Titlebook: Social Media Processing; 6th National Confere Xueqi Cheng,Weiying Ma,Xing Xie Conference proceedings 2017 Springer Nature Singapore Pte Ltd

linguistics

过于平凡

Supervised Hashing for Multi-labeled Data with Order-Preserving Featureough deep convolutional neural network. Secondly, the order-preserving features would be used for learning hash codes. Extensive experiments on two real-world public datasets show that the proposed method outperforms state-of-the-art baselines in the image retrieval tasks.

DEI

晚间

Exploring Effective Methods for On-line Societal Risk Classification and Feature Mininghat CRFs model has superior performance with capturing the contextual constraints on HNSW. Besides, state features can be extracted based on CRFs model to study distributions of terms in each risk category. The distribution rules of geographical terms are found and summarized.

极深

A Markov Chain Monte Carlo Approach for Source Detection in Networksrved graph rather than the entire one. Extensive experiments on public data sets show that our MCMC algorithm significantly outperforms several state-of-the-art baselines, which validates the potential of our algorithm in source detection task.

aquatic

不规则

Mere仅仅

FEAS

Social Annotation for Query Expansion Learning from Multiple Expansion Strategiesies. Furthermore, we also introduce learning to rank methods for phrase weighting, and select the features from social annotation resource for training ranking model. Experimental results on three TREC test collections show that the retrieval performance can be improved by our proposed method.

AGONY