Feedback

Mining domain knowledge from app descriptions

Liu, Y, Liu, L, Liu, H, Wang, X and Yang, H (2017) 'Mining domain knowledge from app descriptions.' Journal of Systems and Software, 133. pp. 126-144. ISSN 0164-1212

[img] Text
9969.pdf - Accepted Version
Restricted to Repository staff only until 12 August 2018.

Abstract

Domain analysis aims at obtaining 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 obtain features and relationship from them using data technologies. In this paper, we propose an approach to mine domain knowledge from App descriptions automatically. In our approach, the information of features in a single app description is firstly extracted and formally described by a Concern-based Description Model (CDM), this process 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.

Item Type: Article
Keywords: domain analysis, feature extraction, app descriptions, data analysis
Divisions: College of Liberal Arts
Date Deposited: 29 Aug 2017 10:34
Last Modified: 19 Sep 2017 16:33
Request a change to this item or report an issue Request a change to this item or report an issue
Update item (repository staff only) Update item (repository staff only)