改良
发表于 2025-3-25 06:05:23
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灿烂
发表于 2025-3-25 10:46:35
Unsupervised Ensemble Learning Based on Graph Embedding for Image Clusterings well on the large-scale data, has been proposed for manifold learning. To improve the clustering performance, a novel Unsupervised Ensemble Learning based on Graph Embedding (UEL-GE) is explored, which takes ULGE to get low-dimensional embeddings of the given data and uses the .-means method to ob
irreducible
发表于 2025-3-25 13:53:23
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盖他为秘密
发表于 2025-3-25 16:45:13
Event Causality Identification by Modeling Events and Relation Embeddingion. Traditional approaches of causality relation identification rely on the recognition of casual relationship connectives or manual features of causality relationships, and these methods have disadvantage of low recognition coverage and being lack of adaptive. To solve this problem, we propose a n
lanugo
发表于 2025-3-25 20:34:48
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似少年
发表于 2025-3-26 01:32:49
Hybridized Character-Word Embedding for Korean Traditional Document Translationatical patterns. In recent times, a neural network-based machine translation architecture such as sequence-to-sequence (seq2seq) model showed superior performance in translation. However, it suffers out-of-vocabulary (OOV) issue when dealing with very complex and vocabulary languages such as Chinese
拥护者
发表于 2025-3-26 04:22:07
Word Embedding Based on Low-Rank Doubly Stochastic Matrix Decompositionachine learning tasks. However, in most current word embedding approaches, the similarity in embedding space is not optimized in the learning. In this paper we propose a novel neighbor embedding method which directly learns an embedding simplex where the similarities between the mapped words are opt
个阿姨勾引你
发表于 2025-3-26 09:25:39
Meta-path Based Heterogeneous Graph Embedding for Music Recommendationtion techniques which are based on conventional collaborative filtering or acoustic content features usually sufffer from data sparsity or time-consuming computation problems, respectively. In fact, online music services not only generate listening history for each user but also accumulate a large a
Intruder
发表于 2025-3-26 14:20:15
Knowledge Graph Embedding via Entities’ Type Mapping Matrixowever, KG remains incomplete, inconsistent, and not completely accurate. To deal with the challenges of KGs, many state-of-the-art models, such as TransE, TransH, and TransR, have been proposed. TransE and TransH use one semantic space for entities and relations, whereas TransR uses two different s
分发
发表于 2025-3-26 18:49:11
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