Identifying the queries' topics based-on computing domain ontology

The World Wide Web (WWW) is a massive data repository that continues to grow daily. Most people in the world are familiar with the WWW and use it to find information on any domain. However, most of the search engines usually are based on the vocabulary of queries to find information, some of the results coming back from WWW are good, and the others are not good. To resolve this problem, a large sum of past search engines have relied on the methods related to lexical-syntactic analysis and the handcrafted knowledge sources; conversely, this paper proposes a method used to explore latent semantic features in order to identify topics of queries automatically based on the domain specific ontology. Besides, we select for our experiments with two real data sets. The first is the ACM Digital Library and the second is the queries, which are input made directly by users. The experimental results are evaluated by Precision, Recall measures. We provide details of the technical implementation and extensive experimental evaluation.