Pub Date : 2009-09-22DOI: 10.1109/GRC.2009.5255026
Xiang Yin, I. Düntsch, G. Gediga
Granular computing is closely related to the depth of the detail of information with which we are presented, or choose to process. In spatial cognition and image processing such detail is given by the resolution of a picture. The quadtree representation of an image offers a quick look at the image at various stages of granularity, and successive quadtree representations can be used to represent change. In this paper we present a heuristic algorithm to find a root node of a region quadtree which reduces the number of leaves when compared with the standard quadtree decomposition.
{"title":"Choosing the root node of a quadtree","authors":"Xiang Yin, I. Düntsch, G. Gediga","doi":"10.1109/GRC.2009.5255026","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255026","url":null,"abstract":"Granular computing is closely related to the depth of the detail of information with which we are presented, or choose to process. In spatial cognition and image processing such detail is given by the resolution of a picture. The quadtree representation of an image offers a quick look at the image at various stages of granularity, and successive quadtree representations can be used to represent change. In this paper we present a heuristic algorithm to find a root node of a region quadtree which reduces the number of leaves when compared with the standard quadtree decomposition.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128027944","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 : 2009-09-22DOI: 10.1109/GRC.2009.5255031
Xibei Yang, Xinzhe Li, T. Lin
Neighborhood System(NS) is revisited from the view of Formal GrC Model. NS formalize the ancient intuition, infinitesimals, which led to the invention of calculus, topology and non-standard analysis. In this paper, we show that Ziarko's variable precision model can be expressed by NS. Together with previously known results (NS includes topology, binary relation(binary neighborhood system) and covering as special cases), NS is the most general rough set model. A new operation “and” is introduced that generates a base of a topology; we will call it knowledge base. The approximations based on such knowledge base can be interpreted as learning. This is different from traditional rough set approximations.
{"title":"First GrC model - Neighborhood Systems the most general rough set models","authors":"Xibei Yang, Xinzhe Li, T. Lin","doi":"10.1109/GRC.2009.5255031","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255031","url":null,"abstract":"Neighborhood System(NS) is revisited from the view of Formal GrC Model. NS formalize the ancient intuition, infinitesimals, which led to the invention of calculus, topology and non-standard analysis. In this paper, we show that Ziarko's variable precision model can be expressed by NS. Together with previously known results (NS includes topology, binary relation(binary neighborhood system) and covering as special cases), NS is the most general rough set model. A new operation “and” is introduced that generates a base of a topology; we will call it knowledge base. The approximations based on such knowledge base can be interpreted as learning. This is different from traditional rough set approximations.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126526026","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 : 2009-09-22DOI: 10.1109/GRC.2009.5255024
Juan Yu, Jianmin Han, Jianmin Chen, Zanzhu Xia
K-anonymity is an effective model for protecting privacy while publishing data. KACA algorithm is a typical generalization algorithm for k-anonymity, which can generate small information loss, but its efficiency is low, especially when dataset is large. Another generalization algorithm, topDown, has high efficiency but generates heavy information loss. In this paper, we propose an efficient generalization algorithm for k-anonymity, called topDown-KACA, which combines the topDown algorithm with the KACA algorithm. The idea of topDown-KACA algorithm is to partition the whole dataset into some subsets by topDown algorithm at first, and then k-anonymize these subsets by KACA algorithm respectively. Experiments show that the proposed algorithm is more efficient than KACA algorithm with similar information loss, and generates less information loss than topDown algorithm with similar execution time.
