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Filters: Author is Pavan Kapanipathi [Clear All Filters]
. Twitris: A System for Collective Social Intelligence. In: . Encyclopedia of Social Network Analysis and Mining. 2nd ed. New York: Springer-Verlag New York; 2018. p. 1-23. 
(2.08 MB)
(2.08 MB). Domain-specific Hierarchical Subgraph Extraction: A Recommendation Use Case. In IEEE Conference on Big Data. Boston, MA, USA; 2017. S. Lalithsena, S. Perera, P. Kapanipathi and A. Sheth, "Domain-specific hierarchical subgraph extraction: A recommendation use case," 2017 IEEE International Conference on Big Data (Big Data), Boston, MA, 2017, pp. 666-675. doi: 10.1109/BigData.2017.8257982
(475.77 KB)
S. Lalithsena, S. Perera, P. Kapanipathi and A. Sheth, "Domain-specific hierarchical subgraph extraction: A recommendation use case," 2017 IEEE International Conference on Big Data (Big Data), Boston, MA, 2017, pp. 666-675. doi: 10.1109/BigData.2017.8257982
(475.77 KB). Harnessing Relationships for Domain-specific Subgraph Extraction: A Recommendation Use Case. In IEEE International Conference on Big Data. Washington D.C.; 2016. (920.03 KB)
(920.03 KB). Semantic Filtering for Social Data. IEEE Internet Computing. IEEE; 2016 ;20(4):74-78. (342.08 KB)
(342.08 KB). Entity Recommendations Using Hierarchical Knowledge Bases. Extended Semantic Web Conference 2015 (ESWC 2015). Portoroz, Slovenia; 2015. (355.5 KB)
(355.5 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). Hierarchical Interest Graph from Tweets. . 3rd International World Wide Web Conference. Seoul, South Korea: ACM; 2014. (248.6 KB)
(248.6 KB). Location Prediction of Twitter Users using Wikipedia. Dayton: Wright State University; 2014 . (835.27 KB)
(835.27 KB). 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). 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). Characterising Concepts of Interest Leveraging Linked Data and the Social Web. 2013 IEEE/WIC/ACM International Conference on Web Intelligence. Atlanta, GA; 2013. p. 519-526. (260.38 KB)
(260.38 KB). Personalized Filtering of the Twitter Stream. In ISWC 2011. Bonn, Germany: International Semantic Web Conference; 2011. (402.68 KB)
(402.68 KB). Privacy-Aware and Scalable Content Dissemination in Distributed Social Networks. In International Semantic Web Conference InUSe. Bonn, Germany; 2011.
. Privacy-By-Design in Federated Social Web Applications. In Web Science 2011. Koblenz, Germany; 2011. (1.09 MB)
(1.09 MB). Sem PuSH Privacy Aware and Scalable Broadcasting for Semantic Microblogging. 2011. (353.51 KB)
(353.51 KB). SemPuSH: Privacy-Aware and Scalable Broadcasting for Semantic Microblogging. In 10th International Semantic Web Conference. Bonn, Germany; 2011. (353.51 KB)
(353.51 KB). SMOB: The Best of Both Worlds. In Federated Social Web Europe Conference. 2011. (227.29 KB)
(227.29 KB). Dynamic Associative Relationships on the Linked Open Data Web. WebSci10, Extending the Frontiers of Society On-Line Conference. Raleigh, NC; 2010. (426.57 KB)
(426.57 KB). Linked Open Social Signals. In International Conference on Web Intelligence. Toronto, Canada: IEEE/WIC/ACM International Conference on Web Intelligence (WI-10); 2010. (526.46 KB)
(526.46 KB). Twarql: Tapping into the Wisdom of the Crowd. In Triplification Challenge 2010. 6th International Conference on Semantic Systems (I-SEMANTICS); 2010. (157.11 KB)
(157.11 KB)