The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Optimizing web search using social annotations
Abstract
This paper explores the use of social annotations to improve web search. Nowadays, many services, e.g. del.icio.us, have been developed for web users to organize and share their favorite web pages on line by using social annotations. We observe that the social annotations can benefit web search in two aspects: 1) the annotations are usually good summaries of corresponding web pages; 2) the count of annotations indicates the popularity of web pages. Two novel algorithms are proposed to incorporate the above information into page ranking: 1) SocialSimRank (SSR) calculates the similarity between social annotations and web queries; 2) SocialPageRank (SPR) captures the popularity of web pages. Preliminary experimental results show that SSR can find the latent semantic association between queries and annotations, while SPR successfully measures the quality (popularity) of a web page from the web users ’ perspective. We further evaluate the proposed methods empirically with 50 manually constructed queries and 3000 auto-generated queries on a dataset crawled from del.icio.us. Experiments show that both SSR and SPR benefit web search significantly.
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Cites
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
The anatomy of a large-scale hypertextual Web search engine
Brin, S., & Page, L. (1998) · Computer Networks and ISDN Systems · doi:10.1016/s0169-7552(98)00110-x · Cited by 16,004
Learning to rank using gradient descent
Burges, C., Shaked, T., Renshaw, E., Lazier, A., Deeds, M., Hamilton, N., & Hullender, G. (2005) · Proceedings of the 22nd international conference on Machine learning - ICML '05 · doi:10.1145/1102351.1102363 · Cited by 2,836
Cited by
Personalized recommendation in social tagging systems using hierarchical clustering
Shepitsen, A., Gemmell, J., Mobasher, B., & Burke, R. (2008) · Proceedings of the 2008 ACM conference on Recommender systems · doi:10.1145/1454008.1454048 · Cited by 522
Latent dirichlet allocation for tag recommendation
Krestel, R., Fankhauser, P., & Nejdl, W. (2009) · Proceedings of the third ACM conference on Recommender systems · doi:10.1145/1639714.1639726 · Cited by 494
Can social bookmarking improve web search?
Heymann, P., Koutrika, G., & Garcia-Molina, H. (2008) · Proceedings of the international conference on Web search and web data mining - WSDM '08 · doi:10.1145/1341531.1341558 · Cited by 434
Can all tags be used for search?
Bischoff, K., Firan, C. S., Nejdl, W., & Paiu, R. (2008) · Proceedings of the 17th ACM conference on Information and knowledge management · doi:10.1145/1458082.1458112 · Cited by 290
Evaluating similarity measures for emergent semantics of social tagging
Markines, B., Cattuto, C., Menczer, F., Benz, D., Hotho, A., & Stumme, G. (2009) · Proceedings of the 18th international conference on World wide web · doi:10.1145/1526709.1526796 · Cited by 287
Metadata
- Authors
- Bao, S., Xue, G., Wu, X., Yu, Y., Fei, B., & Su, Z.
- Venue
- Proceedings of the 16th international conference on World Wide Web
- Publisher
- ACM
- Published
- 2007-05-08
- Pages
- 501-510
- OpenAlex
- W2147709600
- Cited by
- 546
- References
- 3
- FWCI
- 51.62
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Bao, S., Xue, G., Wu, X., Yu, Y., Fei, B., & Su, Z. (2007). Optimizing web search using social annotations. Proceedings of the 16th international conference on World Wide Web. https://doi.org/10.1145/1242572.1242640
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