k -匿名是一种有效的数据发布隐私保护模式。KACA算法是一种典型的k-匿名泛化算法，其产生的信息损失较小，但效率较低，特别是在数据集较大的情况下。另一种泛化算法topDown效率高，但信息损失大。本文将topDown算法与KACA算法相结合，提出了一种高效的k-匿名泛化算法topDown-KACA。topDown-KACA算法的思想是首先通过topDown算法将整个数据集划分为若干子集，然后分别通过KACA算法对这些子集进行k匿名化。实验表明，该算法在信息损失相似的情况下比KACA算法效率更高，在执行时间相似的情况下比topDown算法产生的信息损失更小。
{"title":"TopDown-KACA: An efficient local-recoding algorithm for k-anonymity","authors":"Juan Yu, Jianmin Han, Jianmin Chen, Zanzhu Xia","doi":"10.1109/GRC.2009.5255024","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255024","url":null,"abstract":"K-anonymity is an effective model for protecting privacy while publishing data. KACA algorithm is a typical generalization algorithm for k-anonymity, which can generate small information loss, but its efficiency is low, especially when dataset is large. Another generalization algorithm, topDown, has high efficiency but generates heavy information loss. In this paper, we propose an efficient generalization algorithm for k-anonymity, called topDown-KACA, which combines the topDown algorithm with the KACA algorithm. The idea of topDown-KACA algorithm is to partition the whole dataset into some subsets by topDown algorithm at first, and then k-anonymize these subsets by KACA algorithm respectively. Experiments show that the proposed algorithm is more efficient than KACA algorithm with similar information loss, and generates less information loss than topDown algorithm with similar execution time.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121882300","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 : 2009-09-22DOI: 10.1109/GRC.2009.5255167
Chien-Chung Chan, G. Tzeng
This paper introduces the representation of generalized Dominance-based decision tables by neighborhood systems. Dominance-based Rough Set Approach (DRSA) introduced by Greco et al. is a useful tool for multi-criteria data analysis problems. Recently, Dembczynski et al. introduced the concept of generalized decisions as a generalization of the DRSA where criteria in a decision table may be assigned a range of values. We use blocks indexed by pairs of decision values as elementary neighborhood systems for computing approximations of generalized decision tables. Each generalized decision table is represented by a pair of lower and upper singleton decision tables, which are represented by a pair of elementary neighborhood systems. A generalized decision table is definable if both its lower and upper singleton decision tables are definable. In addition, we introduce two simple algorithms based on minimum and maximum operations for making a decision table definable. The proposed approach is demonstrated by examples.
{"title":"Representation of second-order Dominance-based approximation space by neighborhood systems","authors":"Chien-Chung Chan, G. Tzeng","doi":"10.1109/GRC.2009.5255167","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255167","url":null,"abstract":"This paper introduces the representation of generalized Dominance-based decision tables by neighborhood systems. Dominance-based Rough Set Approach (DRSA) introduced by Greco et al. is a useful tool for multi-criteria data analysis problems. Recently, Dembczynski et al. introduced the concept of generalized decisions as a generalization of the DRSA where criteria in a decision table may be assigned a range of values. We use blocks indexed by pairs of decision values as elementary neighborhood systems for computing approximations of generalized decision tables. Each generalized decision table is represented by a pair of lower and upper singleton decision tables, which are represented by a pair of elementary neighborhood systems. A generalized decision table is definable if both its lower and upper singleton decision tables are definable. In addition, we introduce two simple algorithms based on minimum and maximum operations for making a decision table definable. The proposed approach is demonstrated by examples.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125022623","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 : 2009-09-22DOI: 10.1109/GRC.2009.5255092
Yan Liang, Yaoting Zhu
Overlapping ambiguity is a kind of ambiguity phenomena in the Chinese word segmentation. Up to now, the researches on overlapping ambiguity always focused on the 3-character overlapping ambiguity strings. In this paper the distribution and forms of overlapping ambiguity strings are discussed empirically. In order to deal with the overlapping ambiguity strings in different forms synchronously, a conditional random fields model is used. Different features for overlapping ambiguity resolution are explored, including component independency probability, component co-occurrence probability, in-word probability of a component and string structures. The experimental results show that the precision reaches 93.81% in the open test.
