDSU. Knowledge-driven Implicit Information Extraction. [Internet] [Doctoral dissertation]. Wright State University; 2016. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1472474558.

Council of Science Editors:

Perera PDSU. Knowledge-driven Implicit Information Extraction. [Doctoral Dissertation]. Wright State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1472474558


Wright State University

16. Balasuriya, Lakshika. Finding Street Gang Member Profiles on Twitter.

Degree: MS, Computer Science, 2017, Wright State University

 The crime and violence street gangs introduce into neighborhoods is a growing epidemic in cities around the world. Today, over 1.4 million people, belonging to… (more)

Subjects/Keywords: Computer Science; Street Gangs; Twitter Profile Identification; Gang Activity Understanding; Social Media Analysis; Word Embeddings; Street Gangs on Twitter

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APA (6th Edition):

Balasuriya, L. (2017). Finding Street Gang Member Profiles on Twitter. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1516054679956178

Chicago Manual of Style (16th Edition):

Balasuriya, Lakshika. “Finding Street Gang Member Profiles on Twitter.” 2017. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1516054679956178.

MLA Handbook (7th Edition):

Balasuriya, Lakshika. “Finding Street Gang Member Profiles on Twitter.” 2017. Web. 24 Oct 2020.

Vancouver:

Balasuriya L. Finding Street Gang Member Profiles on Twitter. [Internet] [Masters thesis]. Wright State University; 2017. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1516054679956178.

Council of Science Editors:

Balasuriya L. Finding Street Gang Member Profiles on Twitter. [Masters Thesis]. Wright State University; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1516054679956178

17. Wijeratne, Sanjaya. A Framework to Understand Emoji Meaning: Similarity and Sense Disambiguation of Emoji using EmojiNet.

Degree: PhD, Computer Science and Engineering PhD, 2018, Wright State University

 Pictographs, commonly referred to as `emoji’, have become a popular way to enhance electronic communications. They are an important component of the language used in… (more)

Subjects/Keywords: Artificial Intelligence; Computer Science; Computer Engineering; Sociolinguistics; Emoji; EmojiNet; Emoji Similarity; Emoji Sense Disambiguation; Emoji Understanding; Emoji Research; Twitter; Word Embedding; Social Media; Linguistics; Natural Language Processing; Machine Learning; Natural Language Understanding; Unicode; Emoji Semiotics

…84 xi ACKNOWLEDGEMENTS I joined Kno.e.sis Center, Wright State University in Fall 2011… …Civic Engagement at Wright State University. I learned many skills from them. Especially, I… …Wright State University. I’m grateful to Nicole Selken, the designer of The Emoji Dictionary… 

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APA (6th Edition):

Wijeratne, S. (2018). A Framework to Understand Emoji Meaning: Similarity and Sense Disambiguation of Emoji using EmojiNet. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1547506375922938

Chicago Manual of Style (16th Edition):

Wijeratne, Sanjaya. “A Framework to Understand Emoji Meaning: Similarity and Sense Disambiguation of Emoji using EmojiNet.” 2018. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1547506375922938.

MLA Handbook (7th Edition):

Wijeratne, Sanjaya. “A Framework to Understand Emoji Meaning: Similarity and Sense Disambiguation of Emoji using EmojiNet.” 2018. Web. 24 Oct 2020.

Vancouver:

Wijeratne S. A Framework to Understand Emoji Meaning: Similarity and Sense Disambiguation of Emoji using EmojiNet. [Internet] [Doctoral dissertation]. Wright State University; 2018. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1547506375922938.

Council of Science Editors:

Wijeratne S. A Framework to Understand Emoji Meaning: Similarity and Sense Disambiguation of Emoji using EmojiNet. [Doctoral Dissertation]. Wright State University; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1547506375922938

18. Lalithsena, Sarasi. Domain-specific Knowledge Extraction from the Web of Data.

Degree: PhD, Computer Science and Engineering PhD, 2018, Wright State University

 Domain knowledge plays a significant role in powering a number of intelligent applications such as entity recommendation, question answering, data analytics, and knowledge discovery. Recent… (more)

Subjects/Keywords: Computer Science; domain-specific knowledge extraction; knowledge graph; subgraphs; relationships

…100 xiv ACKNOWLEDGEMENTS My graduate life at Kno.e.sis Center, Wright State University… 

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APA (6th Edition):

Lalithsena, S. (2018). Domain-specific Knowledge Extraction from the Web of Data. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1527202092744638

Chicago Manual of Style (16th Edition):

Lalithsena, Sarasi. “Domain-specific Knowledge Extraction from the Web of Data.” 2018. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1527202092744638.

