破裂
发表于 2025-3-28 17:02:23
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注视
发表于 2025-3-28 19:59:59
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灰姑娘
发表于 2025-3-29 00:55:12
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Radiculopathy
发表于 2025-3-29 05:02:13
An Online Inference Algorithm for Labeled Latent Dirichlet Allocationpora and text streams. In this paper, we develop an efficient online algorithm for Labeled LDA, called .(online-LLDA). It is based on particle filter, a Sequential Monte Carlo approximation technique. Our experiments show that online-LLDA significantly outperforms batch algorithm(batch-LLDA) in time, while preserving equivalent quality.
Interim
发表于 2025-3-29 09:01:42
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START
发表于 2025-3-29 14:13:57
An Online Inference Algorithm for Labeled Latent Dirichlet Allocationpora and text streams. In this paper, we develop an efficient online algorithm for Labeled LDA, called .(online-LLDA). It is based on particle filter, a Sequential Monte Carlo approximation technique. Our experiments show that online-LLDA significantly outperforms batch algorithm(batch-LLDA) in time, while preserving equivalent quality.
Euthyroid
发表于 2025-3-29 17:49:53
An Ensemble Matchers Based Rank Aggregation Method for Taxonomy Matchingaxonomy matchers and generating an optimal taxonomy mapping. And we introduce TRA, a Threshold Rank Aggregation algorithm for this problem. Experimental results show that TRA outperforms state-of-the-art approaches regardless of domains and scales of taxonomies, which demonstrates that TRA performs good adaptability to taxonomy matching.
Cognizance
发表于 2025-3-29 21:38:26
Distributed XML Twig Query Processing Using MapReducere no knowledge of query pattern; twig queries can be efficiently processed in a single-round MapReduce job with good scalability. Extensive experiments are conducted to verify the efficiency and scalability of our algorithms.
丰满中国
发表于 2025-3-30 01:02:39
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消毒
发表于 2025-3-30 06:07:37
Sentiment Word Identification with Sentiment Contextual Factorsnstead of seed words, we exploit sentiment matching and sentiment consistency for modeling. Extensive experimental studies on three real-world datasets demonstrate that our models outperform the state-of-the-art approaches.