Semantic Matching in APP Search

Past years, with the growth of smart-phones and applications, APP market has become an important mobile internet portal. As an important function in application market, APP search gains lots of attentions.However, mismatch between queries and APP is the most critical problem in APP search because of less text within term matching search engine. In this talk, we describe a semantic matching architecture in APP search--which mining topics and tags in big data. It enriches query and APP representations with topics and tags to achieve semantic matching in search. Some challenge must be considered: 1) How to extract tag-APP relationship from large web text. 2) How to use machine learning technologies to process de-noising and computing confidence. 3) How to hybrid ranking apps retrieved by different matching method. These will be introduced in some of our related works and as examples to describe how semantic matching is used in Tencent MyApp, an application market which serving hundreds of millions of users.