Library
. Semantics-enhanced Geoscience Interoperability, Analytics, and Applications. Madison, WI: Geospatial Semantics Workshop and GeoVoCamp; 2014. 
(6.14 MB)
(6.14 MB). Twitris: A System for Collective Social Intelligence. In: . Encyclopedia of Social Network Analysis and Mining. 1st ed. New York: Springer-Verlag New York; 2014. p. 2240-2253. (2.21 MB)
(2.21 MB). On Understanding Divergence of Online Social Group Discussion. In 8th International AAAI Conference on Weblogs and Social Media (ICWSM 2014). University Park, PA; 2014. (317.78 KB)
(317.78 KB). User Interests Identification on Twitter Using a Hierarchical Knowledge Base. . 11th Extended Semantic Web Conference (ESWC 2014). Crete, Greece: Springer International Publishing; 2014. p. 99-113. (961.33 KB)
(961.33 KB). The Web of Things. Computing Now. 2014 ;7(3).
. What Information about Cardiovascular Diseases do People Search Online?. In 25th European Medical Informatics Conference (MIE 2014). Istanbul, Turkey; 2014. (121.33 KB)
(121.33 KB). When Less is More: A Web-Based Study of User Beliefs about Buprenorphine Dosing in Self-Treatment of Opioid Withdrawal Symptoms. In College on Problems of Drug Dependence (CPDD 2014). San Juan, Puerto Rico; 2014. (477.97 KB)
(477.97 KB). With Whom to Coordinate, Why and How in Ad-hoc Social Media Communities during Crisis Response. In 11th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2014). University Park, PA; 2014. (773.18 KB)
(773.18 KB). YouRank: Let User Engagement Rank Microblog Search Results. In 8th International AAAI Conference on Weblogs and Social Media . Ann Arbor, MI; 2014. (716.37 KB)
(716.37 KB). 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). 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.
. Context-driven automatic subgraph creation for literature-based discovery. Journal of Biomedical Informatics. 2015 ;54:141-157. (2.37 MB)
(2.37 MB). Entity Recommendations Using Hierarchical Knowledge Bases. Extended Semantic Web Conference 2015 (ESWC 2015). Portoroz, Slovenia; 2015. (355.5 KB)
(355.5 KB). Evaluating a Potential Commercial Tool for Healthcare Application for People with Dementia. In International Conference on Health Informatics and Medical Systems (HIMS). Las Vegas, Nevada; 2015. (345.24 KB)
(345.24 KB). Exposing Provenance Metadata Using Different RDF Models. CoRR. 2015 ;abs/1509.02822. (4.91 MB)
(4.91 MB). Extracting City Traffic Events from Social Streams. ACM Transactions on Intelligent Systems and Technology. 2015 ;6(4):2-27. (2.5 MB)
(2.5 MB). ezDI's semantics-enhanced linguistic, NLP, and ML approach for health informatics. In 14th International Semantic Web Conference (ISWC 2015). Bethlehem, PA; 2015. (223.53 KB)
(223.53 KB). FACES: Diversity-Aware Entity Summarization using Incremental Hierarchical Conceptual Clustering. In 29th AAAI Conference on Artificial Intelligence (AAAI 2015). Austin, Texas; 2015. (562.36 KB)
(562.36 KB). Feedback-Driven Radiology Exam Report Retrieval with Semantics. In 2015 IEEE International Conference on Healthcare Informatics. Dallas, Texas; 2015. (591.92 KB)
(591.92 KB). Gender-Based Violence in 140 Characters or Fewer: A #BigData Case Study of Twitter. Dayton: Wright State University; 2015 . (955.68 KB)
(955.68 KB). Implicit Entity Recognition in Clinical Documents. 4th Joint Conference on Lexical and Computational Semantics (*SEM) 2015. Denver, CO: Association for Computational Linguistics; 2015. p. 228-238. (300.69 KB)
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(300.69 KB) (332.44 KB). Intent Classification of Short-Text on Social Media. In SocialCom 2015: 8th IEEE International Conference on Social Computing and Networking. Chengdu, China: IEEE; 2015. (485.79 KB)
(485.79 KB). Internet of Things Perspectives. IT Professional. 2015 ;14(3):60-63. (143.09 KB)
(143.09 KB). Knowledge Enabled Approach to Predict the Location of Twitter Users. . 12th European Semantic Web Conference (ESWC 2015). Portoroz, Slovenia: Springer International Publishing; 2015. p. 187-201. (790.96 KB)
(790.96 KB). Knowledge-driven Personalized Contextual mHealth Service for Asthma Management in Children. 2015 IEEE International Conference on Mobile Services. New York, NY: IEEE; 2015. p. 284 - 291. (1.31 MB)
(1.31 MB). Physical-Cyber-Social Computing: Looking Back, Looking Forward. IEEE Internet Computing. 2015 ;19(3):7-11.
