Learning a Replacement Model for Query Segmentation with Consistency in Search Logs

Query segmentation is to split a query into a sequence of non-overlapping segments that completely cover all tokens in the query. The majority of methods are unsupervised, however, they are usually not as accurate as supervised methods due to the lack of guidance from labeled data. In this paper, we propose a new paradigm of learning a replacement model… CONTINUE READING