论文信息 - Continuous Semantics to Analyze Real-Time Data

Continuous Semantics to Analyze Real-Time Data

The traditional semantic approach has difficulties dealing with the dynamic domains involved in social, mobile, and sensor webs. Continuous semantics, which captures changing conceptualizations and relevant knowledge, can help us model those domains and analyze the related real-time data.

[1] Isabell M. Welpe,et al. Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment , 2010, ICWSM.

[2] Amit P. Sheth,et al. System and Method for Creating Semantic Web and Its Applications in Browsing, Searching, Profiling , 2001 .

[3] Peter Norvig,et al. The Unreasonable Effectiveness of Data , 2009, IEEE Intelligent Systems.

[4] Amit P. Sheth,et al. Spatio-Temporal-Thematic Analysis of Citizen Sensor Data: Challenges and Experiences , 2009, WISE.

[5] Alexandre Passant,et al. Twarql: tapping into the wisdom of the crowd , 2010, I-SEMANTICS '10.

[6] Simone Paolo Ponzetto,et al. Deriving a Large-Scale Taxonomy from Wikipedia , 2007, AAAI.

[7] Amit P. Sheth,et al. Semantic Sensor Web , 2008, IEEE Internet Computing.

[8] Amit P. Sheth,et al. What Goes Around Comes Around — Improving Linked Open Data through On-Demand Model Creation , 2010 .

[9] Amit P. Sheth,et al. Growing Fields of Interest - Using an Expand and Reduce Strategy for Domain Model Extraction , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.