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Lattice navigation for collaborative filtering by means of (fuzzy) formal concept analysis

Published: 18 March 2013 Publication History

Abstract

Recommender systems rely on the opinions of a community of users to provide "recommendations" that can help users of the same community in discerning content of interest from a wide range of possibilities. Particularly, collaborative information filtering represents one of techniques widely exploited by recommender systems to suggest which items better meet the user needs and preferences. This paper introduces a model for collaborative filtering based on Formal Concept Analysis, a theoretical framework suitable to generate correlations among data through a lattice design. In particular, a fuzzy annotation of the lattice allows discovering similarities among items as well as users, arranged as a ranked list.

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  1. Lattice navigation for collaborative filtering by means of (fuzzy) formal concept analysis

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    cover image ACM Conferences
    SAC '13: Proceedings of the 28th Annual ACM Symposium on Applied Computing
    March 2013
    2124 pages
    ISBN:9781450316569
    DOI:10.1145/2480362
    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: 18 March 2013

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    Author Tags

    1. (fuzzy) formal concept analysis
    2. collaborative filtering
    3. lattice navigation algorithm
    4. recommender systems

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    March 18 - 22, 2013
    Coimbra, Portugal

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    SAC '13 Paper Acceptance Rate 255 of 1,063 submissions, 24%;
    Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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    Cited By

    View all
    • (2023)Fuzzy FCA-based Elderly Activity Recognition2023 International Conference on Computer and Applications (ICCA)10.1109/ICCA59364.2023.10401417(1-6)Online publication date: 28-Nov-2023
    • (2022)Interactive Search by Using Minimal GeneratorsComputational Intelligence and Mathematics for Tackling Complex Problems 210.1007/978-3-030-88817-6_17(147-153)Online publication date: 15-Jan-2022
    • (2021)Security-aware multi-cloud service composition by exploiting rough sets and fuzzy FCASoft Computing10.1007/s00500-020-05519-xOnline publication date: 5-Jan-2021
    • (2019)Collaborative Filtering Recommendation Algorithm Based on Linguistic Concept Lattice with Fuzzy Object2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)10.1109/ISKE47853.2019.9170332(57-63)Online publication date: Nov-2019
    • (2018)A comprehensive survey on formal concept analysis, its research trends and applicationsInternational Journal of Applied Mathematics and Computer Science10.1515/amcs-2016-003526:2(495-516)Online publication date: 15-Dec-2018
    • (2017)A recommendation system by collaborative filtering including information and characteristics on users and items2017 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI.2017.8280983(1-8)Online publication date: Nov-2017
    • (2015)Formal Concept Analysis and Information Retrieval – A SurveyFormal Concept Analysis10.1007/978-3-319-19545-2_4(61-77)Online publication date: 27-May-2015
    • (2014)Concepts reduction in formal concept analysis with fuzzy setting using Shannon entropyInternational Journal of Machine Learning and Cybernetics10.1007/s13042-014-0313-68:1(179-189)Online publication date: 26-Nov-2014
    • (2014)Linked Data-based Conceptual Modelling for Recommendation: A FCA-Based ApproachE-Commerce and Web Technologies10.1007/978-3-319-10491-1_8(71-76)Online publication date: 2014

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