Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

10-2008

Abstract

The leading web search engines have spent a decade building highly specialized ranking functions for English web pages. One of the reasons these ranking functions are effective is that they are designed around features such as PageRank, automatic query and domain taxonomies, and click-through information, etc. Unfortunately, many of these features are absent or altered in other languages. In this work, we show how to exploit these English features for a subset of Chinese queries which we call linguistically non-local (LNL). LNL Chinese queries have a minimally ambiguous English translation which also functions as a good English query. We first show how to identify pairs of Chinese LNL queries and their English counterparts from Chinese and English query logs. Then we show how to effectively exploit these pairs to improve Chinese relevance ranking. Our improved relevance ranker proceeds by (1) translating a query into English, (2) computing a cross-lingual relational graph between the Chinese and English documents, and (3) employing the relational ranking method of Qin et al. [15] to rank the Chinese documents. Our technique gives consistent improvements over a state-of-the-art Chinese mono-lingual ranker on web search data from the Microsoft Live China search engine.

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of the ACM International Workshop on Improving Non-English Web Searching (iNEWS 2008)

First Page

17

Last Page

24

Identifier

10.1145/1460027.1460031

Publisher

ACM Press

City or Country

Nappa Valley, California, USA

Additional URL

https://doi.org/10.1145/1460027.1460031

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