Travel Recommendation via Author Topic Model Based Collaborative Filtering
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 lo...
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sg-smu-ink.sis_research-36262020-03-31T02:59:43Z Travel Recommendation via Author Topic Model Based Collaborative Filtering JIANG, Shuhui QIAN, Xueming SHEN, Jialie MEI, Tao 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 pre-define 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. 2015-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2626 info:doi/10.1007/978-3-319-14442-9_45 https://ink.library.smu.edu.sg/context/sis_research/article/3626/viewcontent/TravelRecommendation_2015_MM.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Multimedia Travel Recommendation Author Topic Model Computer Sciences Databases and Information Systems |
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Multimedia Travel Recommendation Author Topic Model Computer Sciences Databases and Information Systems JIANG, Shuhui QIAN, Xueming SHEN, Jialie MEI, Tao Travel Recommendation via Author Topic Model Based Collaborative Filtering |
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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 pre-define 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. |
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text |
author |
JIANG, Shuhui QIAN, Xueming SHEN, Jialie MEI, Tao |
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JIANG, Shuhui QIAN, Xueming SHEN, Jialie MEI, Tao |
author_sort |
JIANG, Shuhui |
title |
Travel Recommendation via Author Topic Model Based Collaborative Filtering |
title_short |
Travel Recommendation via Author Topic Model Based Collaborative Filtering |
title_full |
Travel Recommendation via Author Topic Model Based Collaborative Filtering |
title_fullStr |
Travel Recommendation via Author Topic Model Based Collaborative Filtering |
title_full_unstemmed |
Travel Recommendation via Author Topic Model Based Collaborative Filtering |
title_sort |
travel recommendation via author topic model based collaborative filtering |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2015 |
url |
https://ink.library.smu.edu.sg/sis_research/2626 https://ink.library.smu.edu.sg/context/sis_research/article/3626/viewcontent/TravelRecommendation_2015_MM.pdf |
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