WRS: The Wikipedia Recommender System

نویسندگان

  • Thomas Lefévre
  • Christian Damsgaard Jensen
  • Thomas Rune Korsgaard
چکیده

In 2005, the Wikipedia became the most popular reference website on the Internet and it has continued to grow in size and popularity ever since. With the increasing reliance on the Wikipedia comes issues of the credibility and provenance of content. In order to address these issues, we have developed a Recommender System for the Wikipedia, which allows the users of the Wikipedia to rate articles in order to guide other users about the quality of articles. This rating system provides both an incentive for authors to improve articles and a quantifiable measure of the perceived quality of articles.

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

Expertise classification of recommenders in the Wikipedia Recommender System

Wikipedia is a well known online encyclopedia, which is open to everyone. It is based on a collaborative authoring principle, which gives a great value to the online encyclopedia. Due to this fact the Wikipedia has over three millions articles in English. Nowadays, the speed of increasing amount of articles is getting slower, but still remains stunning. The Wikipedia attracts millions of visito...

متن کامل

Association-Rules-Based Recommender System for Personalization in Adaptive Web-Based Applications

Personalization systems based upon users' surfing behavior analysis imply three phases: data collection, pattern discovery and recommendation. Due to the dimension of log files and high processing time, the first two phases are being achieved offline, in a batch process. In this article, we propose WRS, an architecture for adaptive web applications. Within the framework, usage data is being imp...

متن کامل

An Effective Algorithm in a Recommender System Based on a Combination of Imperialist Competitive and Firey Algorithms

With the rapid expansion of the information on the Internet, recommender systems play an important role in terms of trade and research. Recommender systems try to guess the user's way of thinking, using the in-formation of user's behavior or similar users and their views, to discover and then propose a product which is the most appropriate and closest product of user's interest. In the past dec...

متن کامل

Comparison of growth parameters, cortisol and muscle gene expression of rainbow trout reared in an open and water reuse system

Fish farming in recirculating aquaculture systems (RAS) has been expanding in the recent years, but the effects of water reuse are not well known. The aim of the present study was to compare the growth parameters, stress response and muscle stress- and growth- related gene expression of rainbow trout (Oncorhynchus mykiss) in open system (OS) versus water reuse system (WRS). For this purpose, yo...

متن کامل

A New WordNet Enriched Content-Collaborative Recommender System

The recommender systems are models that are to predict the potential interests of users among a number of items. These systems are widespread and they have many applications in real-world. These systems are generally based on one of two structural types: collaborative filtering and content filtering. There are some systems which are based on both of them. These systems are named hybrid recommen...

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 2009