Recommendation of places of interest for tourists from geo-tagged data using machine learning approaches
by R. Sujithra Kanmani; V. Uma
International Journal of Knowledge Management in Tourism and Hospitality (IJKMTH), Vol. 2, No. 2, 2019

Abstract: With the advanced technologies like global positioning system (GPS), personalised travel recommendations can be done considering user preferences of places by collecting information from diverse sources. Social media websites like Twitter and Facebook can be leveraged to extract geo-tagged data. Geographical location of the user reflects the user preference and can be semantically categorised based on its type using four-square classifier. For identifying similar users preferences of location, collaborative filtering is applied in this work. User preferences are identified from users visit histories and extracted preferences are represented in form of sequences. The frequent sequences are mined using prefix-span algorithm. Sequential rules are mined by applying CM-rules algorithm. By knowing the sequential rules, the subsequent place of interest which is nearer to the user's current location is recommended using k-nearest neighbour (kNN) algorithm. The proposed system has been implemented and the system is found to be promising in terms of accuracy and execution time.

Online publication date: Mon, 22-Jun-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Knowledge Management in Tourism and Hospitality (IJKMTH):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com