. On Reasoning with RDF Statements about Statements using Singleton Property Triples. CoRR. 2015 ;abs/1509.04513. (182.65 KB)
(182.65 KB). Semantic, Cognitive, and Perceptual Computing: Advances Toward Computing for Human Experience. CoRR. 2015 ;abs/1510.05963. (1.55 MB)
(1.55 MB). Semantic Gateway as a Service architecture for IoT Interoperability. In IEEE 4th International Conference on Mobile Services. New York City, New York: IEEE; 2015. (1.67 MB)
(1.67 MB). Smart Data: How You and I Will Exploit Big Data for Personalized Digital Health and Many Other Activities. 2015. (240.65 KB)
(240.65 KB). Social Health Signals. In International Semantic Web Conference 2015 (ISWC 2015). Bethlehem, Pennsylvania; 2015. (183.28 KB)
(183.28 KB). Sub is a Weird Drug: A Web-Based Study of Lay Attitudes About Use of Buprenorphine to Self-Treat Opioid Withdrawal Symptoms. The American Journal on Addictions. 2015 ;24(5):403-409. (275.33 KB)
(275.33 KB). "Time for dabs": Analyzing Twitter data on butane hash oil use. In College on Problems of Drug Dependence CPDD 2015. Phoenix, Arizona; 2015. (87.2 KB)
(87.2 KB). "Time for dabs": Analyzing Twitter data on marijuana concentrates across the U.S. Drug and Alcohol Dependence. 2015 ;155:307-311.
. Transforming Big Data into Smart Data: Deriving Value via Harnessing Volume, Variety & Velocity Using Semantics and Semantic Web. Dunedin, New Zealand: University of Otago; 2015. (98.76 KB)
(98.76 KB). Transforming Big Data into Smart Data: Deriving Value via Harnessing Volume, Variety & Velocity Using Semantics and Semantic Web. Hobart, Australia: CSIRO; 2015.
. Transforming Big Data into Smart Data: Deriving Value via Harnessing Volume, Variety & Velocity Using Semantics and Semantic Web. Melbourne, Australia: RMIT School of Computer Science and Information Technology; 2015.
. Transforming Big Data into Smart Data: Deriving Value via Harnessing Volume, Variety & Velocity Using Semantics and Semantic Web. Singapore, Singapore: Singapore University of Technology and Design; 2015. (98.76 KB)
(98.76 KB). Analyzing Clinical Depressive Symptoms in Twitter. In 23rd NIMH Conference on Mental Health Services Research (MHSR): Harnessing Science to Strengthen the Public Health Impact. Bethesda, MD; 2016. (1.98 MB)
(1.98 MB). Building the Web of Knowledge with Smart IoT Applications. IEEE Intelligent Systems. IEEE; 2016 ;32(5). (379.84 KB)
(379.84 KB). Clustering for Simultaneous Extraction of Aspects and Features from Reviews. In North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL: HLT). San Diego, California: NAACL; 2016. (299.4 KB)
(299.4 KB). 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). 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. (1.13 MB) (488 KB)
(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)
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