A comparison of information retrieval models

M. Pannu, Anne James, Bob Bird

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Abstract

    The personalization process can either be focused on individuals and their interaction with documents, or on the identification of shared patterns of behavior and the segmentation of the user population into groups of common interests. One issue in the personalization and the filtering processes is the selection of an appropriate model for the efficient representation and manipulation of user profiles and documents. It should be capable of facilitating the determination of relevant documents in terms of similarity between users and documents. The aim of this paper is to introduce three models for representing documents and profiles in the search process, and to examine their computational processes. The volume of document databases, the large number of users and their different interests creates the need for precise and efficient filtering techniques. This paper investigates different information retrieval models, which can be used to determine the similarity between documents and user profiles.
    Original languageEnglish
    Title of host publicationProceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE
    PublisherACM
    Pages12
    ISBN (Print)978-1-4503-2899-9
    DOIs
    Publication statusPublished - 2014

    Fingerprint

    Information retrieval

    Bibliographical note

    The full text of this item is not available from the repository.
    © ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE (2014) http://doi.acm.org/10.1145/2597959.2597978.

    Keywords

    • boolean model
    • information retrieval
    • probabilistic model
    • vector space model

    Cite this

    Pannu, M., James, A., & Bird, B. (2014). A comparison of information retrieval models. In Proceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE (pp. 12). ACM. https://doi.org/10.1145/2597959.2597978

    A comparison of information retrieval models. / Pannu, M.; James, Anne; Bird, Bob.

    Proceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE. ACM, 2014. p. 12.

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Pannu, M, James, A & Bird, B 2014, A comparison of information retrieval models. in Proceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE. ACM, pp. 12. https://doi.org/10.1145/2597959.2597978
    Pannu M, James A, Bird B. A comparison of information retrieval models. In Proceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE. ACM. 2014. p. 12 https://doi.org/10.1145/2597959.2597978
    Pannu, M. ; James, Anne ; Bird, Bob. / A comparison of information retrieval models. Proceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE. ACM, 2014. pp. 12
    @inbook{9deb02d4ebb745308bbe1a43946062f2,
    title = "A comparison of information retrieval models",
    abstract = "The personalization process can either be focused on individuals and their interaction with documents, or on the identification of shared patterns of behavior and the segmentation of the user population into groups of common interests. One issue in the personalization and the filtering processes is the selection of an appropriate model for the efficient representation and manipulation of user profiles and documents. It should be capable of facilitating the determination of relevant documents in terms of similarity between users and documents. The aim of this paper is to introduce three models for representing documents and profiles in the search process, and to examine their computational processes. The volume of document databases, the large number of users and their different interests creates the need for precise and efficient filtering techniques. This paper investigates different information retrieval models, which can be used to determine the similarity between documents and user profiles.",
    keywords = "boolean model, information retrieval, probabilistic model, vector space model",
    author = "M. Pannu and Anne James and Bob Bird",
    note = "The full text of this item is not available from the repository. {\circledC} ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE (2014) http://doi.acm.org/10.1145/2597959.2597978.",
    year = "2014",
    doi = "10.1145/2597959.2597978",
    language = "English",
    isbn = "978-1-4503-2899-9",
    pages = "12",
    booktitle = "Proceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE",
    publisher = "ACM",
    address = "United States",

    }

    TY - CHAP

    T1 - A comparison of information retrieval models

    AU - Pannu, M.

    AU - James, Anne

    AU - Bird, Bob

    N1 - The full text of this item is not available from the repository. © ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE (2014) http://doi.acm.org/10.1145/2597959.2597978.

    PY - 2014

    Y1 - 2014

    N2 - The personalization process can either be focused on individuals and their interaction with documents, or on the identification of shared patterns of behavior and the segmentation of the user population into groups of common interests. One issue in the personalization and the filtering processes is the selection of an appropriate model for the efficient representation and manipulation of user profiles and documents. It should be capable of facilitating the determination of relevant documents in terms of similarity between users and documents. The aim of this paper is to introduce three models for representing documents and profiles in the search process, and to examine their computational processes. The volume of document databases, the large number of users and their different interests creates the need for precise and efficient filtering techniques. This paper investigates different information retrieval models, which can be used to determine the similarity between documents and user profiles.

    AB - The personalization process can either be focused on individuals and their interaction with documents, or on the identification of shared patterns of behavior and the segmentation of the user population into groups of common interests. One issue in the personalization and the filtering processes is the selection of an appropriate model for the efficient representation and manipulation of user profiles and documents. It should be capable of facilitating the determination of relevant documents in terms of similarity between users and documents. The aim of this paper is to introduce three models for representing documents and profiles in the search process, and to examine their computational processes. The volume of document databases, the large number of users and their different interests creates the need for precise and efficient filtering techniques. This paper investigates different information retrieval models, which can be used to determine the similarity between documents and user profiles.

    KW - boolean model

    KW - information retrieval

    KW - probabilistic model

    KW - vector space model

    U2 - 10.1145/2597959.2597978

    DO - 10.1145/2597959.2597978

    M3 - Chapter

    SN - 978-1-4503-2899-9

    SP - 12

    BT - Proceedings of WCCCE 2014: The 19th Western Canadian Conference on Computing Education - In-Cooperation with ACM SIGCSE

    PB - ACM

    ER -