Using English information in Non-English web search

• Main Authors: GAO, Wei, ZHOU, Ming
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2008
• Subjects: Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/4600; https://ink.library.smu.edu.sg/context/sis_research/article/5603/viewcontent/p17_gao.pdf
• Institution: Singapore Management University

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.