Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426148
Bin Wen, Ziqiang Luo, Yazhi Wen
The evidence has three properties including relevance, authenticity and legitimacy. For evidence, once implemented, it must not be tampered with and can always be traced back. For trust, the content can be forensics, so the relationship between each other is trustworthy and exchangeable value. Blockchain is a tamper-proof and unforgeable decentralized shared ledger that chunks data blocks chronologically into specific data structures and is cryptographically guaranteed. In this paper, we use the key technologies of blockchain to investigate and achieve collaborative security for IoT devices. This approach uses distributed crowd-sourcing to make tampering of critical data evidence (security). Combination of theoretical research and empirical validation, the paper tries to provide a technical operational and cost-effective solution for collaborative security with blockchain services and promoting the key data stability and self-healing ability.
{"title":"Evidence and Trust: IoT Collaborative Security Mechanism","authors":"Bin Wen, Ziqiang Luo, Yazhi Wen","doi":"10.1109/ICIST.2018.8426148","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426148","url":null,"abstract":"The evidence has three properties including relevance, authenticity and legitimacy. For evidence, once implemented, it must not be tampered with and can always be traced back. For trust, the content can be forensics, so the relationship between each other is trustworthy and exchangeable value. Blockchain is a tamper-proof and unforgeable decentralized shared ledger that chunks data blocks chronologically into specific data structures and is cryptographically guaranteed. In this paper, we use the key technologies of blockchain to investigate and achieve collaborative security for IoT devices. This approach uses distributed crowd-sourcing to make tampering of critical data evidence (security). Combination of theoretical research and empirical validation, the paper tries to provide a technical operational and cost-effective solution for collaborative security with blockchain services and promoting the key data stability and self-healing ability.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123357240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426135
R. Feng, Chenguang Li, Qiu Ran, Yinfeng Wu, N. Yu
With great development of wireless sensor networks (WSNs) technology, one of its important applications, source localization, has attracted numerous interests of recent scientific researches. Among different kinds of methods, techniques based on time difference of arrival (TDOA) and time of arrival (TOA) are practical and of high accuracy. In consideration of TDOA-based methods' inherent noise correlation and loss in signal-to-noise ratio (SNR), this paper focuses on TOA-based source localization method in WSNs. We formulate the localization problem as a maximum-likelihood (ML) problem, and exploit the relationship between the emitting time constant of signal and the coordinate of source to remove the time constant in the ML function. Then the conjugate gradient method is utilized to obtain the final solution. Simulation results validate the convergence of the proposed algorithm and demonstrate its better performance than some existing TDOA based techniques.
{"title":"A Novel TOA-Based Source Localization Algorithm in Wireless Sensor Networks","authors":"R. Feng, Chenguang Li, Qiu Ran, Yinfeng Wu, N. Yu","doi":"10.1109/ICIST.2018.8426135","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426135","url":null,"abstract":"With great development of wireless sensor networks (WSNs) technology, one of its important applications, source localization, has attracted numerous interests of recent scientific researches. Among different kinds of methods, techniques based on time difference of arrival (TDOA) and time of arrival (TOA) are practical and of high accuracy. In consideration of TDOA-based methods' inherent noise correlation and loss in signal-to-noise ratio (SNR), this paper focuses on TOA-based source localization method in WSNs. We formulate the localization problem as a maximum-likelihood (ML) problem, and exploit the relationship between the emitting time constant of signal and the coordinate of source to remove the time constant in the ML function. Then the conjugate gradient method is utilized to obtain the final solution. Simulation results validate the convergence of the proposed algorithm and demonstrate its better performance than some existing TDOA based techniques.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124379224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426064
Wenqiang Ji, M. Wang, Jianbin Qiu
A robust H∞ output-feedback (DOF) control method is proposed for discrete-time non-affine nonlinear systems based on Takagi-Sugeno (T-S) fuzzy models. On the basis of several convexification techniques and piecewise quadratic Lyapunov functions (PQLFs), sufficient conditions for the controller design are derived. A simulation example is presented to show the feasibility of the proposed method.
