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

監(jiān)管

書目名稱Social Media Processing影響因子(影響力)




書目名稱Social Media Processing影響因子(影響力)學(xué)科排名




書目名稱Social Media Processing網(wǎng)絡(luò)公開度




書目名稱Social Media Processing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Social Media Processing被引頻次




書目名稱Social Media Processing被引頻次學(xué)科排名




書目名稱Social Media Processing年度引用




書目名稱Social Media Processing年度引用學(xué)科排名




書目名稱Social Media Processing讀者反饋




書目名稱Social Media Processing讀者反饋學(xué)科排名

難管

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

ELUC

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.

逃避現(xiàn)實(shí)

對手

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.

耕種

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.

growth-factor

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.

synchronous

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.

贊美者

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.

Juvenile