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Author, Editor

Author(s):

Schenkel, Ralf
Crecelius, Tom
Kacimi, Mouna
Michel, Sebastian
Neumann, Thomas
Parreira, Josiane Xavier
Weikum, Gerhard

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Not MPG Author(s):

Michel, Sebastian

Editor(s):





BibTeX cite key*:

SchenkelCKMNPW_SIGIR08

Title, Booktitle

Title*:

Efficient Top-k Querying over Social-Tagging Networks

Booktitle*:

Proceedings of the 31st Annual International ACM SIGIR Conference on Research & Development on Information Retrieval (SIGIR 2008)

Event, URLs

URL of the conference:

http://www.sigir2008.org/

URL for downloading the paper:


Event Address*:

Singapore, Singapore

Language:

English

Event Date*
(no longer used):


Organization:


Event Start Date:

20 July 2008

Event End Date:

24 July 2008

Publisher

Name*:

ACM

URL:

http://www.acm.org

Address*:

New York, USA

Type:


Vol, No, Year, pp.

Series:


Volume:


Number:


Month:


Pages:

523-530

Year*:

2008

VG Wort Pages:


ISBN/ISSN:

978-1-60558-164-4

Sequence Number:


DOI:




Note, Abstract, ©


(LaTeX) Abstract:

Online communities have become popular for publishing and searching content, as well as for finding and connecting to other users. User-generated content includes, for example, personal blogs, bookmarks, and digital photos. These items can be annotated and rated by different users, and these
social tags and derived user-specific scores can be leveraged for searching relevant content and discovering subjectively interesting items. Moreover, the relationships among users can also be taken into consideration for ranking search results, the intuition being that you trust the recommendations of your close friends more than those of your casual acquaintances.

Queries for tag or keyword combinations that compute and rank the top-k results thus face a large variety of options that complicate the query processing and pose efficiency challenges. This paper addresses these issues by developing an incremental top-k algorithm with two-dimensional expansions: social expansion considers the strength of relations among users, and semantic expansion considers the relatedness of different tags. It presents a new algorithm, based on principles of threshold algorithms, by folding friends and related tags into the search space in an incremental on-demand manner. The excellent performance of the method is demonstrated by an experimental evaluation on three real-world datasets, crawled from deli.cio.us, Flickr, and LibraryThing.



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Access Level:

Institute

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Databases and Information Systems Group

Audience:

popular

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort



BibTeX Entry:

@INPROCEEDINGS{SchenkelCKMNPW_SIGIR08,
AUTHOR = {Schenkel, Ralf and Crecelius, Tom and Kacimi, Mouna and Michel, Sebastian and Neumann, Thomas and Parreira, Josiane Xavier and Weikum, Gerhard},
TITLE = {Efficient Top-k Querying over Social-Tagging Networks},
BOOKTITLE = {Proceedings of the 31st Annual International ACM SIGIR Conference on Research & Development on Information Retrieval (SIGIR 2008)},
PUBLISHER = {ACM},
YEAR = {2008},
PAGES = {523--530},
ADDRESS = {Singapore, Singapore},
ISBN = {978-1-60558-164-4},
}


Entry last modified by Martin Theobald, 04/15/2009
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Editor(s)
Ralf Schenkel
Created
04/03/2008 12:18:18 PM
Revisions
7.
6.
5.
4.
3.
Editor(s)
Martin Theobald
Tom Crecelius
Olha Condor
Olha Condor
Olha Condor
Edit Dates
04/15/2009 02:08:32 PM
03/16/2009 04:30:41 PM
18.11.2008 11:34:38
17.11.2008 15:08:16
23.09.2008 16:43:24