{"title":"Fuzzy-Model-Based Output Feedback Controller Design for Discrete-Time Non-Affine Nonlinear Systems via Piecewise Lyapunov Functions","authors":"Wenqiang Ji, M. Wang, Jianbin Qiu","doi":"10.1109/ICIST.2018.8426064","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426064","url":null,"abstract":"A robust H∞ output-feedback (DOF) control method is proposed for discrete-time non-affine nonlinear systems based on Takagi-Sugeno (T-S) fuzzy models. On the basis of several convexification techniques and piecewise quadratic Lyapunov functions (PQLFs), sufficient conditions for the controller design are derived. A simulation example is presented to show the feasibility of the proposed method.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116589599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426185
Zhen Wang, Hang Su, Xuemei Guo, Guoli Wang
Radio tomographic imaging (RTI) provides an efficient method to realize device-free localization (DFL) which does not require the target to carry any tags or electronic devices. By the measurement of received signal strength (RSS) between node pairs in a wireless sensor network, the attenuation image caused by the target can be reconstructed. Subsequently, the target location can be extracted from the attenuation image. Sparse Bayesian learning (SBL) can be employed for reconstruction because of the sparseness of the attenuation image. However, the fast SBL degrades in reconstruction performances due to the inaccurate estimation on the noise hyper-parameters. To address this, this paper exploits a feedback-based fast SBL framework both for homogeneous-noise and heterogeneous-noise cases. Theoretical modeling and Bayesian inference procedure are given for this feedback-based framework. Finally, RTI experimental results from three different scenarios demonstrate the effectiveness of the proposed scheme.
{"title":"Radio Tomographic Imaging with Feedback-Based Sparse Bayesian Learning","authors":"Zhen Wang, Hang Su, Xuemei Guo, Guoli Wang","doi":"10.1109/ICIST.2018.8426185","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426185","url":null,"abstract":"Radio tomographic imaging (RTI) provides an efficient method to realize device-free localization (DFL) which does not require the target to carry any tags or electronic devices. By the measurement of received signal strength (RSS) between node pairs in a wireless sensor network, the attenuation image caused by the target can be reconstructed. Subsequently, the target location can be extracted from the attenuation image. Sparse Bayesian learning (SBL) can be employed for reconstruction because of the sparseness of the attenuation image. However, the fast SBL degrades in reconstruction performances due to the inaccurate estimation on the noise hyper-parameters. To address this, this paper exploits a feedback-based fast SBL framework both for homogeneous-noise and heterogeneous-noise cases. Theoretical modeling and Bayesian inference procedure are given for this feedback-based framework. Finally, RTI experimental results from three different scenarios demonstrate the effectiveness of the proposed scheme.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130318701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426088
ChenHan Lin, Fei Long, J. Huang, Jun Li
For its wide range of applications in public security and psychotherapy, recognizing micro-expressions from facial image sequences has gain increasing attentions recently. Subtlety and short duration are major challenges for micro-expression recognition. In this paper, we propose a method for micro-expression recognition based on spatiotemporal Gabor filters. In preprocessing, for each video clip, the intensities of facial movements are first magnified by Eulerian video magnification (EVM), and then a sequence of frame difference is generated by subtracting a non-expression frame from all the frames in original video clip. Following that, we convolve a bank of spatiotemporal Gabor filters with the difference sequences, and the magnitudes of Gabor filter responses are used as features. The final features are fed up into a linear SVM for classification after spatiotemporal max pooling. The proposed method is evaluated on two micro-expression datasets, CASME2 and SMIC. Experimental results on CASME2 demonstrate the importance of preprocessing for micro-expression recognition. Furthermore, the proposed method achieves better recognition performance than some popular methods on both CASME2 and SMIC datasets, such as LBP-TOP and HOOF, in micro-expression recognition.
