Site icon Premium Researchers

Personalized Travel Sequence Recommendation on Multi-Source Big Social Media

Do You Have New or Fresh Topic? Send Us Your Topic

Personalized Travel Sequence Recommendation on Multi-Source Big Social Media

Abstract:

Big data increasingly benefit both research and industrial area such as health care, finance service and commercial recommendation. This paper presents a personalized travel sequence recommendation from both travelogues and community contributed photos and the heterogeneous metadata (e.g., tags, geo-location, and date taken) associated with these photos.

Unlike most existing travel recommendation approaches, our approach is not only personalized to user’s travel interest but also able to recommend a travel sequence rather than individual Points of Interest (POIs). Topical package space including representative tags, the distributions of cost, visiting time and visiting season of each topic, is mined to bridge the vocabulary gap between user travel preference and travel routes.

We take advantage of the complementary of two kinds of social media: travelogue and community contributed photos. We map both user’s and routes’ textual descriptions to the topical package space to get user topical package model and route topical package model (i.e., topical interest, cost, time and season).

To recommend personalized POI sequence, first, famous routes are ranked according to the similarity between user package and route package. Then top ranked routes are further optimized by social similar users’ travel records. Representative images with viewpoint and seasonal diversity of POIs are shown to offer a more comprehensive impression.

We evaluate our recommendation system on a collection of 7 million Flickr images uploaded by 7,387 users and 24,008 travelogues covering 864 travel POIs in nine famous cities, and show its effectiveness. We also contribute a new dataset with more than 200 K photos with heterogeneous metadata in nine famous cities.

 

 

Do You Have New or Fresh Topic? Send Us Your Topic 

 

 

education repository

Personalized Travel Sequence Recommendation on Multi-Source Big Social Media

Not What You Were Looking For? Send Us Your Topic

INSTRUCTIONS AFTER PAYMENT

After making payment, kindly send the following:

» Send the above details to our email; contact@premiumresearchers.com or to our support phone number; (+234) 0813 2546 417 . As soon as details are sent and payment is confirmed, your project will be delivered to you within minutes.