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The emphases of this study are Web log data preprocessing and collaborative filtering. Aiming at user session identification in the process of data preprocessing and analyzing existing algorithms, this paper established a Web log data preprocessing algorithm based on collaborative filtering. Detailed steps of algorithm and an experimental simulation were carried out. The results of the experiment...
In social news services, selecting valuable and credible news content is one of the most important issues. In traditional journalism, a small number of people called editors selected news that they considered worthwhile. Recently, several services have utilized reader voting to find news that is popular or credible but most of them are prone to abuse. In this paper, we present a collaborative news...
With the expansion of digital networks and TV devices and the rapid increase of the number of channels, people are exposed to an information overload, due to the presence of several hundreds of alternative programs to watch. In this context, personalization is achieved with the employment of algorithms and data collection schemes that predict and recommend to television viewers content that match...
Many applications of collaborative filtering (CF), such as news item recommendation and bookmark recommendation, are most naturally thought of as one-class collaborative filtering (OCCF) problems. In these problems, the training data usually consist simply of binary data reflecting a user's action or inaction, such as page visitation in the case of news item recommendation or webpage bookmarking in...
A novel personalized instructing recommendation system (PIRS) is designed for Web-based learning. This system recognizes different patterns of learning style and Web using habits through testing the learning styles of students and mining their Web browsing logs. Firstly, it processes the sparse data by item-based top-N recommendation algorithm in the course of testing the learning styles. Then it...
With the rapid development of the Internet and the worldwide popularity of the Web is growing exponentially. Automation collaborative filtering (CF) is becoming efficient tool to assist users with accurate information. We present multi-agent model based on collaborative filtering system to find similar users' interesting and choose JACK Intelligent Agentstrade to design CF system. Meanwhile, a novel...
The explosive growth of information makes people confused in making a choice among a huge amount of products, like movies, books, etc. To help people clarify what they want easily, in this study, we present an intelligent recommendation approach named RSCF (recommendation by rough-set and collaborative filtering) that integrates collaborative information and content features to predict user preferences...
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