Scope of context awareness in cross domain recommender system – a brief review

  • Abstract
  • Keywords
  • References
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  • Abstract

    Cross Domain Recommender Systems (CDRS) and Context Aware Recommender systems (CARS) are the major emerging and fast growing research topics in the active research field of Recommender Systems. For personalized recommendation, CARS utilizes different contexts in a particular domain along with user ratings, whereas CDRS utilizes data from one or more domains to make predictions to the users either one of the domains by using utilizing the context similarity among those domains. These research areas are still new and largely unexplored. Here we are surveying different researches happened in each field of Recommender System(RS) separately and thus tries to find out the scope of combining them to solve the state of the art problems in RS research and the possibilities of improving the efficiency and accuracy of RS. CDRS is emphasized mainly only the historical data of both source and target domains only, but the thing is that users choice may change according to different temporal contexts such as time, location etc. Both can complement each other for the betterment of recommendation tasks. As a result of this survey, an outline of the framework is proposed for Cross Domain-Context Aware Recommender System (CDCARS).




  • Keywords

    Cross Domain Recommender Systems; Context Aware Recommender Systems; Cross Domain-Context Aware Recommender System (CDCARS); Multi Domain RS; Contextual Modeling; Evaluation Metrics.

  • References

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Article ID: 19108
DOI: 10.14419/ijet.v7i4.19108

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