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Extremely Short Chinese Text Classification Method Based on Bidirectional Semantic Extension

Journal of Physics: Conference Series 2020年第1期1437卷

作者： Yongzeng Yue Yuhong Zhang Xuegang Hu Peipei Li Key Laboratory of knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology Hefei 23061 China

Short text classification methods have achieved significant progress and wide application on text data such as Twitter and Weibo. However, the extremely short chinese texts like tax invoice data are different with traditional short texts in lackness of contextual semantic information, feature sparseness and extremely short length. The existing short text classification methods are difficult to achieve a satisfactory performance in these texts. To address these problems, this paper proposes a text classification method based on bidirectional semantic extension for extremely short texts like Chinese tax invoice data. More specifically, firstly, the Chinese knowledge graph is introduced for extending bidirectional semantic of texts and label data to expand the extremely short texts and ease the problem of feature sparseness; secondly, the hash vectorization is used to avoid the semantic problem caused by the lackness of contextual information. Experimental results conducted the real tax invoice dataset demonstrate the effectiveness of our proposed method.

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Automated vision inspection of rail surface cracks: A double-layer data driven framework 48

Automated vision inspection of rail surface cracks: A double...

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48th International Conference on Computers and Industrial engineering, CIE 2018

作者： Zhuang, Li Wang, Long Zhang, Zijun School of Data Science City University of Hong Kong Hong Kong Beijing100083 China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083 China

A double-layer data-driven framework for the automated vision inspection of the rail surface cracks is proposed in this paper. Based on images of rails, the proposed framework is capable to detect the location of cracks firstly and next automatically obtain the boundary of cracks via a feature-based linear iterative crack aggregation (FLICA). Extended Haar-like features are applied to develop significant features for identifying cracks in images. Built on extended Haar-like features, a cascading classifier ensemble integrating three single cascading classifiers with a major voting scheme is proposed to decide the presence of cracks in the image. Each single cascading classifier is composed of a sequence of stage classifiers trained by the LogitBoost algorithm. A scalable sliding window carrying the cascading classifier ensemble is applied to scan images of rail tracks, which is identified by the Otsu’s method, and detect cracks. After completing the crack registration in the first layer, the FLICA is developed to discover boundaries of cracks. The effectiveness of the proposed data-driven framework for identifying rail surface cracks is validated with the rail images provided by the China Railway Corporation and Hong Kong Mass Transit Railway (MRT). Six benchmarking methods, the Otsu’s method, mean shift, the visual detection system, the geometrical approach, fully convolutional networks and the U-net, are utilized to prove advantages of the proposed framework. Results of the validation and comparative analyses demonstrate that the proposed framework is most effective in the rail surface crack detection. © 2018, Curran Associates Inc. All rights reserved.

关键词： Crack detection

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Research and Implementation of Chinese Text Automatic Proofreading System 2

Research and Implementation of Chinese Text Automatic Proofr...

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2018 2nd Annual International Conference on Cloud Technology and Communication engineering, CTCE 2018

作者： Gong, Yonggang Fu, Junying Lian, Xiaoqin Li, Yuying Beijing Key Laboratory of Big Data Technology for Food Safety School of Computer and Information Engineering Beijing Technology and Business University Beijing100048 China

The news media platform has a huge amount of original news releases every day, it is impractical to use manual review of text typos. This paper designed and implemented a Chinese text automatic proofreading system for large-scale text content and high-speed processing. The proofreading content is first analyzed and classified: typos and sensitive information. Firstly, the system used the n-gram model to statistically analyze the corpus after segmentation to form a 2-gram model library and a contextual context library;secondly, builded a typo confusion set, and then calculated the probability of the target word in the knowledge base to realize automatic error detection and correction of Chinese text. The system has been successfully applied to the error of the content of many government news media platforms, each server can handle one million articles every day. The results show that the recall rate of the article is 78.9% and the accuracy rate is 85.1%. It meets the demand of high speed and accurate processing of massive text error, and has important practical significance and application fields. © Published under licence by IOP Publishing Ltd.

