Titlebook: Web Technologies and Applications; 17th Asia-Pacific We Reynold Cheng,Bin Cui,Jia Xu Conference proceedings 2015 Springer International Pub

只看該作者 · 發(fā)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.

只看該作者 · 發(fā)表于 2025-3-29 09:01:42

只看該作者 · 發(fā)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.

只看該作者 · 發(fā)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.

只看該作者 · 發(fā)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.

只看該作者 · 發(fā)表于 2025-3-30 01:02:39

只看該作者 · 發(fā)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.

		自動登錄	找回密碼
密碼			To register

關于派博傳思			派博傳思旗下網站			友情鏈接
派博傳思介紹	公司地理位置	論文服務流程	影響因子官網	吾愛論文網	大講堂	北京大學	Oxford Uni.	Harvard Uni.
發(fā)展歷史沿革	期刊點評	投稿經驗總結	SCIENCEGARD	IMPACTFACTOR	派博系數(shù)	清華大學	Yale Uni.	Stanford Uni.
\|Archiver\|手機版\|小黑屋\| 派博傳思國際 ( 京公網安備110108008328) GMT+8, 2025-10-7 11:06
Copyright © 2001-2015 派博傳思京公網安備110108008328 版權所有 All rights reserved