MLA Handbook (7th Edition):

Lalithsena, Sarasi. “Domain-specific Knowledge Extraction from the Web of Data.” 2018. Web. 24 Oct 2020.

Vancouver:

Lalithsena S. Domain-specific Knowledge Extraction from the Web of Data. [Internet] [Doctoral dissertation]. Wright State University; 2018. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1527202092744638.

Council of Science Editors:

Lalithsena S. Domain-specific Knowledge Extraction from the Web of Data. [Doctoral Dissertation]. Wright State University; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1527202092744638

19. Saxena, Ankita. A Semantically Enhanced Approach to Identify Depression-Indicative Symptoms Using Twitter Data.

Degree: MS, Computer Science, 2018, Wright State University

 According to the World Health Organization, more than 300 million people suffer from Major Depressive Disorder (MDD) worldwide. PHQ-9 is used to screen and diagnose… (more)

Subjects/Keywords: Computer Science; Major Depressive Disorder; MDD; depression; PHQ-9; social media; Twitter

…ACKNOWLEDGEMENTS My graduate life at Kno.e.sis Center at Wright State University adds a… 

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APA (6th Edition):

Saxena, A. (2018). A Semantically Enhanced Approach to Identify Depression-Indicative Symptoms Using Twitter Data. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright152764172911888

Chicago Manual of Style (16th Edition):

Saxena, Ankita. “A Semantically Enhanced Approach to Identify Depression-Indicative Symptoms Using Twitter Data.” 2018. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright152764172911888.

MLA Handbook (7th Edition):

Saxena, Ankita. “A Semantically Enhanced Approach to Identify Depression-Indicative Symptoms Using Twitter Data.” 2018. Web. 24 Oct 2020.

Vancouver:

Saxena A. A Semantically Enhanced Approach to Identify Depression-Indicative Symptoms Using Twitter Data. [Internet] [Masters thesis]. Wright State University; 2018. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright152764172911888.

Council of Science Editors:

Saxena A. A Semantically Enhanced Approach to Identify Depression-Indicative Symptoms Using Twitter Data. [Masters Thesis]. Wright State University; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright152764172911888

20. Jaykumar, Nishita. ResQu: A Framework for Automatic Evaluation of Knowledge-Driven Automatic Summarization.

Degree: MS, Computer Science, 2016, Wright State University

 Automatic generation of summaries that capture the salient aspects of a search resultset (i.e., automatic summarization) has become an important task in biomedical research. Automatic… (more)

Subjects/Keywords: Science Education; Bioinformatics; Biomedical Research; Biomedical Engineering; Computer Science; Computer Engineering; Automatic Summarization, Summarization Evaluation, Abstractive Summaries, Quality-based evaluation, Semantic Similarity, Medical Subject Headings, MetaMap, SemRep

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APA (6th Edition):

Jaykumar, N. (2016). ResQu: A Framework for Automatic Evaluation of Knowledge-Driven Automatic Summarization. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1464628801

Chicago Manual of Style (16th Edition):

Jaykumar, Nishita. “ResQu: A Framework for Automatic Evaluation of Knowledge-Driven Automatic Summarization.” 2016. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1464628801.

MLA Handbook (7th Edition):

Jaykumar, Nishita. “ResQu: A Framework for Automatic Evaluation of Knowledge-Driven Automatic Summarization.” 2016. Web. 24 Oct 2020.

Vancouver:

Jaykumar N. ResQu: A Framework for Automatic Evaluation of Knowledge-Driven Automatic Summarization. [Internet] [Masters thesis]. Wright State University; 2016. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1464628801.

