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共 1879 条记录，以下是91-100 订阅

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Smart Grid Data Mining and Visualization 4

Smart Grid Data Mining and Visualization

引用

4th ieee international conference on progress in informatics and computing (ieee PIC)

作者： Zhou, Yingyao Li, Ping Xiao, Yuning Masood, Anum Yu, Qichen Sheng, Bin China Southern Power Grid Informat Dept Guangzhou Peoples R China Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai Peoples R China Chinese Acad Sci State Key Lab Comp Sci Inst Software Beijing Peoples R China Educ Univ Hong Kong Dept Math & Informat Technol Hong Kong Peoples R China COMSATS Inst Informat Technol Dept Comp Sci Wah Cantt Pakistan Shanghai Jiao Tong Univ Dept Elect Engn & Automat Shanghai Peoples R China

ISBN: (纸本)9781509034840

The power industry innovation has increasingly become a top concern for current reforms. Power systems feature scattered data storage, incapable data analysis ability, poor computing capability, and ineffective interaction interface. To resolve these issues, we need multiple data mining techniques to extract information for analytical capacity improvement. Secondly, we need visualization techniques to analyze and optimize interaction. Lastly, we need distributed technologies for unified data management to increase computing capability and system scalability. Considering China's smart grid information, this paper proposes solutions to problems, such as the existing underdeveloped power management systems, a lack of automation methods, low data visualization, and poor data management. The electric power industry has functional requirements for this research. Based on existing data mining, visualization and understanding of distributed technologies, we discussed the functions of each part of the implementation in a smart grid management system: the data mining module, visualization module and data management module.

关键词： smart grid data mining visualization geographic information systems distributed computing

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Lexicon-Based Semi-CRF for Chinese Clinical Text Word Segmentation 5

Lexicon-Based Semi-CRF for Chinese Clinical Text Word Segmen...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Guoqing Xia Yao Shen Qiang Lin Department of Computer Science Shanghai Jiao Tong University

ISBN: (纸本)9781538619797;9781538619780

Word segmentation is in most cases a base for text analysis and absolutely vital to the accuracy of subsequent natural language processing(NLP) tasks. While word segmentation for normal text has been intensively studied and quite a few algorithms have been proposed, these algorithms however do not work well in special fields, e.g., in clinical text analysis. Besides, most state-of-the-art methods have difficulties in identifying out-of-vocabulary(OOV) words. For these two reasons, in this paper, we propose a semi-supervised CRF(semiCRF) algorithm for Chinese clinical text word ***-CRF is implemented by modifying the learning objective so as to adapt for partial labeled data. Training data are obtained by applying a bidirectional lexicon matching scheme. A modified Viterbi algorithm using lexicon matching scheme is also proposed for word segmentation on raw sentences. Experiments show that our model has a precision of 93.88% on test data and outperforms two popular open source Chinese word segmentation tools i.e.,Han LP and THULAC. By using lexicon, our model is able to be adapted for other domain text word segmentation.

关键词： Chinese word segmentation Chinese clinical text semi-CRF bidirectional lexicon matching

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Multiple Objects Tracking Based on Multiple Information Integration 5

Multiple Objects Tracking Based on Multiple Information Inte...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Kejia Pu Zhichao Lian Zhongeng Liu School of Computer Science and Engineering Key Laboratory of Spectral Imaging and Intelligent Sense Nanjing University of Science and Technology

ISBN: (纸本)9781538619797;9781538619780

Multi-target tracking algorithm often fail when targets are covered, or move fast, and it cannot be recovered from the failure. To solve this problem, firstly we use multiple information which integrate the target motion information and shape information. Based on the Fisher Criteria, we make the distance between same targets as close as possible which the distance between different targets far away. Secondly, the single target tracker based on strong discriminative ability and the Kalman predictor can track accurately when the target is covered or moves fast. The experimental results show that our multi-target tracking algorithm can track target in occlusion or in fast moving accurately in real time.

关键词： patter recognition correlation filter deep neural network information integration

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An Intelligent Old-age Home Endowment Monitoring System Based on Internet of Things 5

An Intelligent Old-age Home Endowment Monitoring System Base...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Xiao-xuan Ma Xiu-xia Zhang Li-Xin Guo Zhen-wei Ding li-long zhang Shu-yi Wei Rong Fan Yuan-ze Ma College of Computer Science and Engineering North Minzu University School of Electronics and Information Engineering North Minzu University School of Instrument Science and Opto-electronics Engineering HeFei University of Technology School of Mechanical Engineering Xi'an Jiaotong University

ISBN: (纸本)9781538619797;9781538619780

The intelligent home old-age service was an important way to solve the problem of current worsening old-age care reality in *** intelligent old-age home endowment monitoring system based on internet of things was proposed in this *** system has higher practical value,old-age health condition could be real-time monitored,the alerts could be sent when the unforeseen situation happened to the old man.

关键词： IOT Old-age ZigBee

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A Discourse Coherence Model for Analyzing Chinese Students' Essay 5

A Discourse Coherence Model for Analyzing Chinese Students' ...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Guimin Huang Min Tan Sirui Huang Ruyu Mo Ya Zhou Guilin University of Electronic Technology Xi'an Jiaotong-Liverpool University

ISBN: (纸本)9781538619797;9781538619780

Many attempts on improving entity grid model have been made and boost the research on text ***,only a few of them applied it to noisy data domain and students' ***,we proposed a novel discourse coherence model,which is based on entity grid model,to evaluate coherence on Chinese students' *** allusion to the feature of Chinese students' essay,frequently using lexical repetition and coreference methods in coherence essay,we designed a coreference module,instead of clustering algorithm or knowledge base search methods,to integrate with the enhanced coherence *** addition,we fully merged coreference feature into similarity assessment of adjacent sentences,and the semantic *** show that our model outperforms entity-based model and LSA methods and has an ideal effect on students' essay automatic assessment.

