Chinese query expansion based on topic-relevant terms

In this paper we present a Chinese query expansion model based on topic-relevant terms which were acquired from the Google search engine automatically. In contrast to earlier methods, our queries are expanded by adding those terms that are most relevant to the concept of the query, rather than selecting terms that are relevant to the query terms. Firstly, we use automatically extracted short terms from document sets to build indexes and use the short terms in both the query and documents to do initial retrieval. Next, we acquire the topic-relevant terms of the short terms from the Internet and the top 30 initial retrieval documents. Finally, we use the topic-relevant terms to do query expansion. The experiments show that our query expansion model is more effective than the standard Rocchio expansion.