Abstract
This paper explores the feasibility of including image information embedded in Web pages in relevance computation to improve search performance. In determining the ranking of Web pages against a given query, most (if not all) modern Web search engines consider two kinds of factors: text information (including title, URL, body text, anchor text, etc) and static ranking (e.g. PageRank [1]). Although images have been widely used to help represent Web pages and carry valuable information, little work has been done to take advantage of them in computing the relevance score of a Web page given a query. We propose, in this paper, a framework to contain image information in ranking functions. Preliminary experimental results show that, when image information is used properly, ranking results can be improved.
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Yu, Q., Shi, S., Li, Z., Wen, JR., Ma, WY. (2007). Improve Ranking by Using Image Information. In: Amati, G., Carpineto, C., Romano, G. (eds) Advances in Information Retrieval. ECIR 2007. Lecture Notes in Computer Science, vol 4425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71496-5_62
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DOI: https://doi.org/10.1007/978-3-540-71496-5_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71494-1
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