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Z - Bibliography, Library Science, Information Resources (General) - Concordia University Libraries Recent Acquisitions

Items in Bibliography, Library Science or Information Resources (General) that were added to the Concordia University Libraries collection in the last 30 days.


  • NAFTA and GATT : environmental and economic issues : a bibliography / compiled by Joan Nordquist
    Z 7164 C8N68 1996

  • Africa south of the Sahara : index to periodical literature, 1900-1970 / compiled in the African Section, General Reference and Bibliography Division, Reference Department, Library of Congress
    Z 3503 U47

  • NII Testbeds and Community for Information Access Research 14th International Conference, NTCIR 2019, Tokyo, Japan, June 10-13, 2019, Revised Selected Papers / Makoto P. Kato, Yiqun Liu, Noriko Kando, Charles L. A. Clarke (eds.)
    Z699.A1

  • Big data recommender systems. edited by Osman Khalid, Samee U. Khan and Albert Y. Zomaya
    ZA 3084 B54 2019eb

    First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users' data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges.

    Divided into two volumes, this comprehensive set covers recent advances, challenges, novel solutions, and applications in big data recommender systems. Volume 2 covers a broad range of application paradigms for recommender systems over 22 chapters. Volume 1 contains 14 chapters addressing foundations, algorithms and architectures, approaches for big data, and trust and security measures.


  • Big data recommender systems. edited by Osman Khalid, Samee U. Khan and Albert Y. Zomaya
    ZA 3084 B54 2019eb

    First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users' data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges.

    Divided into two volumes, this comprehensive set covers recent advances, challenges, novel solutions, and applications in big data recommender systems. Volume 1 contains 14 chapters addressing foundations, algorithms and architectures, approaches for big data, and trust and security measures. Volume 2 covers a broad range of application paradigms for recommender systems over 22 chapters.

Updated: Thursday 23 January 2020
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