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A Mobile Application Recommender System Based on User's Reviwes

Mossein, Mobasher | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 49168 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Heydarnoori, Abbas
  7. Abstract:
  8. The ever increasing growth of smart phones and their applications have led to the emergence of various platforms, i.e. online stores, for distributing them among users and providing a way for customers and developers to interact with each other. In recent years, these stores have turned into an important form of software repositories, which brought out new challenges for researchers. One of these challenges is the task of searching for suitable applications and providing simple access to them for users. Pervious work has focused on the relationships between users and applications’ contents. Among the shortcomings of these approaches, is not considering users’ reviews of applications and what they have explicitly expressed through them in these stores. Therefore, in this work, we present a novel method based on analyzing users’ reviews to tackle this challenge. Our approach exploits developers’ descriptions of applications, users’ reviews and applications’ categories in order to find similar apps and recommend them to users. Our evaluations of the proposed approach with 100 users indicate that it has a precision of 81%. Furthermore, the level of acceptance and the diversity of recommended applications by our approach are respectively 4% and approximately 100% more compared to the results of Google play
  9. Keywords:
  10. Recommender System ; Smart Phones ; Miming Software Repositories ; Application Stores ; User Reviews

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