基于人脸图像序列的微表情识别由于在公安、心理治疗等领域的广泛应用，近年来越来越受到人们的关注。微表情识别的难点在于微表情的微妙性和持续时间短。本文提出了一种基于时空Gabor滤波器的微表情识别方法。在预处理过程中，首先对每个视频片段进行欧拉视频放大(Eulerian video magnification, EVM)，然后在原始视频片段的所有帧中减去一个无表情帧，生成一个帧差序列。然后，我们将一组时空Gabor滤波器与差分序列进行卷积，并将Gabor滤波器响应的幅度作为特征。经过时空最大池化后，将最终特征输入线性支持向量机进行分类。在CASME2和SMIC两个微表情数据集上对该方法进行了评价。CASME2的实验结果证明了预处理对微表情识别的重要性。此外，在微表情识别方面，该方法在CASME2和SMIC数据集上的识别性能均优于现有的LBP-TOP和HOOF方法。
{"title":"Micro-Expression Recognition Based on Spatiotemporal Gabor Filters","authors":"ChenHan Lin, Fei Long, J. Huang, Jun Li","doi":"10.1109/ICIST.2018.8426088","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426088","url":null,"abstract":"For its wide range of applications in public security and psychotherapy, recognizing micro-expressions from facial image sequences has gain increasing attentions recently. Subtlety and short duration are major challenges for micro-expression recognition. In this paper, we propose a method for micro-expression recognition based on spatiotemporal Gabor filters. In preprocessing, for each video clip, the intensities of facial movements are first magnified by Eulerian video magnification (EVM), and then a sequence of frame difference is generated by subtracting a non-expression frame from all the frames in original video clip. Following that, we convolve a bank of spatiotemporal Gabor filters with the difference sequences, and the magnitudes of Gabor filter responses are used as features. The final features are fed up into a linear SVM for classification after spatiotemporal max pooling. The proposed method is evaluated on two micro-expression datasets, CASME2 and SMIC. Experimental results on CASME2 demonstrate the importance of preprocessing for micro-expression recognition. Furthermore, the proposed method achieves better recognition performance than some popular methods on both CASME2 and SMIC datasets, such as LBP-TOP and HOOF, in micro-expression recognition.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128303172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426093
Mingming Ha, Ding Wang, Derong Liu, Bo Zhao
This paper investigates an event-based controller for the near-optimal control policy of nonaffine discrete-time systems with constrained inputs. This algorithm is based on the dual heuristic dynamic programming (DHP) approach. In order to overcome the challenge which is generated by systems with control constraints, a useful nonquadratic performance index is introduced. Besides, the event-based control technique is employed to reduce the computational burden. Meanwhile, a Lyapunov stability analysis is elaborated to prove that the proposed control algorithm can asymptotically stabilize this type of systems. Moreover, we give the stablility condition and the design procedure of the event-based controller. Additionally, we apply three neural networks to realize the present algorithm. Finally, a numerical simulation is conducted to verify the feasibility and performance of the proposed control algorithm.
{"title":"Adaptive Event-Based Control for Discrete-Time Nonaffine Systems with Constrained Inputs","authors":"Mingming Ha, Ding Wang, Derong Liu, Bo Zhao","doi":"10.1109/ICIST.2018.8426093","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426093","url":null,"abstract":"This paper investigates an event-based controller for the near-optimal control policy of nonaffine discrete-time systems with constrained inputs. This algorithm is based on the dual heuristic dynamic programming (DHP) approach. In order to overcome the challenge which is generated by systems with control constraints, a useful nonquadratic performance index is introduced. Besides, the event-based control technique is employed to reduce the computational burden. Meanwhile, a Lyapunov stability analysis is elaborated to prove that the proposed control algorithm can asymptotically stabilize this type of systems. Moreover, we give the stablility condition and the design procedure of the event-based controller. Additionally, we apply three neural networks to realize the present algorithm. Finally, a numerical simulation is conducted to verify the feasibility and performance of the proposed control algorithm.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123755624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426166
Yongchi Su, Chunping Li, Shaoxu Song, Kenji Takao
As we know, table data is a popular data form in industry and scientific research fields. However, sometimes the original table data could not meet updating requirements in real applications, so we need to convert them into required form. In this paper we propose an approach to learn the transformation rules that convert original table data to target form. Based on Inductive Logic Programming(ILP), we design a learning system called Table Transformation Rule Learner (TTRL). It uses specific predicates and background knowledge for this task to generate table transformation rules. We implement a unique heuristic function (HF) in TTRL to accelerate searching process for rule generation, and we use semi-supervised learning (SSL) in order to obtain more information especially from small set of sample data. We also address the problem like over-generalization which may occur when having only positive training examples in ILP learning process. We test our program in several kinds of table data, and the result shows that the transformation rules can be learned correctly. Moreover, our designed searching strategy can greatly reduce the time cost of searching rules.
