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Cloud detection from visual band of satellite image based on variance of fractal dimension

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Journal of Systems engineering and Electronics 2019年第3期30卷 485-491页

作者： TIAN Pingfang GUANG Qiang LIU Xing School of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-Time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-Media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

Cover ratio of cloud is a very important factor which affects the quality of a satellite image, therefore cloud detection from satellite images is a necessary step in assessing the image quality. The study on cloud detection from the visual band of a satellite image is developed. Firstly, we consider the differences between the cloud and ground including high grey level, good continuity of grey level, area of cloud region, and the variance of local fractal dimension (VLFD) of the cloud region. A single cloud region detection method is proposed. Secondly, by introducing a reference satellite image and by comparing the variance in the dimensions corresponding to the reference and the tested images, a method that detects multiple cloud regions and determines whether or not the cloud exists in an image is described. By using several Ikonos images, the performance of the proposed method is demonstrated.

关键词： cloud detection visual image satellite image variance of local fractal dimension (VLFD)

Weighted partial order oriented three-way decisions under score-based common voting rules

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International Journal of Approximate Reasoning 2020年 123卷 41-54页

作者： Li, Lei Wu, Xindong Chen, Huanhuan Zhou, Chuan Liu, Guanfeng Jiang, Yongkang Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education Hefei 230601 China Mininglamp Academy of Sciences Mininglamp Technologies Beijing 100084 China School of Computer Science and Technology University of Science and Technology of China Hefei 230026 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China Computing Dept Macquarie University Sydney A1C 5S7 Australia

Recently, with the trisecting and acting models of human cognitive behaviors, three-way decisions are introduced to deal with uncertain decisions in many applications. To define and conduct the three-way decisions on the possible or necessary loser or co-loser and/or winner or co-winner, we first define the score-based common voting rules, where a score-based function is introduced to evaluate certain utility, including positional scoring rules, maximin, Bucklin, and so on. Then on one hand, it has been proved that under certain conditions three-way decisions on the possible loser or co-loser and/or winner or co-winner are NP-complete with positional scoring rules, maximin, and Bucklin, respectively. On the other hand, we have presented algorithms whose time complexity is polynomial to conduct three-way decisions on the necessary winner or co-winner and/or necessary loser or co-loser with positional scoring rules, maximin, and Bucklin in time O(nm²), O(nm³), and O(nm²), respectively, which has been validated experimentally. © 2020 Elsevier Inc.

关键词： Common voting rules Three-way decisions Weighted partial orders

Trustworthy preference completion in social choice

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arXiv 2020年

作者： Li, Lei Xue, Minghe H., Chen X., Wu The School of Computer Science and Technology University of Science and Technology of China China Mininglamp Academy of Sciences Mininglamp Technologies Beijing China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology School of Computer Science and Information Engineering Hefei University of Technology Hefei China

As from time to time it is impractical to ask agents to provide linear orders over all alternatives, for these partial rankings it is necessary to conduct preference completion. Specifically, the personalized preference of each agent over all the alternatives can be estimated with partial rankings from neighboring agents over subsets of alternatives. However, since the agents’ rankings are nondeterministic, where they may provide rankings with noise, it is necessary and important to conduct the trustworthy preference completion. Hence, in this paper firstly, a trust-based anchor-kNN algorithm is proposed to find k-nearest trustworthy neighbors of the agent with trust-oriented Kendall-Tau distances, which will handle the cases when an agent exhibits irrational behaviors or provides only noisy rankings. Then, for alternative pairs, a bijection can be built from the ranking space to the preference space, and its certainty and conflict can be evaluated based on a well-built statistical measurement Probability-Certainty Density Function. Therefore, a certain common voting rule for the first k trustworthy neighboring agents based on certainty and conflict can be taken to conduct the trustworthy preference completion. The properties of the proposed certainty and conflict have been studied empirically, and the proposed approach has been experimentally validated compared to state-of-arts approaches with several data sets. © 2020, CC BY.

关键词： Nearest neighbor search

XTQA: Span-Level Explanations for Textbook Question Answering

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arXiv 2020年

作者： Ma, Jie Chai, Qi Liu, Jun Yin, Qingyu Wang, Pinghui Zheng, Qinghua Ministry of Education of Key Lab for Intelligent Networks and Network Security School of Cyber Science and Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering The School of Computer Science and Technology Xi’an Jiaotong University Shaanxi Xi’an710049 China Amazon United States

Textbook Question Answering (TQA) is the task of correctly answering diagram or non-diagram questions given large multi-modal contexts consisting of abundant essays and diagrams. In real-world scenarios, an explainable TQA system plays a key role in deepening humans’ understanding of learned knowledge. However, there is no work to investigate how to provide explanations currently. To address this issue, we devise a novel architecture towards span-level eXplanations for TQA (XTQA). In this paper, spans are the combinations of sentences within a paragraph. The key idea is to consider the entire textual context of a lesson as candidate evidence, and then use our proposed coarse-to-fine grained Explanation Extracting (EE) algorithm to narrow down the evidence scope and extract the span-level explanations with varying lengths for answering different questions. The EE algorithm can also be integrated into other TQA methods to make them explainable and improve the TQA performance. Experimental results show that XTQA obtains the best overall explanation result (mIoU) of 52.38% on the first 300 questions of CK12-QA test splits, demonstrating the explainability of our method (non-diagram: 150 and diagram: 150). The results also show that XTQA achieves the best TQA performance of 36.46% and 36.95% on the aforementioned splits respectively. We have released our code in https://***/dr-majie/*** Codes 68T07 Copyright © 2020, The Authors. All rights reserved.

