Titlebook: Information Retrieval; 25th China Conferenc Qi Zhang,Xiangwen Liao,Zhaochun Ren Conference proceedings 2019 Springer Nature Switzerland AG

MAPLE

Document-Level Named Entity Recognition by Incorporating Global and Neighbor Featuresevel module, we use CNN to encode global consistency features and apply BiLSTM to model neighbor relevance features. We further apply a gate to effectively fuse these two non-local features and use a CRF layer to decode labels. We evaluate our model on the CoNLL-2003 dataset. Experimental results show that our model outperforms existing methods.

漂浮

Headstrong

A User Effort Measurement for Query Selectionortant as browsing effort. This paper further introduces an entropy-like effort measurement approach for query selection. Statistic and simulation results strongly indicate that our measurement reflects real user effort better.

lavish

高度

A Method for User Avatar Authenticity Based on Multi-feature Fusiond text-based features. We use deep learning, image recognition and topic model techniques to process features. The method is verified on the Sina Weibo data set. The experimental results show that the method can achieve 84.1% accuracy.

Collar

0302-9743 f the Internet and IT fields, enhance the production efficiency of the industry, and have a major impact on various fields of social life..978-3-030-31623-5978-3-030-31624-2Series ISSN 0302-9743 Series E-ISSN 1611-3349

高度赞扬

Conference proceedings 20192019. ..The 13 full papers presented were carefully reviewed and selected from 45 submissions..Academic research is aimed at the precise acquisition of information and knowledge by human beings. The research results will support national strategic decision-making, promote the development of the Inte

苦涩

ESO

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