A New Similarity Model Based on Collaborative Filtering for New User Cold Start Recommendation
نویسندگان
چکیده
منابع مشابه
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 کاملa 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...
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Collaborative Filtering (CF) is a technique to generate personalised recommendations for a user from a collection of correlated preferences in the past. In general, the effectiveness of CF greatly depends on the amount of available information about the target user and the target item. The cold-start problem, which describes the difficulty of making recommendations when the users or the items a...
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Cold start is one of the main challenges in recommender systems. Solving sparsechallenge of cold start users is hard. More cold start users and items are new. Sine many general methods for recommender systems has over fittingon cold start users and items, so recommendation to new users and items is important and hard duty. In this work to overcome sparse problem, we present a new method for rec...
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Recommender system data presents unique challenges to the data mining, machine learning, and algorithms communities. The high missing data rate, in combination with the large scale and high dimensionality that is typical of recommender systems data, requires new tools and methods for efficient data analysis. Here, we address the challenge of evaluating similarity between two users in a recommen...
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ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2020
ISSN: 0916-8532,1745-1361
DOI: 10.1587/transinf.2019edp7258