A Novel Model and Efficient Topic Extraction for Travel Package Recommendation

Abstract

The new concept recommendation system is applying in many applications.in this project explore the online travel information of tourists to provide personalized travel package. But traditional recommendation system cant providing better travel package to tourists from various geo-graphic locations. Many technical challenges are available for designing and implementation of efficient travel package recommendation system. Proposing a new model named as tourist-area-season topic model along with Latent Dirichlet Allocation algorithm which extracts the features like locations, travel seasons of various landscapes. Introducing cocktail approach for better personalized travel package recommendation. Further Extending TAST model with the tourist-relation-areaseason topic model includes relationship among the tourists.Eventually our proposed approach is efficient to give better package recommendation for tourists.

Authors and Affiliations

Villa Satya Dhanumjaya, Aruna Rekha Gollapalli

Keywords

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  • EP ID EP28356
  • DOI -
  • Views 342
  • Downloads 6

How To Cite

Villa Satya Dhanumjaya, Aruna Rekha Gollapalli (2015). A Novel Model and Efficient Topic Extraction for Travel Package Recommendation. International Journal of Research in Computer and Communication Technology, 4(12), -. https://europub.co.uk/articles/-A-28356