Travel Route Recommendation by Mining Travelogues and Community Contributed Photos using Cosine Similarity

Travel planning and recommendation is an important problem in day to day life. Social media (e.g facebook, flicker, twitter) offers great opportunities to address many riddle for instance. This paper presents a Travel route recommendation by mining travelogues and community contributed photos, which are gained by this Social media using cosine similarity method. Unlike most existing travel recommendation approaches is not only personalized to user travel interest but also able to produce the travel route rather than individual point of interest (POI) .By constructing topical package space it mined to bridge the gap between user travel preference and travel route. We used the two complementary social media travelogue and community contributed photos we map the both user and routes textual description to the topical package space and generate user package and route package it consist of Topic interest, cost, season and time. To recommend personalized travel route first famous routes are ranked according to similarity between user package and route package. Then top ranked routes are further optimised by social similar users travel record.