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Issue No.01 - January/February (2009 vol.13)
pp: 76-80
Amit Sheth , Wright State University
Meenakshi Nagarajan , Wright State University
ABSTRACT
User-generated textual content on social media has unique characteristics owing to the interpersonal and interactional nature of the communication medium. Web 3.0 applications that aim to automatically create accurate annotations from user-generated content to common reference models will have to invariably deal with the informal nature of this content. In this article, the authors discuss opportunities in addressing challenges posed by this content by supplementing traditional statistical and NLP techniques with domain knowledge.
INDEX TERMS
Semantic services, Internet computing, user-generated content, social Semantic Web, domain knowledge, Semantic Web 2.0
CITATION
Amit Sheth, Meenakshi Nagarajan, "Semantics-Empowered Social Computing", IEEE Internet Computing, vol.13, no. 1, pp. 76-80, January/February 2009, doi:10.1109/MIC.2009.21
REFERENCES
1. A. Sheth et al., "Managing Semantic Content for the Web," IEEE Internet Computing, vol. 6, no. 4, 2002, pp. 80–87.
2. D. Nadeau and S. Sekine, "A Survey of Named Entity Recognition and Classification," Lingvisticae Investigationes, vol. 30, no. 1, 2007, pp. 3–26.
3. M. Nagarajan et al., Monetizing User Activity on Social Networks, tech. report, Kno.e.sis Ctr., Wright State Univ., 2008; http://knoesis.wright.edu/library/download MonetizingUserActivity-TechReport.pdf .
4. J. Grace et al., Artist Ranking through Analysis of Online Community Contents, tech. report, Kno.e.sis Ctr., Wright State Univ., 2007; http://knoesis.wright.edu/library/publications 200711010839-submission.pdf.
5. A. Alba et al., "Applications of Voting Theory to Information Mashups," to be published in Proc. 2nd IEEE Int'l Conf. Semantic Computing (ICSC 08), IEEE CS Press, 2008.
6. P. Mika, Social Networks and the Semantic Web (Semantic Web and Beyond), Springer-Verlag, 2007.
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