Welcome to the InfoSci Platform
Reference Hub1
Aspect-Oriented Recommender Systems

Aspect-Oriented Recommender Systems

Punam Bedi, Sumit Kr Agarwal
Copyright: © 2013 |Pages: 18
ISBN13: 9781466629585|ISBN10: 1466629584|EISBN13: 9781466629592
DOI: 10.4018/978-1-4666-2958-5.ch004
Cite Chapter Cite Chapter

MLA

Bedi, Punam, and Sumit Kr Agarwal. "Aspect-Oriented Recommender Systems." Designing, Engineering, and Analyzing Reliable and Efficient Software, edited by Hardeep Singh and Kulwant Kaur, IGI Global, 2013, pp. 55-72. https://doi.org/10.4018/978-1-4666-2958-5.ch004

APA

Bedi, P. & Agarwal, S. K. (2013). Aspect-Oriented Recommender Systems. In H. Singh & K. Kaur (Eds.), Designing, Engineering, and Analyzing Reliable and Efficient Software (pp. 55-72). IGI Global. https://doi.org/10.4018/978-1-4666-2958-5.ch004

Chicago

Bedi, Punam, and Sumit Kr Agarwal. "Aspect-Oriented Recommender Systems." In Designing, Engineering, and Analyzing Reliable and Efficient Software, edited by Hardeep Singh and Kulwant Kaur, 55-72. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2958-5.ch004

Export Reference

Mendeley
Favorite

Abstract

Recommender systems are widely used intelligent applications which assist users in a decision-making process to choose one item amongst a potentially overwhelming set of alternative products or services. Recommender systems use the opinions of members of a community to help individuals in that community by identifying information most likely to be interesting to them or relevant to their needs. Recommender systems have various core design crosscutting issues such as: user preference learning, security, mobility, visualization, interaction etc that are required to be handled properly in order to implement an efficient, good quality and maintainable recommender system. Implementation of these crosscutting design issues of the recommender systems using conventional agent-oriented approach creates the problem of code scattering and code tangling. An Aspect-Oriented Recommender System is a multi agent system that handles core design issues of the recommender system in a better modular way by using the concepts of aspect oriented programming, which in turn improves the system reusability, maintainability, and removes the scattering and tangling problems from the recommender system.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.