| Available via | http://dbpubs.stanford.edu/pub/2008-2 |
| Previous version | 2007-33 |
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Submitted on |
12th of February 2008 |
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Author |
Heymann, Paul; Koutrika, Georgia; Garcia-Molina, Hector |
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Title |
Can Social Bookmarking Improve Web Search? |
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Date of publication |
12th of February 2008 |
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Published in |
First ACM International Conference on Web Search and Data Mining (WSDM'08) |
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Citation |
Heymann, Paul; Koutrika, Georgia; Garcia-Molina, Hector. "Can Social Bookmarking Improve Web Search?", First ACM International Conference on Web Search and Data Mining (WSDM'08), 2008. |
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Number of pages |
11 |
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Language |
English |
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Project |
Miscellaneous |
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Type |
Conference or Journal Paper |
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Subject group |
Data Mining; Databases and the Web; Digital Libraries; Semistructured data; Miscellaneous |
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Abstract |
Social bookmarking is a recent phenomenon which has the potential to give us a great deal of data about pages on the web. One major question is whether that data can be used to augment systems like web search. To answer this question, over the past year we have gathered what we believe to be the largest dataset from a social bookmarking site yet analyzed by academic researchers. Our dataset represents about forty million bookmarks from the social bookmarking site del.icio.us. We contribute a characterization of posts to del.icio.us: how many bookmarks exist (about 115 million), how fast is it growing, and how active are the URLs being posted about (quite active). We also contribute a characterization of tags used by bookmarkers. We found that certain tags tend to gravitate towards certain domains, and vice versa. We also found that tags occur in over 50 percent of the pages that they annotate, and in only 20 percent of cases do they not occur in the page text, backlink page text, or forward link page text of the pages they annotate. We conclude that social bookmarking can provide search data not currently provided by other sources, though it may currently lack the size and distribution of tags necessary to make a significant impact. |
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Keywords |
Social Bookmarking, Web Search, Collaborative Tagging Systems |
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Contact address |
http://heymann.stanford.edu/improvewebsearch.html |
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Sponsored by |
Supported by an NSF GRFP Fellowship. |
| Fulltext source |
PDF (pdf, pdf.gz, pdf.zip)
| Management of the document by | siroker@db.stanford.edu
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