Optimizing web search using social annotations Export

@inproceedings{citeulike:1288940, abstract = {This paper explores the use of social annotations to improve websearch. Nowadays, many services, e.g. del.icio.us, have been developed for web users to organize and share their favorite webpages 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 webpages; 2) the count of annotations indicates the popularity of webpages. Two novel algorithms are proposed to incorporate the above information into page ranking: 1) SocialSimRank (SSR)calculates the similarity between social annotations and webqueries; 2) SocialPageRank (SPR) captures the popularity of webpages. 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 webpage 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 crawledfrom delicious. Experiments show that both SSR and SPRbenefit web search significantly.}, address = {New York, NY, USA}, author = {Bao, Shenghua and Xue, Guirong and Wu, Xiaoyuan and Yu, Yong and Fei, Ben and Su, Zhong}, booktitle = {WWW '07: Proceedings of the 16th international conference on World Wide Web}, citeulike-article-id = {1288940}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1242572.1242640}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1242572.1242640}, doi = {10.1145/1242572.1242640}, isbn = {9781595936547}, keywords = {folksonomy, search, social-annotation, web}, pages = {501--510}, posted-at = {2008-01-10 15:51:26}, priority = {2}, publisher = {ACM Press}, title = {Optimizing web search using social annotations}, url = {http://dx.doi.org/10.1145/1242572.1242640}, year = {2007} }

TY - CONF ID - citeulike:1288940 L3 - citeulike-article-id:1288940 N2 - This paper explores the use of social annotations to improve websearch. Nowadays, many services, e.g. del.icio.us, have been developed for web users to organize and share their favorite webpages 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 webpages; 2) the count of annotations indicates the popularity of webpages. Two novel algorithms are proposed to incorporate the above information into page ranking: 1) SocialSimRank (SSR)calculates the similarity between social annotations and webqueries; 2) SocialPageRank (SPR) captures the popularity of webpages. 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 webpage 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 crawledfrom delicious. Experiments show that both SSR and SPRbenefit web search significantly. SN - 9781595936547 AD - New York, NY, USA EP - 510 TI - Optimizing web search using social annotations PB - ACM Press T2 - WWW '07: Proceedings of the 16th international conference on World Wide Web SP - 501 KW - folksonomy KW - search KW - social-annotation KW - web AU - Bao, Shenghua AU - Xue, Guirong AU - Wu, Xiaoyuan AU - Yu, Yong AU - Fei, Ben AU - Su, Zhong PY - 2007/// UR - http://dx.doi.org/10.1145/1242572.1242640 ER -