Inferring user interests from relevance feedback with high similarity sequence data-driven clustering

Roman Y. Shtykh; Qun Jin

doi:10.1109/ISUC.2008.39

Inferring user interests from relevance feedback with high similarity sequence data-driven clustering

Roman Y. Shtykh, Qun Jin

School of Human Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Relevance feedback is an important source of information about a user and often used for usage and user modeling for further personalization of usersystem interactions. In this paper we present a method to infer the user's interests from his/her relevance feedback using an online incremental clustering method. For inference of a new interest (concept) and concept update the method uses the similarity characteristics of uniform user relevance feedback. It is fast, easy to implement and gives reasonable clustering results. We evaluate the method against two different data sets, demonstrate and discuss the outcomes.

Original language	English
Title of host publication	Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008
Pages	390-396
Number of pages	7
DOIs	https://doi.org/10.1109/ISUC.2008.39
Publication status	Published - 2008 Dec 1
Event	2nd International Symposium on Universal Communication, ISUC 2008 - Osaka, Japan Duration: 2008 Dec 15 → 2008 Dec 16

Publication series

Name	Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008

Conference

Conference	2nd International Symposium on Universal Communication, ISUC 2008
Country/Territory	Japan
City	Osaka
Period	08/12/15 → 08/12/16

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Information Systems
Software

Access to Document

10.1109/ISUC.2008.39

Cite this

Shtykh, R. Y., & Jin, Q. (2008). Inferring user interests from relevance feedback with high similarity sequence data-driven clustering. In Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008 (pp. 390-396). [4724491] (Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008). https://doi.org/10.1109/ISUC.2008.39

Inferring user interests from relevance feedback with high similarity sequence data-driven clustering. / Shtykh, Roman Y.; Jin, Qun.

Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008. 2008. p. 390-396 4724491 (Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Shtykh, RY & Jin, Q 2008, Inferring user interests from relevance feedback with high similarity sequence data-driven clustering. in Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008., 4724491, Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008, pp. 390-396, 2nd International Symposium on Universal Communication, ISUC 2008, Osaka, Japan, 08/12/15. https://doi.org/10.1109/ISUC.2008.39

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Inferring user interests from relevance feedback with high similarity sequence data-driven clustering

Abstract

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