Unison-CF: A Multiple-Component, Adaptive Collaborative Filtering System

نویسندگان

  • Manolis G. Vozalis
  • Konstantinos G. Margaritis
چکیده

In this paper we present the Unison-CF algorithm, which provides an efficient way to combine multiple collaborative filtering approaches, drawing advantages from each one of them. Each collaborative filtering approach is treated as a separate component, allowing the Unison-CF algorithm to be easily extended. We evaluate the Unison-CF algorithm by applying it on three existing filtering approaches: User-based Filtering, Item-based Filtering and Hybrid-CF. Adaptation is utilized and evaluated as part of the filtering approaches combination. Our experiments show that the Unison-CF algorithm generates promising results in improving the accuracy and coverage of the existing filtering algorithms. keywords: collaborative filtering, memory-based filtering, adaptation, personalization, prediction, recommender systems

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Use of Semantic Similarity and Web Usage Mining to Alleviate the Drawbacks of User-Based Collaborative Filtering Recommender Systems

  One of the most famous methods for recommendation is user-based Collaborative Filtering (CF). This system compares active user’s items rating with historical rating records of other users to find similar users and recommending items which seems interesting to these similar users and have not been rated by the active user. As a way of computing recommendations, the ultimate goal of the user-ba...

متن کامل

An Item-Based Collaborative Filtering using Dimensionality Reduction Techniques on Mahout Framework

Collaborative Filtering (CF) is the most widely used prediction technique in Recommendation System (RS). Most of the current CF recommender systems maintains single criteria user rating in user-item matrix. However, recent studies indicate that recommender system depending on multi-criteria can improve prediction and accuracy levels of recommendation by considering the user preferences in multi...

متن کامل

Collaborative Filtering Recommender Systems

One of the potent personalization technologies powering the adaptive web is collaborative filtering. Collaborative filtering (CF) is the process of filtering or evaluating items through the opinions of other people. CF technology brings together the opinions of large interconnected communities on the web, supporting filtering of substantial quantities of data. In this chapter we introduce the c...

متن کامل

Predicting Correctness of Problem Solving in ITS with a Temporal Collaborative Filtering Approach

Collaborative filtering (CF) is a technique that utilizes how users are associated with items in a target application and predicts the utility of items for a particular user. Temporal collaborative filtering (temporal CF) is a timesensitive CF approach that considers the change in user-item interactions over time. Despite its capability to deal with dynamic educational applications with rapidly...

متن کامل

Speech Enhancement by Modified Convex Combination of Fractional Adaptive Filtering

This paper presents new adaptive filtering techniques used in speech enhancement system. Adaptive filtering schemes are subjected to different trade-offs regarding their steady-state misadjustment, speed of convergence, and tracking performance. Fractional Least-Mean-Square (FLMS) is a new adaptive algorithm which has better performance than the conventional LMS algorithm. Normalization of LMS ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004