检索结果-内蒙古大学图书馆

A Chinese Topic Crawler Focused on Customer Development

Procedia CIRP 2016年 56卷 476-480页

作者： Tong Wu Yanchun Liang Chunguo Wu Shifeng Piao Deyin Ma Guozhong Zhao Xiaosong Han College of Computer Science and Technology Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry Jilin University Changchun 130012 China Zhuhai Laboratory of Key Laboratory for Symbol Computation and Knowledge Engineering of Ministry of Education Zhuhai College of Jilin University Zhuhai 519041 China School of Business Jilin University Changchun 130012 China Daqing Oilfield Personnel Development Institute CNPC Daqing 163000 China

This paper presents a Chinese topic crawler focused on customer development, in order to meet the needs of users for more accurate and particular Internet information. The concept of meta-search engine is introduced, and the keywords are expanded by the ontology of HowNet. Through the web crawler, preprocessing and classification, the information on customer relations can be divided into three categories: company, platform and meaningless. Numerical experiments show that satisfactory results can be obtained in some particular information-seeking areas. The average accuracy for classification is more than 80%, which can meet customer needs in most cases.

关键词： Topic crawler Customer development Meta-search engine Semantic similarity

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Entailment-based axiom pinpointing in debugging incoherent terminologies 1

Entailment-based axiom pinpointing in debugging incoherent t...

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1st International Workshop on Semantic Technologies, IWOST 2015

作者： Ye, Yuxin Ouyang, Dantong Su, Jing College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China

One of the major problems of axiom pinpointing for incoherent terminologies is the precise positioning within the conflict axioms. In this paper we present a formal notion for the entailment-based axiom pinpointing of incoherent terminologies, where the parts of an axiom is defined by atomic entailment. Based on these concepts, we prove the one-to-many relationship between existing axiom pinpointing with the entailment-based axiom pinpointing. For its core task, calculating minimal unsatisfiable entailment, we provide algorithms for OWL DL terminologies using incremental strategy and Hitting Set Tree algorithm. The feasibility of our method is shown by case study and experiment evaluations.

关键词： Terminology

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Designment of E-R model based on RDF (S) 2

Designment of E-R model based on RDF (S)

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2nd International Workshop on Semantic Technologies, IWOST 2015

作者： Gao, Xiangbin Ouyang, Dantong Ye, Yuxin College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China

Based on the vast domain resources of RDF (S) on the web and SPARQL's powerful query ability, this article presents a new method of designment of E-R model. The steps for this design are: (1) Formu- lating SPARQL rules (including resource query rules and schema query rules) by the analysis of RDF (S)'s structure. (2) Parsing the optimal resource obtained through the query sentences. (3) Completing the de- signment by taking advantages of the translation from RDF (S) model to entity-relationship model in accordance with the content queried. The re- sults indicate that, the designment of E-R model based on RDF (S) could restore user real requirements of great possibilities and help database de- signer to complete design in a strange area.

关键词： Syntactics

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A Sustainable City Planning Algorithm Based on TLBO and Local Search

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IOP Conference Series: Materials Science and engineering 2017年第1期242卷

作者： Ke Zhang Li Lin Xuanxuan Huang Yiming Liu Yonggang Zhang College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering (Jilin University) Ministry of Education Changchun 130012 China

Nowadays, how to design a city with more sustainable features has become a center problem in the field of social development, meanwhile it has provided a broad stage for the application of artificial intelligence theories and methods. Because the design of sustainable city is essentially a constraint optimization problem, the swarm intelligence algorithm of extensive research has become a natural candidate for solving the problem. TLBO (Teaching-Learning-Based Optimization) algorithm is a new swarm intelligence algorithm. Its inspiration comes from the 'teaching' and 'learning' behavior of teaching class in the life. The evolution of the population is realized by simulating the 'teaching' of the teacher and the student 'learning' from each other, with features of less parameters, efficient, simple thinking, easy to achieve and so on. It has been successfully applied to scheduling, planning, configuration and other fields, which achieved a good effect and has been paid more and more attention by artificial intelligence researchers. Based on the classical TLBO algorithm, we propose a TLBO_LS algorithm combined with local search. We design and implement the random generation algorithm and evaluation model of urban planning problem. The experiments on the small and medium-sized random generation problem showed that our proposed algorithm has obvious advantages over DE algorithm and classical TLBO algorithm in terms of convergence speed and solution quality.

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Topic modeling for large-scale text data

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Frontiers of Information Technology & Electronic engineering 2015年第6期16卷 457-465页

作者： Xi-ming LI College of Computer Science and Technology Jilin University Changchun 130012 China MOE Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun 130012 China

This paper develops a novel online algorithm, namely moving average stochastic variational inference （MASVI）, which applies the results obtained by previous iterations to smooth out noisy natural gradients. We analyze the convergence property of the proposed algorithm and conduct a set of experiments on two large-scale collections that contain millions of documents. Experimental results indicate that in contrast to algorithms named ＇stochastic variational inference＇ and ＇SGRLD＇, our algorithm achieves a faster convergence rate and better performance.

