缝纫
发表于 2025-3-28 18:33:31
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赏心悦目
发表于 2025-3-28 20:13:35
A Soft Subspace Clustering Method for Text Data Using a Probability Based Feature Weighting Scheme,d different clusters in subspaces using a weighted distance measure. The weighting scheme heavily affects the clustering performance and requires special consideration. Since text data has semantic information along with syntactic information, a weighting scheme, which uses semantic information, is
analogous
发表于 2025-3-28 23:11:18
A Web-Based Application for Semantic-Driven Food Recommendation with Reference Prescriptions,systems, since it often has educational purposes, to improve behavioural habits of users. In this paper, we discuss the application of Semantic Web technologies in a menu generation system, that uses a recipe dataset and annotations to recommend menus according to user’s preferences. Reference presc
ironic
发表于 2025-3-29 06:09:39
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anesthesia
发表于 2025-3-29 08:13:45
Incorporating Cohesiveness into Keyword Search on Linked Data,query language and the structure of the data. However, the imprecision of keyword queries results in overwhelming numbers of candidate results making the identification of relevant results challenging and hindering the scalability of the query evaluation algorithms..To address these issues, we intro
dilute
发表于 2025-3-29 12:33:33
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Outwit
发表于 2025-3-29 16:11:13
Privacy-Enhancing Range Query Processing over Encrypted Cloud Databases,ate information and the cloud servers may not be fully trusted, it is desirable to encrypt the data before outsourcing and as a result, the functionality and efficiency has to be sacrificed. In this paper, we propose a privacy-enhancing range query processing scheme by utilizing polynomials and kNN
Foolproof
发表于 2025-3-29 21:50:40
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四溢
发表于 2025-3-30 03:55:33
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整顿
发表于 2025-3-30 08:02:54
Cross-Domain Collaborative Recommendation by Transfer Learning of Heterogeneous Feedbacks, by mining useful knowledge from massive data. The big data is often multi-source and heterogeneous, which challenges the recommendation seriously. Collaborative filtering is the widely used recommendation method, but the data sparseness is its major bottleneck. Transfer learning can overcome this p