User correlation discovery and dynamical profiling based on social streams

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7669 LNCS, Issue , 2012, Pages 53-62

  Zhou, Xiaokang ^a   Jin, Qun ^a  

^a WASEDA UNIVERSITY   (Japan)

Author keywords

Information Seeking; SNS; Social Stream; Stream Metaphor; User Profiling

Indexed keywords

INFORMATION SEEKING; SNS; SOCIAL STREAM; STREAM METAPHOR; USER PROFILING;

ARTIFICIAL INTELLIGENCE;

INFORMATION USE;

EID: 84870337617     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-35236-2_6     Document Type: Conference Paper

References (13)

1. Carpineto, C., Osiński, S., Romano, G., Weiss, D.: A Survey of Web Clustering Engines. ACM Computing Surveys (CSUR) 41(3) (2009)
2. Chi, E.H.: Information Seeking Can Be Social. Computer 42(3), 42-46 (2009)
3. Chen, H., Zhou, X.K., Man, H.F., Wu, Y., Ahmed, A.U., Jin, Q.: A Framework of Organic Streams: Integrating Dynamically Diversified Contents into Ubiquitous Personal Study. In: 2nd International Symposium on Multidisciplinary Emerging Networks and Systems. Xi'an (2010)
4. Zhou, X.K., Chen, H., Jin, Q., Yong, J.M.: Generating Associative Ripples of Relevant Information from a Variety of Data Streams by Throwing a Heuristic Stone. In: ACM ICUIMC 2011 (5th International Conference on Ubiquitous Information Management and Communication), Seoul, Korea (2011)
5. Zhou, X., Jin, Q.: Dynamical User Networking and Profiling Based on Activity Streams for Enhanced Social Learning. In: Leung, H., Popescu, E., Cao, Y., Lau, R.W.H., Nejdl, W. (eds.) ICWL 2011. LNCS, vol. 7048, pp. 219-225. Springer, Heidelberg (2011)
6. Signorini, A., Segre, A.M., Polgreen, P.M.: The Use of Twitter to Track Levels of Disease Activity and Public Concern in the US during the Influenza A H1N1 Pandemic. PLOS ONE 6(5) (2011)
7. Junco, R., Heiberger, G., Loken, E.: The effect of Twitter on college student engagement and grades. Journal of Computer Assisted Learning 27(2), 119-132 (2011)
8. Johnson, K.A.: The effect of Twitter posts on students' perceptions of instructor credibility. Learning Media and Technology 36(1), 21-38 (2011)
9. Srivastava, J., Cooley, R., Deshpande, M., Tan, P.-N.: Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data. ACM SIGKDD 1(2), 12-23 (2000)
10. Stumme, G., Hotho, A., Berendt, B.: Semantic Web Mining State of the Art and Future Directions. Elsevier Web Semantics: Science, Services and Agents on the World Wide Web 4(2), 124-143 (2006)
11. Poblete, B., Baeza-Yates, R.: Query-Sets: Using Implicit Feedback and Query Patterns to Organize Web Documents. In: Proc. WWW 2008, Beijing, pp. 41-48 (2008)
12. Bilenko, M., White, R.W.: Mining the Search Trails of Surfing Crowds: Identifying Relevant Websites From User Activity. In: Proc. WWW 2008, Beijing, pp. 51-60 (2008)
13. Fang, X., Liu Sheng, O.R.: LinkSelector: A Web Mining Approach to Hyperlink Selection for Web Portals. ACM Transactions on Internet Technology 4(2), 209-237 (2004)