{"title":"Table Transformation Rule Learner","authors":"Yongchi Su, Chunping Li, Shaoxu Song, Kenji Takao","doi":"10.1109/ICIST.2018.8426166","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426166","url":null,"abstract":"As we know, table data is a popular data form in industry and scientific research fields. However, sometimes the original table data could not meet updating requirements in real applications, so we need to convert them into required form. In this paper we propose an approach to learn the transformation rules that convert original table data to target form. Based on Inductive Logic Programming(ILP), we design a learning system called Table Transformation Rule Learner (TTRL). It uses specific predicates and background knowledge for this task to generate table transformation rules. We implement a unique heuristic function (HF) in TTRL to accelerate searching process for rule generation, and we use semi-supervised learning (SSL) in order to obtain more information especially from small set of sample data. We also address the problem like over-generalization which may occur when having only positive training examples in ILP learning process. We test our program in several kinds of table data, and the result shows that the transformation rules can be learned correctly. Moreover, our designed searching strategy can greatly reduce the time cost of searching rules.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130228956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426079
Le Yang, Z. Zeng
The imitation of classical conditioning reflex at circuit level is a significant procedure to achieve biology-like circuit systems. In order to realize the imitation, the important process are to imitate synaptic behaviors. As an emerging device, the memristor has some excellent properties like nonvolatility, adjustability, nanoscale. Therefore, it is an appropriate candidate to simulate the synaptic behavior in artificial neural network circuits. This paper presents a memristor-CMOS hybrid circuit to imitate classical conditioning reflex of aplysia californica. Besides, the proposed circuit can simulate additional forgetting stages that are activated by the single unconditional stimulus (US) or the single conditioned stimulus (CS) after the learning stage. The learning and forgetting stages can be described as: when US and CS are given to an aplysia californica together, it forms classical conditioning reflex through associative learning. Then, giving US or CS alone to the aplysia californica after the learning, it will forget the classical conditioning reflex gradually. The proposed circuit is simulated on PSPICE to demonstrate the effectiveness.
{"title":"A Memristor-CMOS Hybrid Circuit for Classical Conditioning Reflex","authors":"Le Yang, Z. Zeng","doi":"10.1109/ICIST.2018.8426079","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426079","url":null,"abstract":"The imitation of classical conditioning reflex at circuit level is a significant procedure to achieve biology-like circuit systems. In order to realize the imitation, the important process are to imitate synaptic behaviors. As an emerging device, the memristor has some excellent properties like nonvolatility, adjustability, nanoscale. Therefore, it is an appropriate candidate to simulate the synaptic behavior in artificial neural network circuits. This paper presents a memristor-CMOS hybrid circuit to imitate classical conditioning reflex of aplysia californica. Besides, the proposed circuit can simulate additional forgetting stages that are activated by the single unconditional stimulus (US) or the single conditioned stimulus (CS) after the learning stage. The learning and forgetting stages can be described as: when US and CS are given to an aplysia californica together, it forms classical conditioning reflex through associative learning. Then, giving US or CS alone to the aplysia californica after the learning, it will forget the classical conditioning reflex gradually. The proposed circuit is simulated on PSPICE to demonstrate the effectiveness.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124394411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426173
Guoliang Zhao, Wei Wu, Degang Wang
The main results of the paper concern the enhanced tensor product model transformation-based variable universe of discourse controller (EHTPVUD) design, which uses Hammersley sampling method to generate hyper-cube grid for higher order singular value decomposition. Moreover, Hammersley sampling method-based parallel distributed compensation is also proposed as a comparison to the newly proposed variable universe of discourse controller. Error and error derivative are synthesized by the gains which are generated by Hammersley sampling method-based parallel distributed compensation. Then, EHTPVUD is designed based on the error universe of discourse and error derivative universe of discourse. Finally, EHTPVUD is tested by the gantry crane stabilization control problem and gantry crane tracking control problem.
