Recommending HTML-documents using Features Guided Automated Collaborative Filtering

نویسنده

  • Gabriela Kosková
چکیده

We proposed the system that utilizes Feature Guided Automated Collaborative Filtering for recommending relevant HTML-documents to the users. While browsing the World Wide Web, user expresses his opinions on documents by rating them. The system "learns" user's opinions and searches for like-minded users in order to recommend him unseen relevant documents of interest.

برای دانلود رایگان 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

Recommending HTML-documents using Feature Guided Automated Collaborative Filtering

We proposed the system that utilizes Feature Guided Automated Collaborative Filtering for recommending relevant HTML-documents to the users. While browsing the World Wide Web, user expresses his opinions on documents by rating them. The system "learns" user's opinions and searches for like-minded users in order to recommend him unseen relevant documents of interest.

متن کامل

Feature-Guided Automated Collaborative Filtering

Information ltering systems have traditionally relied on some form of content analysis of documents to represent a proole of user interests. Such content ltering is generally ineeective in domains with diverse media types such as audio, video, and images, because machine-analysis of such media is hard. Recently, information ltering systems relying primarily on human evaluations of documents hav...

متن کامل

QoS-based Web Service Recommendation using Popular-dependent Collaborative Filtering

Since, most of the organizations present their services electronically, the number of functionally-equivalent web services is increasing as well as the number of users that employ those web services. Consequently, plenty of information is generated by the users and the web services that lead to the users be in trouble in finding their appropriate web services. Therefore, it is required to provi...

متن کامل

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

A New Similarity Measure Based on Item Proximity and Closeness for Collaborative Filtering Recommendation

Recommender systems utilize information retrieval and machine learning techniques for filtering information and can predict whether a user would like an unseen item. User similarity measurement plays an important role in collaborative filtering based recommender systems. In order to improve accuracy of traditional user based collaborative filtering techniques under new user cold-start problem a...

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1999