Council of Science Editors:

Jaykumar N. ResQu: A Framework for Automatic Evaluation of Knowledge-Driven Automatic Summarization. [Masters Thesis]. Wright State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1464628801

21. Krishnamurthy, Revathy. Knowledge Enabled Location Prediction of Twitter Users.

Degree: MS, Computer Science, 2015, Wright State University

 As the popularity of online social networking sites such as Twitter and Facebook continues to rise, the volume of textual content generated on the web… (more)

Subjects/Keywords: Computer Science; Wikipedia, Twitter, Location Prediction, Semantics

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APA (6th Edition):

Krishnamurthy, R. (2015). Knowledge Enabled Location Prediction of Twitter Users. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1424349831

Chicago Manual of Style (16th Edition):

Krishnamurthy, Revathy. “Knowledge Enabled Location Prediction of Twitter Users.” 2015. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1424349831.

MLA Handbook (7th Edition):

Krishnamurthy, Revathy. “Knowledge Enabled Location Prediction of Twitter Users.” 2015. Web. 24 Oct 2020.

Vancouver:

Krishnamurthy R. Knowledge Enabled Location Prediction of Twitter Users. [Internet] [Masters thesis]. Wright State University; 2015. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1424349831.

Council of Science Editors:

Krishnamurthy R. Knowledge Enabled Location Prediction of Twitter Users. [Masters Thesis]. Wright State University; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1424349831

22. Cameron, Delroy Huborn. A Context-Driven Subgraph Model for Literature-Based Discovery.

Degree: PhD, Computer Science and Engineering PhD, 2014, Wright State University

 Literature-Based Discovery (LBD) refers to the process of uncovering hidden connections that are implicit in scientific literature. Numerous hypotheses have been generated from scientific literature… (more)

Subjects/Keywords: Computer Science; Biomedical Research; Information Systems; Semantic Predications; Graph mining; Path clustering; Semantic relatedness; Literature-based discovery

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APA (6th Edition):

Cameron, D. H. (2014). A Context-Driven Subgraph Model for Literature-Based Discovery. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1417034001

Chicago Manual of Style (16th Edition):

Cameron, Delroy Huborn. “A Context-Driven Subgraph Model for Literature-Based Discovery.” 2014. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1417034001.

MLA Handbook (7th Edition):

Cameron, Delroy Huborn. “A Context-Driven Subgraph Model for Literature-Based Discovery.” 2014. Web. 24 Oct 2020.

Vancouver:

Cameron DH. A Context-Driven Subgraph Model for Literature-Based Discovery. [Internet] [Doctoral dissertation]. Wright State University; 2014. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1417034001.

Council of Science Editors:

Cameron DH. A Context-Driven Subgraph Model for Literature-Based Discovery. [Doctoral Dissertation]. Wright State University; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1417034001

23. Mendes, Pablo N. Adaptive Semantic Annotation of Entity and Concept Mentions in Text.

Degree: PhD, Computer Science and Engineering PhD, 2014, Wright State University

 The recent years have seen an increase in interest for knowledge repositories that are useful across applications, in contrast to the creation of ad hoc… (more)

Subjects/Keywords: Computer Science; semantic annotation; semantic tagging; named entity recognition; name resolution; entity disambiguation; entity linking; keyphrase extraction; word sense disambiguation; entity classification; entity extraction; adaptive; flexible

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APA (6th Edition):

Mendes, P. N. (2014). Adaptive Semantic Annotation of Entity and Concept Mentions in Text. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1401665504

Chicago Manual of Style (16th Edition):

Mendes, Pablo N. “Adaptive Semantic Annotation of Entity and Concept Mentions in Text.” 2014. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1401665504.

MLA Handbook (7th Edition):

Mendes, Pablo N. “Adaptive Semantic Annotation of Entity and Concept Mentions in Text.” 2014. Web. 24 Oct 2020.

Vancouver:

Mendes PN. Adaptive Semantic Annotation of Entity and Concept Mentions in Text. [Internet] [Doctoral dissertation]. Wright State University; 2014. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1401665504.

Council of Science Editors:

Mendes PN. Adaptive Semantic Annotation of Entity and Concept Mentions in Text. [Doctoral Dissertation]. Wright State University; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1401665504

24. Cheekula, Siva Kumar. Characterizing Concepts in Taxonomy for Entity Recommendations.

Degree: MS, Computer Science, 2017, Wright State University

 Entity recommendation systems are enormously popular on the Web. These systems harness manually crafted taxonomies for improving recommendations. For example, Yahoo created the Open Directory… (more)

Subjects/Keywords: Computer Science; Taxonomies; Entity Recommendations; Knowledge-bases; Characteristics of Taxonomy

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APA (6th Edition):

Cheekula, S. K. (2017). Characterizing Concepts in Taxonomy for Entity Recommendations. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1495668638038457

Chicago Manual of Style (16th Edition):

Cheekula, Siva Kumar. “Characterizing Concepts in Taxonomy for Entity Recommendations.” 2017. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1495668638038457.

