Travelogue Mining Based on User Point of Interest and Travel Sequence Generation with Route Optimization

Abstract

Nowadays, travel recommendation is basic for customer who is the game plan for traveling. There are many existing strategies which are used for travel recommendation. This framework clear up a personalized travel sequence recommendation structure using travelogs by differentiating existing various technique. It recommends personalized customers travel interest and endorse a sequence of travel interest instead of an individual motivation behind interest. The present structure can't complete the need i.e. personalized and sequential recommendation together. To deal with the issue of giving personalized and sequential travel package recommendation, a topical recommendation is made using social media data in which actually mine customer travel interest with another quality like time , cost , and time of traveling . The proposed system uses the travelogs of social media which plot customer and routes delineation to the package zone to incite customer topical package model and route topical package appear. To propose personalized POI sequence, first acclaimed routes are stratified by the comparability between customer package and route package. By then high stratified routes are more streamlined by using social similar customers travel records for more precision.

Authors and Affiliations

Mr. Nitin Pangrekar, Prof. P. R. Ugale

Keywords

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  • EP ID EP24425
  • DOI -
  • Views 240
  • Downloads 10

How To Cite

Mr. Nitin Pangrekar, Prof. P. R. Ugale (2017). Travelogue Mining Based on User Point of Interest and Travel Sequence Generation with Route Optimization. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(6), -. https://europub.co.uk/articles/-A-24425