Query Classification based on Textual Patterns Mining and Linguistic Features

We argue that verbose natural language queries used for software retrieval contain many terms that follow specific discourse rules, yet hinder retrieval. Through verbose queries, users can express complex or highly specific information needs. However, it is difficult for search engine to deal with this type of queries. Moreover, the emergence of social me-dias allows users to get opinions, suggestions, or recommendations from other users about complex information needs. In order to increase the understanding of user needs, a tasks, as the CLEF Social Book Search Classification Track, the aims is to investigates how systems can automatically identify book search requests in online forums. In this respect, we introduce in the present paper a new approach to automatically detect the type of each thread. Our proposal aims to identify book search queries by syntactic patterns, association rules between terms and tex-tual sequences mining.