Library
. Data Processing System and Method for Computer-Assisted Coding of Natural Language Medical Text. USA: ezDI, LLC; 2016. 
(231.65 KB)
(231.65 KB). EmojiNet: A Machine Readable Emoji Sense Inventory. Wright Brother's Day, Wright State University. Dayton, Ohio, USA; 2016 . (66.92 KB) (815.49 KB)
(66.92 KB) (815.49 KB). EmojiNet: Building a Machine Readable Sense Inventory for Emoji. . 8th International Conference on Social Informatics (SocInfo 2016). Bellevue, WA: Springer International Publishing; 2016. p. 527-541. (712.1 KB)
(712.1 KB). Exploring Term Networks for Semantic Search over RDF Knowledge Graphs. . Metadata and Semantics Research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Cham: Springer International Publishing; 2016. p. 249–261. (432.38 KB)
(432.38 KB). Features for Ranking Tweets Based on Credibility and Newsworthiness. In 17th International Conference on Collaboration Technologies and Systems (CTS 2016). Orlando, Florida, USA: IEEE Computer Society; 2016. p. 18-25. (215.93 KB)
(215.93 KB). Finding Street Gang Members on Twitter. In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016). San Francisco, CA, USA; 2016. p. 685-692. (2.02 MB)
(2.02 MB). A Formal Graph Model for RDF and Its Implementation. CoRR. 2016 ;abs/1606.00480. (701.27 KB)
(701.27 KB). Gender-based Violence in 140 Characters or Fewer: A #BigData Case Study of Twitter. First Monday. 2016 ;21(1-4).
. Gleaning Types for Literals in RDF Triples with Application to Entity Summarization. . 13th International Conference, ESWC 2016. Heraklion, Crete, Greece: Springer International Publishing; 2016. p. 85-100. 
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(1.13 MB) (488 KB). Harnessing Relationships for Domain-specific Subgraph Extraction: A Recommendation Use Case. In IEEE International Conference on Big Data. Washington D.C.; 2016. (670.22 KB)
(670.22 KB). Identifying Offensive Videos on YouTube [Internet]. 2016. https://etd.ohiolink.edu/!etd.send_file?accession=wright1484751212961772&disposition=inline Rajeshwari Kandakatla: Identifying Offensive Videos on YouTube, MS Thesis, Wright State University, Dayton, OH, December 2016. (3.45 MB)
Rajeshwari Kandakatla: Identifying Offensive Videos on YouTube, MS Thesis, Wright State University, Dayton, OH, December 2016.
(3.45 MB). Identifying Tweets with Implicit Entity Mentions. Department of Computer Science and Engineering. [Dayton]: Wright State University; 2016. p. 56. (566.8 KB)
(566.8 KB). Implicit Entity Linking in Tweets. Extended Semantic Web Conference. Heraklion, Crete, Greece : Springer; 2016. p. 118-132. (365.33 KB) (530.27 KB)
(365.33 KB) (530.27 KB). Internet of Things to Smart IoT Through Semantic, Cognitive, and Perceptual Computing. IEEE Intelligent Systems. IEEE; 2016 ;31(2):108-112.
. Knowledge will Propel Machine Understanding of Content: Extrapolating from Current Examples. 2016 . (994.44 KB)
(994.44 KB). Knowledge-driven Implicit Information Extraction. Department of Computer Science & Engineering. [Dayton]: Wright State University; 2016. p. 123. (1.65 MB)
(1.65 MB). Knowledge-driven Search Intent Mining. Department of Computer Science & Engineering. [Dayton]: Wright State University; 2016. p. 180. (11.11 MB)
(11.11 MB). Knowledge-empowered Probabilistic Graphical Models For Physical-cyber-social Systems. Department of Computer Science & Engineering. [Dayton]: Wright State University; 2016. p. 172. (14.4 MB)
(14.4 MB). KnowledgeWiki: An OpenSource Tool for Creating Community-Curated Vocabulary, with a Use Case in Materials Science. In World Wide Web 2016. Montreal, Canada; 2016. (904.53 KB) (1.82 MB)
(904.53 KB) (1.82 MB). Ontology-enabled Healthcare Applications Exploiting Physical-Cyber-Social Big Data. In Ontology Summit 2016. Virtual; 2016.
. Preliminary Investigation of Walking Motion Using a Combination of Image and Signal Processing. In 2016 International Conference on Computational Science and Computational Intelligence. Las Vegas, NV; 2016. (514.03 KB)
(514.03 KB). Privacy-Preserving Spectral Analysis of Large Graphs in Public Clouds. Asia Conference on Computer and Communications Security 2016. Xi'an, China: ACM; 2016. p. 71-82.
. Qanary - A Methodology for Vocabulary-driven Open Question Answering Systems. ESWC 2016. Heraklion, Crete, Greece: Springer International Publishing; 2016. p. 625--641.
. Question Answering on Linked Data: Challenges and Future Directions. International World Wide Web Conference. Republic and Canton of Geneva, Switzerland: International World Wide Web Conferences Steering Committee; 2016. p. 693-698.
