Leveraging app features to improve mobile app retrieval Online publication date: Mon, 26-Apr-2021
by Messaoud Chaa; Omar Nouali; Patrice Bellot
International Journal of Intelligent Information and Database Systems (IJIIDS), Vol. 14, No. 2, 2021
Abstract: The continued increase in the use of smartphones and other mobile devices has led to a substantial increase in the demand for mobile applications. With the growing availability of mobile apps, retrieving the right application from a large set has become difficult. However, the existing term-based search engines tend to retrieve relevant apps based on query terms rather than considering app features really required by users, such as functionalities, technical or user-interface characteristics. The novelty of this paper lies in extracting app features from app description and social users' reviews, extracting user-requested features and matching between them to get the feature-based score. In addition, we propose effective techniques that extract and weight features requested in the query. Finally, we combine feature-based and term-based scores together to obtain the app relevance score. The experimental results indicate that the proposed approach is effective and outperforms the state-of-the-art retrieval models for app retrieval.
Online publication date: Mon, 26-Apr-2021
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