关键词： Errors

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CitationAS： A Tool of Automatic Survey Generation Based on Citation Content

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Journal of data and Information Science 2018年第2期3卷 20-37页

作者： jie wang chengzhi zhang mengying zhang sanhong deng School of Information Management Nanjing University Nanjing 210023 China Department of Information Management Nanjing University of Science and Technology Nanjing 210094 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing University Nanjing 210023 China

Purpose： This study aims to build an automatic survey generation tool, named CitationAS, based on citation content as represented by the set of citing sentences in the original ***/methodology/approach： Firstly, we apply LDA to analyse topic distribution of citation content. Secondly, in CitationAS, we use bisecting K-means, Lingo and STC to cluster retrieved citation content. Then Word2Vec, Word Net and combination of them are applied to generate cluster labels. Next, we employ TF-IDF, MMR, as well as considering sentence location information, to extract important sentences, which are used to generate surveys. Finally, we adopt manual evaluation for the generated ***： In experiments, we choose 20 high-frequency phrases as search terms. Results show that Lingo-Word2Vec, STC-Word Net and bisecting K-means-Word2Vec have better clustering effects. In 5 points evaluation system, survey quality scores obtained by designing methods are close to 3, indicating surveys are within acceptable limits. When considering sentence location information, survey quality will be improved. Combination of Lingo, Word2Vec, TF-IDF or MMR can acquire higher survey *** limitations： The manual evaluation method may have a certain subjectivity. We use a simple linear function to combine Word2Vec and Word Net that may not bring out their strengths. The generated surveys may not contain some newly created knowledge of some articles which may concentrate on sentences with no *** implications： CitationAS tool can automatically generate a comprehensive, detailed and accurate survey according to user’s search terms. It can also help researchers learn about research status in a certain ***/value： Citaiton AS tool is of practicability. It merges cluster labels from semantic level to improve clustering results. The tool also considers sentence location information when calculating sentence score by TF-IDF and MMR.

关键词： Automatic survey system Citation content Clustering algorithms Labelgeneration approaches Sentence extraction methods

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The Second-order h-type Indicators for Identifying Top Units

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data and Information Management 2018年第1期2卷 49-56页

作者： Ye, Fred Y. Bornmann, Lutz School of Information Management Nanjing University 210023 Nanjing China Jiangsu Key Laboratory of Data Engineering and Knowledge Service 210023 Nanjing China Administrative Headquarters of the Max Planck Society Division for Science and Innovation Studies Hofgartenstr. 8 D-80539 Munich Germany

The second-order h-type indicators are suggested to identify top units in scientometrics. Basically, the re-ranking of h-type series leads to the second-order h-type indicator. The second-order h-type indicators provide an interesting and natural method to identify top units, yielding fixed h-top. Differentiating from the series of artificially defined highly cited percentile classes, the h-top contributes a natural definite top in the series of highly cited classes. When studying theoretically, the second-order h-index concerns 3% of the h-top whereas the first-order h-index refers to 10% of the h-core. The ratio of the first- and second-order h-index, hT/h, is 30%. When studying empirically, the ratio of the first- and second-order h-index, hT/h, is © 2018 © 2018 Fred Y. Ye, Lutz Bornmann, published by Sciendo

关键词： Indexing (of information)

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Insight into disinfection byproduct formation potential of aged biochar and its effects during chlorination

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Journal of environmental management 2022年 317卷 115437页

作者： Hailan Yang Shujing Ye Han Wang Chengyun Zhou Ting Xiong Yuanyuan Deng Qianmin Fu Guangming Zeng Zhuotong Zeng Xiaofei Tan Department of Dermatology Second Xiangya Hospital Central South University Changsha 410011 PR China College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China. College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China School of Resources Environment and Materials Guangxi University Nanning 530004 PR China. Institute of Big Data and Internet Innovation Hunan University of Technology and Business Changsha 410205 PR China. College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China. Electronic address: zengzhuotong@***. College of Environmental Science and Engineering and Key Laboratory of Environmental Biology and Pollution Control (Ministry of Education) Hunan University Changsha 410082 PR China. Electronic address: tanxf@***.