MLA Handbook (7th Edition):

Cheekula, Siva Kumar. “Characterizing Concepts in Taxonomy for Entity Recommendations.” 2017. Web. 24 Oct 2020.

Vancouver:

Cheekula SK. Characterizing Concepts in Taxonomy for Entity Recommendations. [Internet] [Masters thesis]. Wright State University; 2017. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1495668638038457.

Council of Science Editors:

Cheekula SK. Characterizing Concepts in Taxonomy for Entity Recommendations. [Masters Thesis]. Wright State University; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1495668638038457

25. Yallamelli, Pavankalyan. A Power Iteration Based Co-Training Approach to Achieve Convergence for Multi-View Clustering.

Degree: MS, Computer Science, 2017, Wright State University

 Collecting diversified opinions is the key to achieve "the Wisdom of Crowd". In this work, we propose to use a novel multi-view clustering method to… (more)

Subjects/Keywords: Computer Science; Social Research; Co-training; Multi-View clustering; Power iteration clustering; Wisdom of Crowd; Fantasy Sports

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APA (6th Edition):

Yallamelli, P. (2017). A Power Iteration Based Co-Training Approach to Achieve Convergence for Multi-View Clustering. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright151605107018487

Chicago Manual of Style (16th Edition):

Yallamelli, Pavankalyan. “A Power Iteration Based Co-Training Approach to Achieve Convergence for Multi-View Clustering.” 2017. Masters Thesis, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright151605107018487.

MLA Handbook (7th Edition):

Yallamelli, Pavankalyan. “A Power Iteration Based Co-Training Approach to Achieve Convergence for Multi-View Clustering.” 2017. Web. 24 Oct 2020.

Vancouver:

Yallamelli P. A Power Iteration Based Co-Training Approach to Achieve Convergence for Multi-View Clustering. [Internet] [Masters thesis]. Wright State University; 2017. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright151605107018487.

Council of Science Editors:

Yallamelli P. A Power Iteration Based Co-Training Approach to Achieve Convergence for Multi-View Clustering. [Masters Thesis]. Wright State University; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright151605107018487

26. Nguyen, Vinh Thi Kim. Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs.

Degree: PhD, Computer Science and Engineering PhD, 2017, Wright State University

 Semantic Web technologies such as RDF and OWL have become World Wide Web Consortium (W3C) standards for knowledge representation and reasoning. RDF triples about triples,… (more)

Subjects/Keywords: Computer Science; semantic web; contextualized knowledge graph; knowledge representation and reasoning; logical inferences; formal graph; RDF; RDFS; W3C

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APA (6th Edition):

Nguyen, V. T. K. (2017). Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1516147861789615

Chicago Manual of Style (16th Edition):

Nguyen, Vinh Thi Kim. “Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs.” 2017. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1516147861789615.

MLA Handbook (7th Edition):

Nguyen, Vinh Thi Kim. “Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs.” 2017. Web. 24 Oct 2020.

Vancouver:

Nguyen VTK. Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs. [Internet] [Doctoral dissertation]. Wright State University; 2017. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1516147861789615.

Council of Science Editors:

Nguyen VTK. Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs. [Doctoral Dissertation]. Wright State University; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1516147861789615

27. Ranabahu, Ajith Harshana. Abstraction Driven Application and Data Portability in Cloud Computing.

Degree: PhD, Computer Science and Engineering PhD, 2012, Wright State University

 Cloud computing has changed the way organizations create, manage, and evolve their applications. While many organizations are eager to use the cloud, tempted by substantial… (more)

Subjects/Keywords: Computer Science; Cloud computing; Domain Specific Languages; Program Generation; Program Portability

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APA (6th Edition):

Ranabahu, A. H. (2012). Abstraction Driven Application and Data Portability in Cloud Computing. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1365271464

Chicago Manual of Style (16th Edition):

Ranabahu, Ajith Harshana. “Abstraction Driven Application and Data Portability in Cloud Computing.” 2012. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1365271464.

