Mining anchor text trends for retrieval

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Abstract

Anchor text has been considered as a useful resource to complement the representation of target pages and is broadly used in web search. However, previous research only uses anchor text of a single snapshot to improve web search. Historical trends of anchor text importance have not been well modeled in anchor text weighting strategies. In this paper, we propose a novel temporal anchor text weighting method to incorporate the trends of anchor text creation over time, which combines historical weights of anchor text by propagating the anchor text weights among snapshots over the time axis. We evaluate our method on a real-world web crawl from the Stanford WebBase. Our results demonstrate that the proposed method can produce a significant improvement in ranking quality. © 2010 Springer-Verlag Berlin Heidelberg.

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Dai, N., & Davison, B. D. (2010). Mining anchor text trends for retrieval. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5993 LNCS, pp. 127–139). Springer Verlag. https://doi.org/10.1007/978-3-642-12275-0_14

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