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Knowledge-aware and conversational recommender systems

Authors:

Markus ZankerAuthors Info & Claims

RecSys '18: Proceedings of the 12th ACM Conference on Recommender Systems

Pages 521 - 522

https://doi.org/10.1145/3240323.3240338

Published: 27 September 2018 Publication History

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Abstract

More and more precise and powerful recommendation algorithms and techniques have been proposed over the last years able to effectively assess users' tastes and predict information that would probably be of interest for them. Most of these approaches rely on the collaborative paradigm (often exploiting machine learning techniques) and do not take into account the huge amount of knowledge, both structured and non-structured ones, describing the domain of interest for the recommendation engine. The aim of knowledge-aware and conversational recommender systems is to go beyond the traditional accuracy goal and to start a new generation of algorithms and interactive approaches which exploit the knowledge encoded in ontological and logic-based knowledge bases, knowledge graphs as well as the semantics emerging from the analysis and exploitation of semi-structured textual sources.

References

[1]

Robert Burke. 2000. Knowledge-based recommender systems. Encyclopedia of Library and Information Systems: Vol. 6.(Supplement 32).

Google Scholar

[2]

Simona Colucci, Tommaso Di Noia, Eugenio Di Sciascio, Francesco M. Donini, Azzurra Ragone, and Raffaele Rizzi. 2006. A Semantic-based Fully Visual Application for Matchmaking and Query Refinement in B2C e-Marketplaces. In Proceedings of the 8th International Conference on Electronic Commerce: The New e-Commerce: Innovations for Conquering Current Barriers, Obstacles and Limitations to Conducting Successful Business on the Internet (ICEC '06). ACM, 174--184.

Digital Library

Google Scholar

[3]

Marco de Gemmis, Pasquale Lops, Cataldo Musto, Fedelucio Narducci, and Giovanni Semeraro. 2015. Semantics-aware content-based recommender systems. In Recommender Systems Handbook. Springer, 119--159.

Digital Library

Google Scholar

[4]

Tommaso Di Noia, Corrado Magarelli, Andrea Maurino, Matteo Palmonari, and Anisa Rula. 2018. Using Ontology-Based Data Summarization to Develop Semantics-Aware Recommender Systems. In The Semantic Web - 15th International Conference, ESWC 2018, Heraklion, Crete, Greece, June 3--7, 2018, Proceedings. Springer New York, 128--144.

Google Scholar

[5]

Tommaso Di Noia and Vito Claudio Ostuni. 2015. Recommender systems and linked open data. In Reasoning Web International Summer School. Springer, 88--113.

Google Scholar

[6]

Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, and Markus Zanker. 2006. An integrated environment for the development of knowledge-based recommender applications. International Journal of Electronic Commerce 11, 2 (2006), 11--34.

Digital Library

Google Scholar

[7]

Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, and Markus Zanker. 2015. Constraint-Based Recommender Systems. In Recommender Systems Handbook. 161--190.

Google Scholar

[8]

Cynthia A Thompson, Mehmet H Goker, and Pat Langley. 2004. A personalized system for conversational recommendations. Journal of Artificial Intelligence Research 21 (2004), 393--428.

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Cited By

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Anelli VFerrara AMusto CNarducci FRagone AZanker M(2024)Sixth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS)Proceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3687114(1245-1249)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3687114
Spillo GBottalico FMusto CDe Gemmis MLops PSemeraro G(2024)Evaluating Content-based Pre-Training Strategies for a Knowledge-aware Recommender System based on Graph Neural NetworksProceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3627043.3659548(165-171)Online publication date: 22-Jun-2024
https://dl.acm.org/doi/10.1145/3627043.3659548
Anelli VBasile PDe Melo GDonini FFerrara AMusto CNarducci FRagone AZanker M(2023)Fifth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS)Proceedings of the 17th ACM Conference on Recommender Systems10.1145/3604915.3608759(1259-1262)Online publication date: 14-Sep-2023
https://dl.acm.org/doi/10.1145/3604915.3608759
Show More Cited By

Index Terms

Knowledge-aware and conversational recommender systems
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Semantic networks
2. Information systems
  1. Information retrieval
    1. Document representation
      1. Ontologies
    2. Retrieval tasks and goals
      1. Recommender systems
  2. World Wide Web
    1. Web searching and information discovery
      1. Social recommendation

