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  • Collaborative filtering with probability and collaborative filtering with privacy

    Creator:
    Yang, Min
    Abstract:
    "Collaborative filtering has seen considerable success in the areas regarding information overload and e-commerce, while the current developed systems are flawed in several respects. Two approaches, the distribution-based algorithm and the blurring profile solution, are proposed to address several outstanding issues. The main findings of this research include: • The...
    Resource Type:
    Capstone Project
    Full Text:
    and collaborative filtering, are proposed. The content-based filtering system locates the

  • 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:
    data to a CF system called SERF (System for Electronic Recommendation Filtering). We explore how bad

  • 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:
    organization of the rest of this report. 1.1 Overview of collaborative filtering As the information on

  • 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:
    collaborative filtering system stores the preferences and opinions of the thousands of users of the system

  • 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:
    the system. We discuss the challenges of designing a collaborative filtering system for digital

  • 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:
    Recommender System that uses Collaborative Filtering techniques has been developed to reduce such

  • Evaluation of collaborative filtering and content based filtering recommenders in jTutors (an online intelligent tutoring system)

    Creator:
    Appasamy, Bharatwaj
    Abstract:
    Software engineers often need help with discovering and learning how to use APIs. For example, software engineers who are starting to learn Java, and they want to implement a certain feature in a program, they might want to reuse existing APIs in order to save time versus rewriting it themselves...
    Resource Type:
    Masters Thesis
    Full Text:
    collaborative filtering recommender in the context of the intelligent tutoring system jTutors. It is not