MLA Handbook (7th Edition):

Ranabahu, Ajith Harshana. “Abstraction Driven Application and Data Portability in Cloud Computing.” 2012. Web. 24 Oct 2020.

Vancouver:

Ranabahu AH. Abstraction Driven Application and Data Portability in Cloud Computing. [Internet] [Doctoral dissertation]. Wright State University; 2012. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1365271464.

Council of Science Editors:

Ranabahu AH. Abstraction Driven Application and Data Portability in Cloud Computing. [Doctoral Dissertation]. Wright State University; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1365271464

28. Gomadam, Karthik Rajagopal. Semantics Enriched Service Environments.

Degree: PhD, Computer Science and Engineering PhD, 2009, Wright State University

  During the past seven years services centric computing has emerged as the preferred approach to architect complex software. Software is increasingly developed by integrating… (more)

Subjects/Keywords: Computer Science; Web 2.0; Service Oriented Architecture; Semantic Web; Semantic Web Services; REST

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APA (6th Edition):

Gomadam, K. R. (2009). Semantics Enriched Service Environments. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1251246445

Chicago Manual of Style (16th Edition):

Gomadam, Karthik Rajagopal. “Semantics Enriched Service Environments.” 2009. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1251246445.

MLA Handbook (7th Edition):

Gomadam, Karthik Rajagopal. “Semantics Enriched Service Environments.” 2009. Web. 24 Oct 2020.

Vancouver:

Gomadam KR. Semantics Enriched Service Environments. [Internet] [Doctoral dissertation]. Wright State University; 2009. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1251246445.

Council of Science Editors:

Gomadam KR. Semantics Enriched Service Environments. [Doctoral Dissertation]. Wright State University; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1251246445

29. Thomas, Christopher J. Knowledge Acquisition in a System.

Degree: PhD, Computer Science and Engineering PhD, 2012, Wright State University

  I present a method for growing the amount of knowledge available on the Web using a hermeneutic method that involves background knowledge, Information Extraction… (more)

Subjects/Keywords: Artificial Intelligence; Computer Science; Information Science; Knowledge Extraction; Knowledge Acquisition; Knowledge Representation; Information Extraction; Ontology Engineering; Community-generated Content

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APA (6th Edition):

Thomas, C. J. (2012). Knowledge Acquisition in a System. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1357753287

Chicago Manual of Style (16th Edition):

Thomas, Christopher J. “Knowledge Acquisition in a System.” 2012. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1357753287.

MLA Handbook (7th Edition):

Thomas, Christopher J. “Knowledge Acquisition in a System.” 2012. Web. 24 Oct 2020.

Vancouver:

Thomas CJ. Knowledge Acquisition in a System. [Internet] [Doctoral dissertation]. Wright State University; 2012. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1357753287.

Council of Science Editors:

Thomas CJ. Knowledge Acquisition in a System. [Doctoral Dissertation]. Wright State University; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1357753287

30. Jain, Prateek. Linked Open Data Alignment & Querying.

Degree: PhD, Computer Science and Engineering PhD, 2012, Wright State University

  The recent emergence of the “Linked Data” approach for publishing data represents a major step forward in realizing the original vision of a web… (more)

Subjects/Keywords: Computer Science; LINKED OPEN DATA; SEMANTIC WEB; RELATIONSHIP IDENTIFICATION; WEB OF DATA; LOD; SCHEMA MATCHING; FEDERATED QUERYING; COMPUTER SCIENCE

…as ’Wright State University is located in Dayton’ can be denoted by making Wright State as… 

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APA (6th Edition):

Jain, P. (2012). Linked Open Data Alignment & Querying. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1345575500

Chicago Manual of Style (16th Edition):

Jain, Prateek. “Linked Open Data Alignment & Querying.” 2012. Doctoral Dissertation, Wright State University. Accessed October 24, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1345575500.

MLA Handbook (7th Edition):

Jain, Prateek. “Linked Open Data Alignment & Querying.” 2012. Web. 24 Oct 2020.

Vancouver:

Jain P. Linked Open Data Alignment & Querying. [Internet] [Doctoral dissertation]. Wright State University; 2012. [cited 2020 Oct 24]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1345575500.

Council of Science Editors:

Jain P. Linked Open Data Alignment & Querying. [Doctoral Dissertation]. Wright State University; 2012. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1345575500

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