Deep Pairwise Hashing for Cold-start Recommendation
نویسندگان
چکیده
منابع مشابه
Representation Learning for cold-start recommendation
A standard approach to Collaborative Filtering (CF), i.e. prediction of user ratings on items, relies on Matrix Factorization techniques. Representations for both users and items are computed from the observed ratings and used for prediction. Unfortunatly, these transductive approaches cannot handle the case of new users arriving in the system, with no known rating, a problem known as user cold...
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Recommender systems are popular in e-commerce as they suggest items of interest to users. Researchers have addressed the coldstart problem where either the user or the item is new. However, the situation with both new user and new item has seldom been considered. In this paper, we propose a cold-start recommendation approach to this situation based on granular association rules. Specifically, w...
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Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users. It plays a critical role in a wide range of online shopping, e-commercial services and social networking applications. Collaborative filtering (CF) is the most popular approaches used for recommender systems, bu...
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With benefits of low storage cost and fast query speed, crossmodal hashing has received considerable attention recently. However, almost all existing methods on cross-modal hashing cannot obtain powerful hash codes due to directly utilizing hand-crafted features or ignoring heterogeneous correlations across different modalities, which will greatly degrade the retrieval performance. In this pape...
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Recommender systems are popular information filtering systems used in various domains. Cold-start problem is a key challenge in a recommender system. In newitem/existing-user case of the cold-start problem, which is recommendation of a recentlyarrived item to a user with historical data, finding links between existing items with recently-arrived items is critical. Using VideoLectures.net Cold-S...
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ژورنال
عنوان ژورنال: IEEE Transactions on Knowledge and Data Engineering
سال: 2020
ISSN: 1041-4347,1558-2191,2326-3865
DOI: 10.1109/tkde.2020.3024022