关键词： Textbooks

Records systems and information systems: Connecting in organizations 8th

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Records systems and information systems: Connecting in organ...

8th International Joint Conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2016

作者： Xie, Sherry L. Fan, Guanyan Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education of China Beijing100872 China Center for Electronic Records Management Research Beijing100872 China School of Information Resource Management Renmin University of China 59 Zhongguancun Ave Haidian District Beijing100872 China

ISBN: (纸本)9783319997001

The field of Information Systems (ISs) has long been recognized, so has Enterprise Information Systems (EISs), a field close to it. Long existing also in organizations or enterprises is the field of records management, now predominantly digital records management (DRM), which shares the many goals of ISs and EISs in supporting the operation and success of organizations. While the DRM field recognized rather early in its battle to digital records challenges that the need to establish formal collaborations with the ISs and EISs professions, it is still rare to spot today discussions regarding such collaborations in the general information and communication technology (ICT) literature. To help bridge the gap, this chapter introduces to the ISs and EISs professions one of the major developments of the international DRM field, that is, the records systems elaborated by the InterPARES (International Research on Permanent and Authentic Records in Electronic Systems) project, for the purpose of invoking further discussions. © Springer Nature Switzerland AG 2019.

关键词： Information systems

Does ad-context matter on the effectiveness of online advertising? 30

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Does ad-context matter on the effectiveness of online advert...

30th International Conference on Software engineering and knowledge engineering, SEKE 2018

作者： Sun, Caihong Zhang, Meina Zuo, Meiyun Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing China

ISBN: (纸本)1891706446

In this paper, we focus on examining the effects of Ad-context on the click-Through rate (CTR) for the online advertising. Many researches have shown that ad-context congruity is a key factor to CTR, but the features of ad-context are rarely introduced in CTR prediction algorithms. By leveraging data from various sources, and using text mining and sentiment analysis techniques, our proposed approach extracts three types of features (i.e. users, advertisements and ad-context features) to predict CTR. User features describe "Who" is browsing the webpage, advertisement features depict "How" an ad serving is, and ad-context features include "What" the product is, "Where" an ad displays, as well as the "Mood" of the context. Experiment results show that our proposed approach outperforms the benchmark models by introducing ad-context features. Novel ad-context features we proposed make good contributions to the prediction of CTR. The research highlights the power of ad-context in online advertising CTR prediction. Moreover it gives an insight into supporting effective advertising and improving users' satisfaction. © 2018 Universitat zu Koln. All rights reserved.

关键词： Sentiment analysis

Retracted: Measurement and analysis of Chinese journal discriminative capacity

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Journal of Informetrics 2021年第1期15卷

作者： Baolong Zhang Hao Wang Sanhong Deng Xinning Su School of Information Management Nanjing University Nanjing 210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing 210023 China

RAKA: Co-training of relationships and attributes for cross-lingual knowledge alignment

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arXiv 2019年

作者： Chen, Bo Zhang, Jing Tang, Xiaobin Chen, Hong Li, Cuiping Key Laboratory of Data Engineering Knowledge Engineering of Ministry of Education Renmin University of China Information School Renmin University of China

Cross-lingual knowledge alignment suffers from the attribute heterogeneity when leveraging the attributes and also suffers from the conflicts when combing the results inferred from attributes and relationships. This paper proposes an interaction-based attribute model to capture the attribute-level interactions for estimating entity similarities, eliminating the negative impact of the dissimilar attributes. A matrix-based strategy is adopted in the model to accelerate the similarity estimation. We further propose a co-training framework together with three merge strategies to combine the alignments inferred by the attribute model and the relationship model. The whole framework can effectively and efficiently infer the aligned entities, relationships, attributes, and values simultaneously. Experimental results on several cross-lingual knowledge datasets show that our model significantly outperforms state-of-the-art comparison methods (improving 2.35-51.57% in terms of Hit Ratio@1). Copyright © 2019, The Authors. All rights reserved.

关键词： Alignment

A deep belief network-based method to identify proteomic risk markers for Alzheimer’s disease

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arXiv 2020年

作者： An, Ning Jin, Liuqi Ding, Huitong Yang, Jiaoyun Yuan, Jing Key Laboratory of Knowledge Engineering Big Data of Ministry of Education Hefei University of Technology Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China Department of Neurology Peking Union Medical College Hospital Chinese Academy of Medical Sciences Beijing China

While a large body of research has formally identified apolipoprotein E (APOE) as a major genetic risk marker for Alzheimer’s disease, accumulating evidence supports the notion that other risk markers may exist. The traditional Alzheimer’s-specific signature analysis methods, however, have not been able to make full use of rich protein expression data, especially the interaction between attributes. This paper develops a novel feature selection method to identify pathogenic factors of Alzheimer’s disease using the proteomic and clinical data. This approach has taken the weights of network nodes as the importance order of signaling protein expression values. After generating and evaluating the candidate subset, the method helps to select an optimal subset of proteins that achieved an accuracy greater than 90%, which is superior to traditional machine learning methods for clinical Alzheimer’s disease diagnosis. Besides identifying a proteomic risk marker and further reinforce the link between metabolic risk factors and Alzheimer’s disease, this paper also suggests that apidonectin-linked pathways are a possible therapeutic drug target. Copyright © 2020, The Authors. All rights reserved.

关键词： Feature extraction