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Information & Contributors

Information

Published In

RecSys '18: Proceedings of the 12th ACM Conference on Recommender Systems

September 2018

600 pages

ISBN:9781450359016

DOI:10.1145/3240323

General Chairs:
Sole Pera
Boise State University
,
Michael Ekstrand
Boise State University
,
Program Chairs:
Xavier Amatriain
Curai, USA
,
John O'Donovan
University of California, Santa Barbara

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 September 2018

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Conference

RecSys '18

Sponsor:

SIGCHI

RecSys '18: Twelfth ACM Conference on Recommender Systems

October 2, 2018

British Columbia, Vancouver, Canada

Acceptance Rates

RecSys '18 Paper Acceptance Rate 32 of 181 submissions, 18%;

Overall Acceptance Rate 254 of 1,295 submissions, 20%

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Citations

Cited By

View all

Anelli VFerrara AMusto CNarducci FRagone AZanker M(2024)Sixth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS)Proceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3687114(1245-1249)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3687114
Spillo GBottalico FMusto CDe Gemmis MLops PSemeraro G(2024)Evaluating Content-based Pre-Training Strategies for a Knowledge-aware Recommender System based on Graph Neural NetworksProceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3627043.3659548(165-171)Online publication date: 22-Jun-2024
https://dl.acm.org/doi/10.1145/3627043.3659548
Anelli VBasile PDe Melo GDonini FFerrara AMusto CNarducci FRagone AZanker M(2023)Fifth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS)Proceedings of the 17th ACM Conference on Recommender Systems10.1145/3604915.3608759(1259-1262)Online publication date: 14-Sep-2023
https://dl.acm.org/doi/10.1145/3604915.3608759
Hegiansyah MBaizal Z(2023)Ontology-Based Conversational Recommender System for Smartphone Domain2023 11th International Conference on Information and Communication Technology (ICoICT)10.1109/ICoICT58202.2023.10262611(52-56)Online publication date: 23-Aug-2023
https://doi.org/10.1109/ICoICT58202.2023.10262611
Richtman FBaizal Z(2023)Ontology-based Conversational Recommender System for Recommending Bicycle2023 International Conference on Advancement in Data Science, E-learning and Information System (ICADEIS)10.1109/ICADEIS58666.2023.10271028(1-6)Online publication date: 2-Aug-2023
https://doi.org/10.1109/ICADEIS58666.2023.10271028
Cheng KLi XXu YDong XSun Y(2022)PGEProceedings of the VLDB Endowment10.14778/3514061.351407415:6(1288-1296)Online publication date: 22-Jun-2022
https://dl.acm.org/doi/10.14778/3514061.3514074
Anelli VBasile Pde Melo GDonini FFerrara AMusto CNarducci FRagone AZanker M(2022)Fourth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS)Proceedings of the 16th ACM Conference on Recommender Systems10.1145/3523227.3547412(663-666)Online publication date: 12-Sep-2022
https://dl.acm.org/doi/10.1145/3523227.3547412
Anelli VDi Noia TDi Sciascio EFerrara AMancino A(2021)Sparse Feature Factorization for Recommender Systems with Knowledge GraphsProceedings of the 15th ACM Conference on Recommender Systems10.1145/3460231.3474243(154-165)Online publication date: 13-Sep-2021
https://dl.acm.org/doi/10.1145/3460231.3474243
Anelli VBelli LDeldjoo YDi Noia TFerrara ANarducci FPomo C(2021)Pursuing Privacy in Recommender Systems: the View of Users and Researchers from Regulations to ApplicationsProceedings of the 15th ACM Conference on Recommender Systems10.1145/3460231.3473326(838-841)Online publication date: 13-Sep-2021
https://dl.acm.org/doi/10.1145/3460231.3473326
Anelli VBasile PDi Noia TDonini FMusto CNarducci FZanker M(2021)Third Knowledge-aware and Conversational Recommender Systems Workshop (KaRS)Proceedings of the 15th ACM Conference on Recommender Systems10.1145/3460231.3470933(806-809)Online publication date: 13-Sep-2021
https://dl.acm.org/doi/10.1145/3460231.3470933
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Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion

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