Abstract
Given the vast amount of information, including the numerous points-of-interest (POIs) and the various hotels, available on travel websites such as tripadvisor or booking, a recommender system would help users, who are planning their next trip, filter out unnecessary information based on their requirements. We improved our previous work on a recommendation system that was intended to facilitate the generation of daily travel itineraries. We used the X-Means clustering algorithm to divide all attraction sites and hotels into groups according to geographical location. Meanwhile, a Word2Vec model was trained using the Wikipedia text corpus to obtain similar tags of specific ones. A tag-based mapping algorithm was applied to create a list of candidate attractions that best match with the user’s favorite spots. Finally, by taking into account the weather information, our recommender can further refine the list of candidate attractions and work out a daily itinerary that involves desirable hotels and attractions. The shortest itinerary (SI) and the itinerary with the highest performance/price ratio (MEI) will then be produced for user selection. The results of a series of experiments demonstrated that, compared to others, our personalized recommender for travel planning can provide a more appealing and detailed travel plan containing daily itineraries for users.
Highlights
It is time-consuming for users to pick up a desirable travel itinerary on various travel websites
We proposed a personalized recommender for travel itineraries [18], which uses the K-Means clustering and tag-based recommendation algorithms
Based on the favorite POIs specified by users, tags of all POIs are collected from travel websites and the recommender calculates the tag
Summary
It is time-consuming for users to pick up a desirable travel itinerary on various travel websites. 1 https://www.mafengwo.cn/mdd/cityroute/10065_5934.html figure out a plan on their own (e.g. elong.com2); and (3) accepting information on the origins, destinations, and travel date from users and in return, offering the driving routes and hotels (e.g. trippy.com). 1 https://www.mafengwo.cn/mdd/cityroute/10065_5934.html figure out a plan on their own (e.g. elong.com2); and (3) accepting information on the origins, destinations, and travel date from users and in return, offering the driving routes and hotels (e.g. trippy.com3) These systems are rarely seen to provide customized travel itineraries.
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