Biochar can achieve multiple benefits including solid waste management, polluted water remediation, carbon sequestration, and emission reduction. However, various environmental factors (such as temperature variations and dry-wet alternation) and microbial activity may lead to the fragmentation, dissolution, and oxidation of biochar. These accelerate the dissolution of biochar-derived dissolved organic matter (DOM) and then influence disinfection byproducts formation potential (DBPFP) throughout the water treatment process. In this paper, biochars from six biomass feedstocks with five aging processes were prepared, and the DBPFP of biochar and its derived DOM were first studied systematically. Different aging processes might increase the DBPFP of biochar by increasing DOM content and changing the fraction distribution of DOM derived from biochar. Especially, the DBPFP of biochar increased apparently with the chemical aging process. Coexisting with the environmental concentration of humic acid, even aged biochar showed the potential to reduce DBPFP and integrated toxic risk value of the mixed system. In this study, the DBPFP of biochar-derived DOM during the disinfection process is confirmed, and the results can give information to the selection of biomass feedstocks of biochar and its service life in the water treatment process.

关键词： Aged biochar Chlorination Disinfection byproducts Dissolved organic matter Integrated toxic risk value

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A Coarse-to-Fine Multi-stream Hybrid Deraining Network for Single Image Deraining

A Coarse-to-Fine Multi-stream Hybrid Deraining Network for S...

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IEEE International Conference on data Mining (ICDM)

作者： Yanyan Wei Zhao Zhang Haijun Zhang Richang Hong Meng Wang Key Laboratory of Knowledge Engineering with Big Data (Ministry of Education) Hefei University of Technology School of Computer Science and Information Engineering Hefei University of Technology Hefei China Department of Computer Science Harbin Institute of Technology (Shenzhen) Xili University Town Shenzhen China

Single image deraining task is still a very challenging task due to its ill-posed nature in reality. Recently, researchers have tried to fix this issue by training the CNN-based end-to-end models, but they still cannot extract the negative rain streaks from rainy images precisely, which usually leads to an over de-rained or under de-rained result. To handle this issue, this paper proposes a new coarse-to-fine single image deraining framework termed Multi-stream Hybrid Deraining Network (shortly, MH-DerainNet). To obtain the negative rain streaks during training process more accurately, we present a new module named dual path residual dense block, i.e., Residual path and Dense path. The Residual path is used to reuse com-mon features from the previous layers while the Dense path can explore new features. In addition, to concatenate different scaled features, we also apply the idea of multi-stream with shortcuts between cascaded dual path residual dense block based streams. To obtain more distinct derained images, we combine the SSIM loss and perceptual loss to preserve the per-pixel similarity as well as preserving the global structures so that the deraining result is more accurate. Extensive experi-ments on both synthetic and real rainy images demonstrate that our MH-DerainNet can deliver significant improvements over several recent state-of-the-art methods.

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An Integrated Semantic-Syntactic SBLSTM Model for Aspect Specific Opinion Extraction 15th

An Integrated Semantic-Syntactic SBLSTM Model for Aspect Spe...

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15th Web Information Systems and Applications Conference, WISA 2018

作者： Han, Zhongming Jiang, Xin Li, Mengqi Zhang, Mengmei Duan, Dagao School of Computer and Information Engineering Beijing Technology and Business University Beijing100048 China Beijing Key Laboratory of Big Data Technology for Food Safety Beijing China

ISBN: (纸本)9783030029333

Opinion Mining (OM) of Internet reviews is one of the key issues in Natural Language Processing (NLP) field. This paper proposes a stacked Bi-LSTM aspect opinion extraction model in which semantic and syntactic features are both integrated. The model takes embedded vector which is composed by word embedding, POS tags and dependency relations as its input while taking label sequence as its output. The experimental results show the effectiveness of this structural features embedded stacked Bi-LSTM model on cross-domain and cross-language datasets, and indicate that this model outperforms the state-of-the-art methods. © 2018, Springer Nature Switzerland AG.