关键词： Chinese Students' Essay Discourse Coherence Model Coreference Module Entity Chain Grid

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A new surrogate for tensor multirank and applications in image and video completion 5

A new surrogate for tensor multirank and applications in ima...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Teng-Yu Ji Ting-Zhu Huang Xi-Le Zhao Dong-Lin Sun School of Mathematical Sciences University of Electronic Science and Technology of China

ISBN: (纸本)9781538619797;9781538619780

How to define and relax the tensor rank is a challenging and meaningful topic. The CP-rank, n-rank, and tensor multirank are three of the most popular *** them n-rank and tensor multirank are widely studied in the low-rank tensor completion problem, and their relaxations are sum of nuclear norm(SNN) and tensor nuclear norm(TNN),respectively. Both the two kinds of nuclear norm treat the singular values equally, while the different singular values for the practical images represent different physical meanings and should be treated differently. In this paper, we propose a tensor log Det function as the relaxation for tensor multirank rather than TNN. To demonstrate the effectiveness of the proposed function, we introduce the function into the low-rank tensor completion problem and develop an alternating direction method of multipliers(ADMM)-based method. Extensive experiments have shown that the proposed method outperforms the SNN and TNN based methods.

关键词： Tensor completion tensor multirank tensor singular value decomposition alternating direction method of multipliers

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Deep and Shallow Features Learning for Short Texts Matching 5

Deep and Shallow Features Learning for Short Texts Matching

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Ziliang Wang Si Li Guang Chen Zhiqing Lin School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781538619797;9781538619780

Short texts matching problem is a special issue in natural language matching. Different from common natural language, short texts have their own characteristices, such as casual expressions and limited lengths, especially in the sentences from social media. Previous works usually use rule-based model and retrieval-based model to match short texts. These models merely focus on word-level similarity between short texts and can not capture deep matching relation of them. To boost the performance of short texts matching, we investigate a basic convolutional neural network model to learn the sentence-level deep matching relation between short texts. Subsequently, we propose a hybrid model to merge sentence-level deep matching relation with shallow features to generate the final matching score. We evaluate our model on a dataset of short-text conversation based on real-world instances from Sina Weibo. The experimental results show that our model outperforms the previous state-of-art work on this task.

关键词： Short Texts Convolutional Neural Network Logistic Regression Sentence-Level Representation Sentence Matching

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Fast Non-blind Deconvolution Method for Blurred Image Corrupted by Poisson Noise 5

Fast Non-blind Deconvolution Method for Blurred Image Corrup...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Shuyin Tao Wende Dong Zhenmin Tang Qiong Wang School of Computer Science and Engineering Nanjing University of Science and Technology Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Collaborative Innovation Center of Social Safety Science and Technology Nanjing University of Science and Technology The 28th Research Institute of China Electronic Technology Group Corporation

ISBN: (纸本)9781538619797;9781538619780

We formulate the deconvolution problem by combining the negative logarithmic Poisson likelihood with the total variation(TV) regularization, and present a fast algorithm which is based on the method of Lagrange multiplier to solve it. In the proposed algorithm, the original problem is converted into two sub-problems. One is a simple convex optimization problem which has a closed-form solution. While the other is a conventional deconvolution problem based on the Gaussian noise model, which can be solved efficiently with the variable splitting and penalty technology. The minimizer is reached by alternately solving the two problems for only a few iterations. Experimental results show that the algorithm runs very fast and can achieve restored image of high accuracy.

关键词： non-blind deconvolution Poisson noise total variation regularization variable splitting penalty technology

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Blind Image Deconvolution Using the Gaussian Scale Mixture Fields of Experts Prior 5

Blind Image Deconvolution Using the Gaussian Scale Mixture F...

引用

2017 international conference on progress in informatics and computing(PIC)

ISBN: (纸本)9781538619797;9781538619780

In this paper, a blind image deconvolution method which is derived from Bayesian probabilistic framework is proposed. A robust prior named Gaussian Scale Mixture Fields of Experts（GSM FoE） and a prior that is constructed with the l-norm（ p≈1.5） are adopted to regularize the latent image and the point spread function（PSF） respectively. We use a two phase optimization approach to solve the resulted maximum a-posteriori（MAP） estimation problem, and a simple gradient selecting method is incorporated into the alternating minimization to improve the accuracy of the estimated PSF. Experiments on both synthetic and real world blurred images show that our method can achieve results with high quality.

关键词： blind image deconvolution GSM FoE lp-norm regularization MAP

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Hot Topic Detection Based on Combined Content and Time Similarity 5

Hot Topic Detection Based on Combined Content and Time Simil...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Yi Zhao Kun Zhang Hong Zhang Xia Yan Ying Cai School of Computer Science &Engineering Nanjing University of Science &Technology

ISBN: (纸本)9781538619797;9781538619780

Hot topic detection has always been a hot research field, and there are a large number of the applications of this technology in real life. Most of the previous work, however, focused only on the textual information of the news itself, while ignoring the other attributes of the news, such as the time the news was published, which can also tell the topic described in its perspective. And others use only one certain method to calculate the text similarity, which all have their disadvantages. To solve these problems, we proposed our own topic detection algorithm, which takes into account the information difference between the title and the text, combines several methods to calculate text similarity, and combines text and time similarity together. We tested the combined similarity calculation methods, and tested the effect of several time similarity equations. Then we took three different models to calculate the combined similarity which are linear model, quadratic polynomial model and neural network model. Finally, we give out the results and analysis of our experiments.

关键词： Topic detection Combined similarity calculation Multi-attribute similarity calculation Machine learning models

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