. Question Answering on Linked Data: Challenges and Future Directions. Computing Research Repository (CoRR). 2016 ;.
. Recognition of side effects as implicit-opinion words in drug reviews. Online Information Review; 2016 ;40(7):1018-1032. (564.66 KB)
(564.66 KB). ResQu: A Framework for Automatic Evaluation of Knowledge-Driven Automatic Summarization. Department of Engineering & Computer Science . [Dayton]: Wright State University; 2016. p. 64. (1.04 MB)
(1.04 MB). On Searching the Internet of Things: Requirements and Challenges. IEEE Intelligent Systems. IEEE; 2016 ;32(6):71-75.
. Semantic, Cognitive, and Perceptual Computing: Paradigms That Shape Human Experience. Computer. IEEE; 2016 ;49(3):64-72. (459.58 KB)
(459.58 KB). Semantic Filtering for Social Data. IEEE Internet Computing. IEEE; 2016 ;20(4):74-78. (342.08 KB)
(342.08 KB). Signals Revealing Street Gang Members on Twitter. In Workshop on Computational Approaches to Social Modeling (ChASM 2016) co-located with 8th International Conference on Social Informatics (SocInfo 2016). Bellevue, WA, USA; 2016. (939.06 KB)
(939.06 KB). Smart Cities – Enabling Services and Applications. Journal of Internet Services and Applications. SpringerOpen; 2016 ;7(6). (400.32 KB)
(400.32 KB). A Study of Social Web Data on Buprenorphine Abuse Using Semantic Web Technology. Fairborn: Wright State University; 2016 . (484.2 KB)
(484.2 KB). SWoTSuite: A Toolkit for Prototyping Cross-domain Semantic Web of Things Applications. 15th International Semantic Web Conference (ISWC 2016). Kobe, Japan: CEUR ; 2016. (459.68 KB)
(459.68 KB). "Those edibles hit hard": Exploration of Twitter data on cannabis edibles in the U.S. Drug and Alcohol Dependence. 2016 ;:64-70. (731.83 KB)
(731.83 KB). Towards a Message-Driven Vocabulary for Promoting the Interoperability of Question Answering Systems. IEEE International Conference on Semantic Computing 2016. Laguna Hills, CA: IEEE; 2016. p. 386-389.
. Tweet Properly: Analyzing Deleted Tweets to Understand and Identify Regrettable Ones. 25th International World Wide Web Conference (WWW 2016). Montreal, Canada: ACM; 2016. p. 603-612. (367.25 KB)
(367.25 KB). Understanding City Traffic Dynamics Utilizing Sensor and Textual Observations. In 30th AAAI Conference on Artificial Intelligence (AAAI-16). Phoenix, Arizona; 2016. (2.05 MB) (5.96 MB)
(2.05 MB) (5.96 MB). Using Social Media Data to Understand Brand Development. In 2016 Direct/Interactive Marketing Research Summit. Los Angeles, CA: Marketing EDGE; 2016. (135.98 KB)
(135.98 KB). What Motivates High School Students to Take Precautions Against the Spread of Influenza? Latent Modeling of Compliance with Preventative Practice: A Data Science Approach. In International Conference on Health Informatics and Medical Systems (HIMS). Las Vegas, Nevada; 2016. (490.51 KB)
(490.51 KB). "When 'Bad' is 'Good'"': Identifying Personal Communication and Sentiment in Drug-Related Tweets. JMIR Public Health Surveillance. JMIR Publications; 2016 ;2.
. Word Embeddings to Enhance Twitter Gang Member Profile Identification. In IJCAI Workshop on Semantic Machine Learning (SML 2016). New York City, NY: CEUR-WS; 2016. p. 18-24. (265.83 KB) (6.23 MB)
(265.83 KB) (6.23 MB). Analyzing the Social Media Footprint of Street Gangs. In 2015 IEEE International Conference on Intelligence and Security Informatics (ISI). Baltimore, MD: IEEE; 2015. p. 91-96. (1.26 MB)
(1.26 MB). Automatic Emotion Identification from Text. Department of Computer Science and Engineering. [Dayton]: Wright State University; 2015. p. 138. (679.48 KB)
(679.48 KB). Big Data and Smart Cities. Dunedin, New Zealand: Dunedin City Council; 2015. (93.5 KB)
(93.5 KB). Citizen Sensor Data Mining, Social Media Analytics and Applications. Singapore: Singapore Symposium on Sentiment Analysis; 2015.
. Community Discovery: Simple and Scalable Approaches. In Human–Computer Interaction Series. Switzerland: Springer International Publishing; 2015. p. 23-54.
. Comparative visualization of protein conformations using large high resolution displays with gestures and body tracking. In Visualization and Data Analysis 2015. San Francisco, California: SPIE; 2015.
. Context-driven automatic subgraph creation for literature-based discovery. Journal of Biomedical Informatics. 2015 ;54:141-157. (2.37 MB)
(2.37 MB). Contrast Pattern Aided Regression and Classification. Department of Computer Science and Engineering. [Dayton]: Wright State University; 2015. p. 120. (1.43 MB)
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