Optimizing web search using social annotations
Optimizing web search using social annotations
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DOI：
10.1145/1242572.1242640
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发表时间：
2007-05
期刊：
影响因子：
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通讯作者：
Shenghua Bao;Gui-Rong Xue;Xiaoyuan Wu;Yong Yu;Ben Fei;Zhong Su
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文献类型：
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作者：
Shenghua Bao;Gui-Rong Xue;Xiaoyuan Wu;Yong Yu;Ben Fei;Zhong Su
本文探讨了使用社会化注释来改善网络搜索。如今，已经开发了许多服务，例如del.icio.us，用于web用户通过使用社交注释来在线组织和共享他们喜爱的网页。我们观察到，社会化注释可以在两个方面有益于网络搜索：1）注释通常是相应网页的良好摘要; 2）注释的计数指示网页的受欢迎程度。提出了两种新的算法将上述信息纳入页面排名：1）SocialSimRank（SSR）计算社交注释和Web查询之间的相似度; 2）SocialPageRank（SPR）捕获网页的流行度。初步的实验结果表明，SSR可以发现查询和注释之间的潜在语义关联，而SPR成功地衡量质量（流行度）的网页从Web用户的角度。我们进一步评估所提出的方法经验与50手动构建的查询和3000自动生成的查询数据集craffile从美味。实验结果表明，SSR和SPR都能显著提高网络搜索效率。
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.