Mining domain knowledge from app descriptions
Abstract Domain analysis aims at gaining knowledge to a particular domain in the early stage of software development. A key challenge in domain analysis is to extract features automatically from related product artifacts. Compared with other kinds of artifacts, high volume of descriptions can be collected from App marketplaces (such as Google Play and Apple Store) easily when developing a new mobile application (App), so it is essential for the success of domain analysis to gain features and relationships from them using data analysis techniques. In this paper, we propose an approach to mine domain knowledge from App descriptions automatically, where the information of features in a single App description is firstly extracted and formally described by a Concern-based Description Model (CDM), which is based on predefined rules of feature extraction and a modified topic modeling method; then the overall knowledge in the domain is identified by classifying, clustering and merging the knowledge in the set of CDMs and topics, and the results are formalized by a Data-based Raw Domain Model (DRDM). Furthermore, we propose a quantified evaluation method for prioritizing the knowledge in DRDM. The proposed approach is validated by a series of experiments.