Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings |
| Subtitle of host publication | 2007 Latin American Web Conference, LA-WEB 2007 |
| Pages | 32-41 |
| Number of pages | 10 |
| Publication status | Published - 2007 |
| Event | 2007 Latin American Web Conference, LA-WEB 2007 - Santiago, Chile Duration: 31 Oct 2007 → 2 Nov 2007 |
Publication series
| Name | Proceedings - 2007 Latin American Web Conference, LA-WEB 2007 |
|---|
Abstract
Collaborative tagging, i.e. the process of assigning metadata in the form of keywords to shared content by many users, has emerged as an important way to provide information about resources on the Web and elsewhere. Such keywords (tags) are used to enable the organization of information within personal information spaces, such as photo collections, but can also be shared, allowing browsing and searching with the help of tags attached by other users to information resources from the Web. Recent research has shown that such tag distributions stabilize over time and can be used to improve search on the Web. In this paper we are interested in another aspect, namely how they characterize the user and enable personalized recommendations. Using data from a frequently used music search portal, Last.fm, we analyze tag usage and statistics and investigate the use of tag-based user profiles in contrast to conventional user profiles based on song and track usage. We specify recommendation algorithms based on tag user profiles, and explore how collaborative filtering recommendations based on these tag profiles are different from recommendations based on song/track profiles. Finally, we describe a new search-based method, which uses tags to recommend songs interesting to a user, yielding substantially improved results. The paper finishes with a discussion of some future work to further improve tag-based search and recommendation in community web sites.
ASJC Scopus subject areas
- Computer Science(all)
- General Computer Science
- Computer Science(all)
- Computer Science Applications
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Proceedings: 2007 Latin American Web Conference, LA-WEB 2007. 2007. p. 32-41 4383156 (Proceedings - 2007 Latin American Web Conference, LA-WEB 2007).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - The benefit of using tag-based profiles
AU - Firan, Claudiu S.
AU - Nejdl, Wolfgang
AU - Paiu, Raluca
PY - 2007
Y1 - 2007
N2 - Collaborative tagging, i.e. the process of assigning metadata in the form of keywords to shared content by many users, has emerged as an important way to provide information about resources on the Web and elsewhere. Such keywords (tags) are used to enable the organization of information within personal information spaces, such as photo collections, but can also be shared, allowing browsing and searching with the help of tags attached by other users to information resources from the Web. Recent research has shown that such tag distributions stabilize over time and can be used to improve search on the Web. In this paper we are interested in another aspect, namely how they characterize the user and enable personalized recommendations. Using data from a frequently used music search portal, Last.fm, we analyze tag usage and statistics and investigate the use of tag-based user profiles in contrast to conventional user profiles based on song and track usage. We specify recommendation algorithms based on tag user profiles, and explore how collaborative filtering recommendations based on these tag profiles are different from recommendations based on song/track profiles. Finally, we describe a new search-based method, which uses tags to recommend songs interesting to a user, yielding substantially improved results. The paper finishes with a discussion of some future work to further improve tag-based search and recommendation in community web sites.
AB - Collaborative tagging, i.e. the process of assigning metadata in the form of keywords to shared content by many users, has emerged as an important way to provide information about resources on the Web and elsewhere. Such keywords (tags) are used to enable the organization of information within personal information spaces, such as photo collections, but can also be shared, allowing browsing and searching with the help of tags attached by other users to information resources from the Web. Recent research has shown that such tag distributions stabilize over time and can be used to improve search on the Web. In this paper we are interested in another aspect, namely how they characterize the user and enable personalized recommendations. Using data from a frequently used music search portal, Last.fm, we analyze tag usage and statistics and investigate the use of tag-based user profiles in contrast to conventional user profiles based on song and track usage. We specify recommendation algorithms based on tag user profiles, and explore how collaborative filtering recommendations based on these tag profiles are different from recommendations based on song/track profiles. Finally, we describe a new search-based method, which uses tags to recommend songs interesting to a user, yielding substantially improved results. The paper finishes with a discussion of some future work to further improve tag-based search and recommendation in community web sites.
UR - http://www.scopus.com/inward/record.url?scp=47849087949&partnerID=8YFLogxK
U2 - 10.1109/LAWEB.2007.4383156
DO - 10.1109/LAWEB.2007.4383156
M3 - Conference contribution
AN - SCOPUS:47849087949
SN - 978-0-7695-3008-6
T3 - Proceedings - 2007 Latin American Web Conference, LA-WEB 2007
SP - 32
EP - 41
BT - Proceedings
T2 - 2007 Latin American Web Conference, LA-WEB 2007
Y2 - 31 October 2007 through 2 November 2007
ER -