{"title":"Enhancement of the Variable Universe of Discourse Control by Hammersley Sequence-Based TP Model Transformation","authors":"Guoliang Zhao, Wei Wu, Degang Wang","doi":"10.1109/ICIST.2018.8426173","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426173","url":null,"abstract":"The main results of the paper concern the enhanced tensor product model transformation-based variable universe of discourse controller (EHTPVUD) design, which uses Hammersley sampling method to generate hyper-cube grid for higher order singular value decomposition. Moreover, Hammersley sampling method-based parallel distributed compensation is also proposed as a comparison to the newly proposed variable universe of discourse controller. Error and error derivative are synthesized by the gains which are generated by Hammersley sampling method-based parallel distributed compensation. Then, EHTPVUD is designed based on the error universe of discourse and error derivative universe of discourse. Finally, EHTPVUD is tested by the gantry crane stabilization control problem and gantry crane tracking control problem.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115547640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426183
Dongcheng Peng, Tie-shan Li, Yang Wang, C. L. Philip Chen
In recent years, with the increasing development of Artificial Intelligence, Big Data and Cloud computing, etc., the information on the Internet has been booming, so how to obtain target information efficiently and quickly has become an urgent problem to be solved. This article aims at the data collection and acquisition problem of shipping job hunting information under the network environment. In this study, two kinds of information collection methods for shipping job hunting based on web crawler are proposed. Based on the Python standard libraries and Scrapy crawl framework, corresponding web crawler program is designed and implemented to scrape the target information from target website and store the collected data into local file eventually. Through the amount of data crawled and time consuming comparative analysis, the result demonstrates that the data collection method based on the Scrapy crawler framework is simple to operate, easily extensible, featuring being targeted, with high efficiency and fast speed in collecting shipping job hunting information. Fortunately, the collected data can not only help researchers conduct subsequent data mining analysis, but also can provide data support for the follow-up shipping job hunting information database.
{"title":"Research on Information Collection Method of Shipping Job Hunting Based on Web Crawler","authors":"Dongcheng Peng, Tie-shan Li, Yang Wang, C. L. Philip Chen","doi":"10.1109/ICIST.2018.8426183","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426183","url":null,"abstract":"In recent years, with the increasing development of Artificial Intelligence, Big Data and Cloud computing, etc., the information on the Internet has been booming, so how to obtain target information efficiently and quickly has become an urgent problem to be solved. This article aims at the data collection and acquisition problem of shipping job hunting information under the network environment. In this study, two kinds of information collection methods for shipping job hunting based on web crawler are proposed. Based on the Python standard libraries and Scrapy crawl framework, corresponding web crawler program is designed and implemented to scrape the target information from target website and store the collected data into local file eventually. Through the amount of data crawled and time consuming comparative analysis, the result demonstrates that the data collection method based on the Scrapy crawler framework is simple to operate, easily extensible, featuring being targeted, with high efficiency and fast speed in collecting shipping job hunting information. Fortunately, the collected data can not only help researchers conduct subsequent data mining analysis, but also can provide data support for the follow-up shipping job hunting information database.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115832200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：