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Titlebook: Social Media Processing; 5th National Confere Yuming Li,Guoxiong Xiang,Mingwen Wang Conference proceedings 2016 Springer Nature Singapore P

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发表于 2025-3-21 20:04:09 | 显示全部楼层 |阅读模式
书目名称Social Media Processing
副标题5th National Confere
编辑Yuming Li,Guoxiong Xiang,Mingwen Wang
视频video
概述Includes supplementary material:
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Social Media Processing; 5th National Confere Yuming Li,Guoxiong Xiang,Mingwen Wang Conference proceedings 2016 Springer Nature Singapore P
描述This book constitutes the thoroughly refereed proceedings of the 5th National Conference of Social Media Processing, SMP 2016, held in Nanchang, China, in October 2016..The 24 revised full papers presented were carefully reviewed and selected from 109 submissions. The papers address issues such as: mining social media and applications; natural language processing; data mining; information retrieval; emergent social media processing problems.
出版日期Conference proceedings 2016
关键词social networks; prediction; recommendation; Convolutional Neural Network; Community Question Answering;
版次1
doihttps://doi.org/10.1007/978-981-10-2993-6
isbn_softcover978-981-10-2992-9
isbn_ebook978-981-10-2993-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2016
The information of publication is updating

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发表于 2025-3-21 23:42:29 | 显示全部楼层
1865-0929 ssions. The papers address issues such as: mining social media and applications; natural language processing; data mining; information retrieval; emergent social media processing problems.978-981-10-2992-9978-981-10-2993-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
发表于 2025-3-22 02:18:47 | 显示全部楼层
Conference proceedings 2016, in October 2016..The 24 revised full papers presented were carefully reviewed and selected from 109 submissions. The papers address issues such as: mining social media and applications; natural language processing; data mining; information retrieval; emergent social media processing problems.
发表于 2025-3-22 08:08:33 | 显示全部楼层
发表于 2025-3-22 08:45:15 | 显示全部楼层
A Novel Approach for Relation Extraction with Few Labeled Data,can be directly applied to classify mentions of newly defined relation without labeling new training data. Experimental results demonstrate that our approach achieves competitive performance and can be incorporated with existing approaches to boost performance.
发表于 2025-3-22 15:06:47 | 显示全部楼层
Query Intent Detection Based on Clustering of Phrase Embedding,tected as query intents. Experimental results, based on the NTCIR-12 IMine-2 corpus, show that query intent generation model via phrase embedding significantly outperforms the state-of-art clustering algorithms in query intent detection.
发表于 2025-3-22 20:02:51 | 显示全部楼层
Individual Friends Recommendation Based on Random Walk with Restart in Social Networks,erimental results show that the performance of friend recommendation outperforms the existing methods, and the proposed algorithm is effective and efficient in terms of PV Value, UV Value and Conversion Rate.
发表于 2025-3-22 22:16:24 | 显示全部楼层
Extracting Opinion Expression with Neural Attention,model on this task. Visualization of some examples show that our model can make use of correlation of words in the sentences and emphasize the crucial parts for this task to improve the performance compared with the vanilla RNNs.
发表于 2025-3-23 03:51:48 | 显示全部楼层
Topic Model Based Adaptation Data Selection for Domain-Specific Machine Translation, from the general-domain. Experiments on an end-to-end domain-specific MT task show that our method outperforms the state of the art, yielding at least 1.5 BLEU points at different scales of training data.
发表于 2025-3-23 09:37:07 | 显示全部楼层
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