{"title":"A conditional random fields model for overlapping ambiguity resolution in Chinese word segmentation","authors":"Yan Liang, Yaoting Zhu","doi":"10.1109/GRC.2009.5255092","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255092","url":null,"abstract":"Overlapping ambiguity is a kind of ambiguity phenomena in the Chinese word segmentation. Up to now, the researches on overlapping ambiguity always focused on the 3-character overlapping ambiguity strings. In this paper the distribution and forms of overlapping ambiguity strings are discussed empirically. In order to deal with the overlapping ambiguity strings in different forms synchronously, a conditional random fields model is used. Different features for overlapping ambiguity resolution are explored, including component independency probability, component co-occurrence probability, in-word probability of a component and string structures. The experimental results show that the precision reaches 93.81% in the open test.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123251441","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 : 2009-09-22DOI: 10.1109/GRC.2009.5255049
Keming Xie, Xiaoli Hao, Jun Xie
For granular computing has advantage to handle a great deal of fuzzy information, it provides new thoughts for image segmentation. Firstly, the paper defines a new granular computing model, which is granular lattice matrix model. Secondly, we applied the model to image segmentation and proposed a new algorithm of segmentation. Finally, we certify the new algorithm is better than traditional algorithm on edge fining by tests.
{"title":"Image segmentation algorithm based on granular lattice matrix space","authors":"Keming Xie, Xiaoli Hao, Jun Xie","doi":"10.1109/GRC.2009.5255049","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255049","url":null,"abstract":"For granular computing has advantage to handle a great deal of fuzzy information, it provides new thoughts for image segmentation. Firstly, the paper defines a new granular computing model, which is granular lattice matrix model. Secondly, we applied the model to image segmentation and proposed a new algorithm of segmentation. Finally, we certify the new algorithm is better than traditional algorithm on edge fining by tests.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"105 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131893603","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 : 2009-09-22DOI: 10.1109/GRC.2009.5255116
Tao Huang, Hongyang Cui
The rich educational resources form network is a great role of promoting for the development of education, but educational retrieval is ineffective at present. Search engine is an available tool but the precision of retrieval is still the crucial problem. Text clustering is an automatic technology to summarize and classified text information. Using the text clustering technology in the field of educational search engine will improve the accuracy of retrieval. Presently clustering in search engine has some preliminary study at home and abroad. There are some clustering engine trial systems can be used on line, but those systems are usually only support for English and not special for professional fields. This paper discusses the concept as well as the lifecycle of the text clustering, then use the search engine tool-- Lucene index the Chinese educational resources, supplied to the Carrot2 tools to build a text-based search results clustering engine, compares the clustering engine with the search engine and analysis the experiments data. As the result achieve Cluster retrieval of educational resources.
{"title":"The implement of searching engine for educational resources using text clustering","authors":"Tao Huang, Hongyang Cui","doi":"10.1109/GRC.2009.5255116","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255116","url":null,"abstract":"The rich educational resources form network is a great role of promoting for the development of education, but educational retrieval is ineffective at present. Search engine is an available tool but the precision of retrieval is still the crucial problem. Text clustering is an automatic technology to summarize and classified text information. Using the text clustering technology in the field of educational search engine will improve the accuracy of retrieval. Presently clustering in search engine has some preliminary study at home and abroad. There are some clustering engine trial systems can be used on line, but those systems are usually only support for English and not special for professional fields. This paper discusses the concept as well as the lifecycle of the text clustering, then use the search engine tool-- Lucene index the Chinese educational resources, supplied to the Carrot2 tools to build a text-based search results clustering engine, compares the clustering engine with the search engine and analysis the experiments data. As the result achieve Cluster retrieval of educational resources.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131743753","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 : 2009-09-22DOI: 10.1109/GRC.2009.5255154
Tianding Chen
The license plate text automatic localization is one of the important research subjects in the intelligent transportation system. License plate texts provide highly condensed information about the contents of images. It proposes a license plate text localization method using discrete wavelet transform (DWT) and neural network. Because the DWT coefficients provide important information of text regions, this paper employs those coefficients and several image processing techniques to preliminarily locate candidate license plate text regions. Then the morphological dilation operation and the neural network are employed to raise the precision rate of the location for license plate text. The objective of the research is to increase the recognition rate of license plates and to improve the success rate of license plate locating. According to the experimental results, the proposed method can successfully locate text region from complex environment. It demonstrates the feasibility of this system and achieves 96% of the correct plate location rate.
