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Related Experiment Videos

weHelp: A Reference Architecture for Social Recommender Systems.

Swapneel Sheth1, Nipun Arora1, Christian Murphy1

  • 1Department of Computer Science, Columbia University, New York, NY 10027.

IEEE/ACM International Conference on Automated Software Engineering Workshops. IEEE/ACM International Conference on Automated Software Engineering
|October 7, 2014
PubMed
Summary
This summary is machine-generated.

This paper introduces weHelp, a novel reference architecture for social recommender systems. weHelp provides a modular design template to simplify the development of application-agnostic recommendation systems based on user activities.

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Area of Science:

  • Computer Science
  • Information Systems

Background:

  • Recommender systems are widely used, but research often prioritizes algorithms over system architecture.
  • Existing architectures lack generalization, hindering broad applicability.

Purpose of the Study:

  • To introduce weHelp, a reference architecture for social recommender systems.
  • To provide a modular and domain-agnostic design template for recommendation system development.

Main Methods:

  • The paper proposes weHelp, a generalized architecture for social recommender systems.
  • The architecture leverages aggregate logged user activities for automated recommendations.

Main Results:

  • weHelp is designed to be application and domain agnostic.
  • It offers a practical template for developers to build well-modularized systems.

Conclusions:

  • A generalized architecture like weHelp can simplify the design of social recommender systems.
  • weHelp facilitates the creation of adaptable and efficient recommendation solutions.