New prediction methods for collaborative filtering
نویسندگان
چکیده
منابع مشابه
Clustering Methods for Collaborative Filtering
Grouping people into clusters based on the items they have purchased allows accurate recommendations of new items for purchase: if you and I have liked many of the same movies, then I will probably enjoy other movies that you like. Recommending items based on similarity of interest (a.k.a. collaborative ltering) is attractive for many domains: books, CDs, movies, etc., but does not always work ...
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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...
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Using only implicit data, many recommender systems fail in general to provide a precise set of recommendations to users with limited interaction history. This issue is regarded as the “Cold Start” problem and is typically resolved by switching to content-based approaches where extra costly information is required. In this paper, we use a dimensionality reduction algorithm, Word2Vec (W2V), origi...
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Web page prediction is a popular personalized service on the Web and has attracted much research attention. One of the most successful and widely used approaches is collaborative filtering. Traditional collaborative filtering requires explicit user participation for providing his/her interest to the pages. However, they suffer from some limitations such as additional user effort, user behavior ...
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Learning sentiment models from short texts such as tweets is a notoriously challenging problem due to very strong noise and data sparsity. This paper presents a novel, collaborative filtering-based approach for sentiment prediction in twitter conversation threads. Given a set of sentiment holders and sentiment targets, we assume we know the true sentiments for a small fraction of holder-target ...
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ژورنال
عنوان ژورنال: Pamukkale University Journal of Engineering Sciences
سال: 2016
ISSN: 1300-7009,2147-5881
DOI: 10.5505/pajes.2016.44227