{"title":"License plate text localization using DWT and neural network","authors":"Tianding Chen","doi":"10.1109/GRC.2009.5255154","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255154","url":null,"abstract":"The license plate text automatic localization is one of the important research subjects in the intelligent transportation system. License plate texts provide highly condensed information about the contents of images. It proposes a license plate text localization method using discrete wavelet transform (DWT) and neural network. Because the DWT coefficients provide important information of text regions, this paper employs those coefficients and several image processing techniques to preliminarily locate candidate license plate text regions. Then the morphological dilation operation and the neural network are employed to raise the precision rate of the location for license plate text. The objective of the research is to increase the recognition rate of license plates and to improve the success rate of license plate locating. According to the experimental results, the proposed method can successfully locate text region from complex environment. It demonstrates the feasibility of this system and achieves 96% of the correct plate location rate.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116597403","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 : 2009-09-22DOI: 10.1109/GRC.2009.5255122
Jun-guo Hu, Qiang Wu
Based on the granular computing theory, a new granularity model of Web structure is proposed in this paper, a new concept called webpage granularity is defined, and some associated factors are presented to impact on the organizational structure of website. Finally, an example is given to calculate and verify the model.
{"title":"Web structure model based on granular computing","authors":"Jun-guo Hu, Qiang Wu","doi":"10.1109/GRC.2009.5255122","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255122","url":null,"abstract":"Based on the granular computing theory, a new granularity model of Web structure is proposed in this paper, a new concept called webpage granularity is defined, and some associated factors are presented to impact on the organizational structure of website. Finally, an example is given to calculate and verify the model.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122277055","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 : 2009-09-22DOI: 10.1109/GRC.2009.5255067
Sua Tan, Anmin Zhu, Simon X. Yang
A genetic algorithm (GA)-based fuzzy-interference control system with an accelerate/brake (A/B) module is developed for a mobile robot in unknown environments with moving obstacles. The A/B module of the proposed system is to enable the mobile robot to make human-like decisions as it moves toward a target. Under the control of the proposed fuzzy inference model, the robot can perform well in avoiding both static and moving obstacles, like human beings, along a reasonable short path. In addition, a GA module is employed to tune the membership functions, which improves the performance of the fuzzy-inference system. The GA is an effective auto-tuning technique in optimizing systems without suffering from local minima. The effectiveness of the proposed approach is demonstrated by simulation studies.
{"title":"A GA-based fuzzy logic approach to mobile robot navigation in unknown dynamic environments with moving obstacles","authors":"Sua Tan, Anmin Zhu, Simon X. Yang","doi":"10.1109/GRC.2009.5255067","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255067","url":null,"abstract":"A genetic algorithm (GA)-based fuzzy-interference control system with an accelerate/brake (A/B) module is developed for a mobile robot in unknown environments with moving obstacles. The A/B module of the proposed system is to enable the mobile robot to make human-like decisions as it moves toward a target. Under the control of the proposed fuzzy inference model, the robot can perform well in avoiding both static and moving obstacles, like human beings, along a reasonable short path. In addition, a GA module is employed to tune the membership functions, which improves the performance of the fuzzy-inference system. The GA is an effective auto-tuning technique in optimizing systems without suffering from local minima. The effectiveness of the proposed approach is demonstrated by simulation studies.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131143871","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}
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