Travel recommendation via author topic model based collaborative filtering

Shuhui Jiang, Xueming Qian, Jialie Shen, Tao Mei

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedingspeer-review


While automatic travel recommendation has attracted a lot of attentions, the existing approaches generally suffer from different kinds of weaknesses. For example, sparsity problem can significantly degrade the performance of traditional collaborative filtering (CF). If a user only visits very few locations, accurate similar user identification becomes very challenging due to lack of sufficient information. Motivated by this concern, we propose an Author Topic Collaborative Filtering (ATCF) method to facilitate comprehensive Points of Interest (POIs) recommendation for social media users. In our approach, the topics about user preference (e.g., cultural, cityscape, or landmark) are extracted from the textual description of photos by author topic model instead of from GPS (geo-tag). Consequently, unlike CF based approaches, even without GPS records, similar users could still be identified accurately according to the similarity of users' topic preferences. In addition, ATCF doesn’t predefine the category of travel topics. The category and user topic preference could be elicited simultaneously. Experiment results with a large test collection demonstrate various kinds of advantages of our approach.

Original languageEnglish
Title of host publicationMultiMedia Modeling - 21st International Conference, MMM 2015, Proceedings
Place of PublicationSydney; Australia
PublisherSpringer-Verlag London Ltd.
Number of pages11
ISBN (Electronic)9783319144412
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event21st International Conference on MultiMedia Modeling, MMM 2015 - Sydney, Australia
Duration: 5 Jan 20157 Jan 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference21st International Conference on MultiMedia Modeling, MMM 2015


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