关键词： Latent Dirichlet allocation （LDA） Topic modeling Online learning Moving average

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Pathological brain detection based on online sequential extreme learning machine

Pathological brain detection based on online sequential extr...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Siyuan Lu Hainan Wang Xueyan Wu Shuihua Wang School of Computer Science and Technology Nanjing Normal University Nanjing Jiangsu China State Key Lab of CAD & CG Zhejiang University Hangzhou Zhejiang China Key laboratory of symbolic computation and knowledge engineering of ministry of education Jilin University Changchun Jilin China Key Laboratory of Statistical information technology and data mining State Statistics Bureau Chengdu Sichuan China Department of Electrical Engineering CUNY New York NY USA

ISBN: (纸本)9781509034857

Magnetic resonance imaging (MRI) is a kind of imaging modality, which offers clearer images of soft tissues than computed tomography (CT). It is especially suitable for brain disease detection. It is beneficial to detect diseases automatically and accurately. We proposed a pathological brain detection method based on brain MR images and online sequential extreme learning machine. First, seven wavelet entropies (WE) were extracted from each brain MR image to form the feature vector. Then, an online sequential extreme learning machine (OS-ELM) was trained to differentiate pathological brains from the healthy controls. The experiment results over 132 brain MRIs showed that the proposed approach achieved a sensitivity of 93.51%, a specificity of 92.22%, and an overall accuracy of 93.33%, which suggested that our method is effective.

关键词： Entropy Discrete wavelet transforms Feature extraction Pathology Training Magnetic resonance imaging Diseases

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Location based surveillance for early detection of contagious outbreaks

Location based surveillance for early detection of contagiou...

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ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2015 ACM International Symposium on Wearable Computers, UbiComp and ISWC 2015

作者： Bai, Yuan Yang, Bo Du, Zhanwei Meyers, Lauren Ancel School of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China University of Texas at Austin AustinTX73301 United States

ISBN: (纸本)9781450335751

In previous studies, non-distance-dependent surveillance strategies have improved the performance of contagious outbreaks detection. In this paper, we propose a new distance-dependent strategy that does not require ascertainment of global or local network structure, namely, simply monitoring the relative significance difference of randomly selected individuals in school and workplace. To evaluate whether such two group could indeed provide early detection, we studied a flu outbreak in contact network simulation experiments. Our experimental results show that this method could provide significant additional time to react to epidemics, especially when the infection rate is not large.

关键词： Wearable technology

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The multilevel relational data model based on trust-label semantics

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Journal of computational Information Systems 2015年第11期11卷 3949-3956页

作者： Chen, Pan Wang, Limin Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Jilin China State Key Laboratory of Computer Science Beijing China

As a new research direction in the field of database security, the technology of multilevel secure database is advancing by leaps and bounds. There are so many great multilevel secure relational models such as Bell-Lapadula model, SeaView model, Jajodia-Sandhu model and Smith-Winslett model in the last 40 years, which have solved or mitigated a lot of problems in this field with their own ways. But each of them still has one or several problems such as covert channels, semantic ambiguity, proliferation of tuples and poor expressiveness for complex situations. In this paper, we attempt to build a new model named TL model which could resolve as many problems as possible independently and retain the simpleness and expressiveness at the same time. We will clarify the TL model and present its simplicity, power and robustness. ©, 2015, Binary Information Press. All right reserved.

关键词： Semantics

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Protein-protein interaction network constructing based on text mining and reinforcement learning with application to prostate cancer 14

Protein-protein interaction network constructing based on te...

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14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015

作者： Zhu, Fei Liu, Quan Zhang, Xiaofang Shen, Bairong School of Computer Science and Technology Soochow University Suzhou215006 China Center for Systems Biology Soochow University Suzhou215006 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China

ISBN: (纸本)9781467379519

As a notoriously lethal human disease, cancer has obtained much concern for a long time. There have accumulated huge amounts of literature and experimental data on cancer-related research. It is impossible for people to deal with these texts manually to discover novel information and knowledge. However, text mining has an advantage of extracting previously unknown and understandable knowledge from large amounts of texts, and forming well-defined knowledge, providing the possibility to fully taking use of the existed texts. With the proceeding of biomedical research, people have gradually realized that complex biological functions and the phenomenon of life are the results of complex interactions among a variety of biological entities, such as protein. Deeply studying protein interaction network is essential to understand life. We, adopting reinforcement learning idea, put forward an algorithm for protein interaction network constructing. With the algorithm, nodes are used to represent proteins and edges denote interactions. During the evolutionary process, a node selects with which nodes in the network it tends to interact. Keep selecting and carrying on iteration, until eventually attaining an optimal network. The network is the result of the dynamic nature of learning behavior. As a malignancy, prostate cancer has been concerned for a long time. We attain biological texts from PubMed and establish a prostate cancer protein interaction networks by the proposed methods. The results show that our proposed method is pretty good. Network topology analysis results also show that the network node degree distribution is scale-free. © 2015 IEEE.

关键词： Reinforcement learning

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On-demand tile preload for large-scale seismic data 3D-visualization

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Journal of computational Information Systems 2015年第4期11卷 1513-1520页

作者： Wei, Xiaohui Bai, Xin Bai, Sen Li, Hongliang College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China

Real-time three-dimensional visualization for seismic data is difficult when seismic data are large-scale and usually exceed the limitation of host memories. This paper proposed a dynamic caching framework based on OCTree data structure to dynamically load data blocks (Tiles) within ROI (Region of Interest) into memory for render in runtime. In order to improve the hit rate of the cache and ensure the smoothness of interaction, an On-Demand tile Preload (ODP) mechanism and algorithm is proposed and implemented. It preloads data tiles based on tile hot zones and ROI track prediction when loading threads are idle. Experiments show that ODP achieved 21% rendering speedup on average in real-time interaction while causing none additional costs. 1553-9105/Copyright © 2015 Binary Information Press

关键词： Visualization

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