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Filtering by: Creator Herlocker, Jon Remove constraint Creator: Herlocker, Jon Subject Recommender systems (Information filtering) Remove constraint Subject: Recommender systems (Information filtering)

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  • Contributions to a Java recommender system

    Creator:
    Wang, Yun
    Abstract:
    Identifying the most relevant items in an e-commerce site is becoming more and more difficult nowadays because of the heavy overload of information. A Java Recommender System that uses Collaborative Filtering techniques has been developed to reduce such information overload and even personalize the information to the individual’s preference. The...
    Resource Type:
    Capstone Project
    Full Text:
    Major Professor: Jon Herlocker Committee Member: Tim Budd

  • A collaborative filtering algorithm and evaluation metric that accurately model the user experience

    Creator:
    McLaughlin, Matthew
    Abstract:
    "Collaborative filtering algorithms’ performances have been evaluated using a variety of metrics. These metrics, such as Mean Absolute Error and Precision, have often ignored recommendations for which they do not have data. Ignoring these recommendations has provided numbers which do not accurately represent the user experience. Qualitatively we have seen...
    Resource Type:
    Capstone Project
    Full Text:
    i ACKNOWLEDGMENTS I would like thank Dr. Jon

  • Contributions to Collaborative Filtering Research

    Creator:
    Nong, Shuzhen
    Abstract:
    In this report, I first introduce three areas of interest to collaborative filtering researchers, namely: (a) how to solve the sparsity and scalability problems in recommendation systems; (b) how to rapidly develop and test collaborative filtering algorithms; and (c) how to apply collaborative filtering to unbounded numeric preference data. In...
    Resource Type:
    Capstone Project
    Full Text:
    Collaborative Filtering Research Shuzhen Nong Major Professor: Jon Herlocker Committee

  • Collaborative filtering for digital libraries

    Creator:
    Oregon State University. Dept. of Computer Science, Herlocker, Jonathan Lee, Jung, Seikyung, and Webster, Janet G.
    Abstract:
    Can collaborative filtering be successfully applied to digital libraries in a manner that improves the effectiveness of the library? Collaborative filtering systems remove the limitation of traditional content-based search interfaces by using individuals to evaluate and recommend information. We introduce an approach where a digital library user specifies their need...
    Resource Type:
    Research Paper
    Full Text:
    Digital Libraries Jon Herlocker*, Seikyung Jung†, Janet Webster§ *Department of Computer Science

  • Identifying and minimizing the effects of malicious behavior in SERF

    Creator:
    Oregon State University. Dept. of Computer Science and Natarajan, Sandeep
    Abstract:
    Collaborative filtering (CF) algorithms are used in a wide range of internet applications. However the chief objective of using CF algorithms across most of these applications is to discover items that might be of interest to its users. CF algorithms work by obtaining feedback from users on the items that...
    Resource Type:
    Research Paper
    Full Text:
    Engineering and Computer Science Oregon State University. Major Professor: Dr. Jonathan L. Herlocker