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Can people collaborate to improve the relevance of search results?.
| Content Provider | CiteSeerX |
|---|---|
| Author | Agrahri, Arun Kumar Divya Anand T., M. Vidyapeetham, Amrita Vishwa Riedl, John |
| Abstract | Search engines are among the most-used resources on the internet. However, even today’s most successful search engines struggle to provide high quality search results. According to recent studies as many as 50 percent of web search sessions fail to find any relevant results for the searcher. Researchers have proposed social search techniques, in which early searchers provide feedback that is used to improve relevance for later searchers. In this paper we investigate foundational questions of social search. In particular, we directly assess the degree of agreement among users about the relevance ranking of search results. We developed a simulated search engine interface that systematically randomizes Google’s normal relevance ordering of the items presented to users. Our results show that (a) people are biased toward items in the top of the search lists, even if the list is randomized; (b) people explicit feedback is not biased and (c) people’s shared preferences do not always agree with Google’s result order. These results suggest that social search techniques might improve the effectiveness of web search engines. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Search Result Social Search Technique Simulated Search Engine Interface Relevant Result Recent Study Information Search Web Search Engine Relevance Ranking Google Result Order Successful Search Engine Social Search Information Storage Google Normal Relevance Ordering Most-used Resource Early Searcher Subject Descriptor Foundational Question Search Engine Web Search Session High Quality Search Result |
| Content Type | Text |
| Resource Type | Article |
