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Wikipedia Recommender System



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Wikipedia is a well known online encyclopedia. It is based on a collaborative authoring principle. The Wikipedia attracts millions of visitors and they are allowed to read, edit or create new articles. Being open to everyone, makes Wikipedia the biggest online encyclopedia on the other hand, this statement leads to some negative features on the Wikipedia: erroneous facts and personal opinion propagation. Wikipedia Recommender System (WRS) is a collaborative filtering system that makes it easy to determine the quality of an article and allows users to submit the ratings and categories. Once the article classification was implemented into the WRS, the classification scheme started playing a vital role in determining the user's expertise area. To evaluate people agreement on classification of the Wikipedia articles, the survey is arranged. It investigates four different information classification schemes: Citizendium, Dewey Decimal Classification, Open Directory Project - Dmoz and top-level Wikiportals. The purpose of survey is to determine the scheme which enables people to classify articles the most consistently with the highest agreement level on it.






Wikipedia is a well known online encyclopedia. It is based on a collaborative authoring principle. The Wikipedia attracts millions of visitors and they are allowed to read, edit or create new articles. Being open to everyone, makes Wikipedia the biggest online encyclopedia on the other hand, this statement leads to some negative features on the Wikipedia: erroneous facts and personal opinion propagation. Wikipedia Recommender System (WRS) is a collaborative filtering system that makes it easy to determine the quality of an article and allows users to submit the ratings and categories. Once the article classification was implemented into the WRS, the classification scheme started playing a vital role in determining the user's expertise area. To evaluate people agreement on classification of the Wikipedia articles, the survey is arranged. It investigates four different information classification schemes: Citizendium, Dewey Decimal Classification, Open Directory Project - Dmoz and top-level Wikiportals. The purpose of survey is to determine the scheme which enables people to classify articles the most consistently with the highest agreement level on it.


  recommender systems. The study of the recommendation system is a branch of information filtering systems Recommender system 2020. OAI identifier Provided by MUCC. About Wikipedia Disclaimers Search. Find read and cite all the research you.


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Jump to navigation Jump to search. Feel free to download it . References 1 A. Leo SiuYin in Towards Data Science. His published works include highly influential research on the social web recommendation systems and collaborative systems. Incentivecentered design ICD is the science of designing a system or institution according to the alignment of individual and user incentives with the goals of the system.Using incentivecentered design system designers can observe systematic and predictable tendencies in users in response to motivators to provide or manage incentives to induce a greater amount and more valuable participation. 1 Area of application 2 Technical implementation 3 Ecommerce using machine learning. RecSys International Workshop on Novelty and Diversity in Recommender Systems. I have just modified 2 external links on Recommender system. A recommender system is a subclass of information filtering system that seeks to predict the rating or preference a user would give to an item. Knowledgebased recommender systems knowledge based recommenders are a specific type of recommender . Being a collaborative filtering system WRS is affected by the cold start problem.


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