Abstract
Recommender systems have gained great popularity in Internet applications in recent years, due to that they facilitate users greatly in information retrieval despite the explosive data growth. Similar to other popular domains such as the movie-, music-, and book- recommendations, cooking recipe selection is also a daily activity in which user experiences can be greatly improved by adopting appropriate recommendation strategies. Based on content-based and collaborative filtering approaches, we present in this paper a comprehensive recipe recommendation framework encompassing the modeling of the recipe cooking procedures and adoption of folksonomy to boost the recommendations. Empirical studies are conducted on a real data set to show that our method outperforms baselines in the recipe domain.
Original language | English |
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Title of host publication | Web Technologies and Applications : 13th Asia-Pacific Web Conference Proceedings |
Editors | Xiaoyong DU, Wenfei FAN, Jianmin WANG, Zhiyong PENG, Mohamed A. SHARAF |
Place of Publication | Berlin |
Publisher | Springer Berlin Heidelberg |
Pages | 119-130 |
Number of pages | 12 |
Volume | 6612 |
ISBN (Electronic) | 9783642202919 |
ISBN (Print) | 9783642202902 |
DOIs | |
Publication status | Published - 2011 |
Externally published | Yes |
Event | The 13th Asia-Pacific Web Conference - Beijing, China Duration: 18 Apr 2011 → 20 Apr 2011 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=11340©ownerid=5211 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 6612 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | The 13th Asia-Pacific Web Conference |
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Abbreviated title | APWeb 2011 |
Country/Territory | China |
City | Beijing |
Period | 18/04/11 → 20/04/11 |
Internet address |