关键词： Syntactics

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BanFEL: A Blockchain Based Smart Contract for Fair and Efficient Lottery Scheme

BanFEL: A Blockchain Based Smart Contract for Fair and Effic...

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IEEE Conference on Dependable and Secure Computing

作者： Jiasheng Li Zijian Zhang Meng Li Beijing Engineering Research Center of Massive Language Information Beijing Institute of Technology Beijing China School of Computer Science University of Auckland Aukland New Zealand Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Hefei University of Technology Anhui China

Lottery is a game with many people's dreams. But corruptions of lottery centers make the lottery unfair. To address this unfair issue, fair lottery schemes have been studied for several years. In these schemes, delay functions or aggregation protocols can be used to generate the winning numbers fairly. However, to the best of our knowledge, none of the existing schemes can achieve the winning number generated randomly, while the randomness can be verified fairly. In this article, we first propose a [B]lockchain based sm[a]rt co[n]tract for [F]air and [E]fficient [L]ottery (BanFEL) scheme. We further present a winning number random generation smart contract, by which players submit the purchased numbers and the non-tampering property is protected. Security analysis and experiments show that the fairness of BanFEL is protected better than the existing works. Meanwhile, the verification cost of this scheme are at least 0.03s lower than the traditional Grumbach's scheme between 1000 and 10000 players.

关键词： Blockchain Smart contracts Security Mathematical model Privacy Information processing

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Culture versus Policy: More Global Collaboration to Effectively Combat COVID-19

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The Innovation 2020年第2期1卷 15-16页

作者： Jianping Li Kun Guo Enrique Herrera Viedma Heesoek Lee Jiming Liu Ning Zhong Luiz Flavio Autran Monteiro Gomes Florin Gheorghe Filip Shu-Cherng Fang Mujgan SagirÖzdemir Xiaohui Liu Guoqing Lu Yong Shi School of Economics and Management University of Chinese Academy of SciencesBeijing 100190China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of SciencesBeijing 100190China Research Center on Fictitious Economy&Data Science Chinese Academy of SciencesBeijing 100190China Department of Computer Science and Artificial Intelligence E.T.S.de Ingenieria Informatica y de TelecomunicacionesUniversity of Granada18071 GranadaSpain Department of Information Management Korea Advanced Institute of Science and TechnologySeoul 207-43 Korea Department of Computer Science and HKBU-CSD&NIPD Joint Research Laboratory for Intelligent Disease Surveillance and Control Hong Kong Baptist UniversityHong KongChina Department of Life Science and Informatics Maebashi Institute of TechnologyMaebashi 371-0816Japan Ibmec University Center Av.Presidente Wilson118Office#111020030-020 Rio de JaneiroBrazil The Romanian Academy Bucharest010071Romania Industrial and Systems Engineering Department North Carolina State UniversityRaleighNC 27695USA Department of Industrial Engineering Eskisehir Osmangazi University26480 EskisehirTurkey Department of Computer Science Brunel University LondonLondonUB83PHUK Department of Biology and School of Interdisciplinary Informatics University of Nebraska at OmahaOmahaNE 68182USA College of Information Science and Technology University of Nebraska at OmahaOmahaNE 68182USA

The outbreak of COVID-19 seriously challenges every government with regard to capacity and management of public health systems facing the catastrophic *** and anti-epidemic policy do not necessarily conflict with each *** countries and governments should be more tolerant to each other in seeking cultural and political consensus to overcome this historically tragic pandemic together.

关键词： seeking overcome policy

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