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Cross-lingual keyword recommendation using latent topics

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HetRec '10: Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems

Pages 52 - 56

https://doi.org/10.1145/1869446.1869454

Published: 26 September 2010 Publication History

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Abstract

Multi-lingual text processing is important for content-based and hybrid recommender systems. It helps recommender systems extract content information from broader sources. It also enables systems to recommend items in a user's native language. We propose a cross-lingual keyword recommendation method, which is built on an extended latent Dirichlet allocation model, for extracting latent features from parallel corpora. With this model, the proposed method can recommend keywords from text written in different languages. We evaluate the proposed method using a cross-lingual bibliographic database that contains both English and Japanese abstracts and keywords and show that the proposed method can recommend keywords from abstracts in a cross-lingual environment with almost the same accuracy as in a monolingual environment.

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Cited By

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Liu PZhang LGulla J(2021)Multilingual Review-aware Deep Recommender System via Aspect-based Sentiment AnalysisACM Transactions on Information Systems10.1145/343204939:2(1-33)Online publication date: 14-Jan-2021
https://dl.acm.org/doi/10.1145/3432049
Komiya KSasaki MShinnou HKotani Y(2017)Cross-lingual Product Recommendation System Using Collaborative FilteringJournal of Natural Language Processing10.5715/jnlp.24.57924:4(579-596)Online publication date: 2017
https://doi.org/10.5715/jnlp.24.579
Vulić IDe Smet WTang JMoens M(2015)Probabilistic topic modeling in multilingual settings: An overview of its methodology and applicationsInformation Processing & Management10.1016/j.ipm.2014.08.00351:1(111-147)Online publication date: Jan-2015
https://doi.org/10.1016/j.ipm.2014.08.003
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Index Terms

Cross-lingual keyword recommendation using latent topics
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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Published In

HetRec '10: Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems

September 2010

84 pages

ISBN:9781450304078

DOI:10.1145/1869446

Conference Chairs:
Peter Brusilovsky
University of Pittsburgh
,
Iván Cantador
Universidad Autónoma de Madrid, Spain
,
Yehuda Koren
Yahoo! Labs
,
Tsvi Kuflik
University of Haifa, Israel
,
Markus Weimer
Yahoo! Labs

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 26 September 2010

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RecSys '10

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SIGCHI

RecSys '10: Fourth ACM Conference on Recommender Systems

September 26, 2010

Barcelona, Spain

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Cited By

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Liu PZhang LGulla J(2021)Multilingual Review-aware Deep Recommender System via Aspect-based Sentiment AnalysisACM Transactions on Information Systems10.1145/343204939:2(1-33)Online publication date: 14-Jan-2021
https://dl.acm.org/doi/10.1145/3432049
Komiya KSasaki MShinnou HKotani Y(2017)Cross-lingual Product Recommendation System Using Collaborative FilteringJournal of Natural Language Processing10.5715/jnlp.24.57924:4(579-596)Online publication date: 2017
https://doi.org/10.5715/jnlp.24.579
Vulić IDe Smet WTang JMoens M(2015)Probabilistic topic modeling in multilingual settings: An overview of its methodology and applicationsInformation Processing & Management10.1016/j.ipm.2014.08.00351:1(111-147)Online publication date: Jan-2015
https://doi.org/10.1016/j.ipm.2014.08.003
Vulić IDe Smet WMoens M(2012)Cross-language information retrieval models based on latent topic models trained with document-aligned comparable corporaInformation Retrieval10.1007/s10791-012-9200-516:3(331-368)Online publication date: 5-May-2012
https://doi.org/10.1007/s10791-012-9200-5
Hassan EGarg VHaque SChaudhury SGopal M(2011)Searching OCR'ed TextProceedings of the 2011 International Conference on Document Analysis and Recognition10.1109/ICDAR.2011.244(1210-1214)Online publication date: 18-Sep-2011
https://dl.acm.org/doi/10.1109/ICDAR.2011.244
Vulić IDe Smet WMoens M(2011)Cross-language information retrieval with latent topic models trained on a comparable corpusProceedings of the 7th Asia conference on Information Retrieval Technology10.1007/978-3-642-25631-8_4(37-48)Online publication date: 18-Dec-2011
https://dl.acm.org/doi/10.1007/978-3-642-25631-8_4

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