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Cross Domain Recommendation System Using Ontology and Sequential Pattern Mining

  • S. UdayambihaiEmail author
  • V. UmaEmail author
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)

Abstract

Recommendation system is very helpful to filter the information according to the user interest and provide user personalized suggestion. Recommendation system is emerging now-a-days in many social networks like Facebook, Twitter, e-commerce etc. Cross domain recommendation system is one of the method to develop the recommendation where we can gather the knowledge from different domains and recommend most similar items related to the user search term. In this work, we try to extend cross domain recommendation by finding semantic similarity of items in Ontology, applying Collaborative Filtering and recommending user preferred items using PrefixSpan algorithm. The similarity between items can be achieved through modified Wpath method. Finally, we can recommend the most preferred items and evaluate using performance measures like F-score.

Keywords

Semantic similarity Ontology Cross domain recommendation Collaborative filtering Prefix span 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer SciencePondicherry UniversityPondicherryIndia

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