M. Esmaeili, Mohamad H. Jabalameli, Zeinab Moghadam
In this paper, dynamic synapse neural network (DSNN) has been applied to perform EEG signal recognition task. The wavelet packet transform is applied to the EEG signal in order to decompose it into frequency sub-bands, before being introduced to the neural network. In this study we have applied a genetic algorithm (GA) learning method with different fitness functions to optimize the neural network. The advantage of the GA method is that it facilitates finding of a semi-optimal parameter set in the search space domain. The network has been testes for EEG signals tat are provided from BCI Competition 2003 and the results show the power of DSNN in processing of noisy nature signals as EEG signals.
{"title":"A New Scheme of EEG Signals Processing in Brain-Computer Interface Systems","authors":"M. Esmaeili, Mohamad H. Jabalameli, Zeinab Moghadam","doi":"10.1109/GrC.2007.149","DOIUrl":"https://doi.org/10.1109/GrC.2007.149","url":null,"abstract":"In this paper, dynamic synapse neural network (DSNN) has been applied to perform EEG signal recognition task. The wavelet packet transform is applied to the EEG signal in order to decompose it into frequency sub-bands, before being introduced to the neural network. In this study we have applied a genetic algorithm (GA) learning method with different fitness functions to optimize the neural network. The advantage of the GA method is that it facilitates finding of a semi-optimal parameter set in the search space domain. The network has been testes for EEG signals tat are provided from BCI Competition 2003 and the results show the power of DSNN in processing of noisy nature signals as EEG signals.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130523661","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}
Experts' reasoning selects the final diagnosis from many candidates by using hierarchical differential diagnosis. In other words, candidates give a sophisticated hiearchical taxonomy, usually described as a tree. In this paper, the characteristics of experts' rules are closely examined from the viewpoint of hierarchical decision steps and and a new approach to rule mining with extraction of diagnostic taxonomy from medical datasets is introduced. The key elements of this approach are calculation of the characterization set of each decision attribute (a given class) and one of the similarities between characterization sets. From the relations between similarities, tree-based taxonomy is obtained, which includes enough information for hierarchical diagnosis. The proposed method was evaluated on three medical datasets, the experimental results of which show that induced rules correctly represent experts' decision processes.
{"title":"Mining Diagnostic Taxonomy and Diagnostic Rules for Multi-Stage Medical Diagnosis from Hospital Clinical Data","authors":"S. Tsumoto","doi":"10.1109/GrC.2007.128","DOIUrl":"https://doi.org/10.1109/GrC.2007.128","url":null,"abstract":"Experts' reasoning selects the final diagnosis from many candidates by using hierarchical differential diagnosis. In other words, candidates give a sophisticated hiearchical taxonomy, usually described as a tree. In this paper, the characteristics of experts' rules are closely examined from the viewpoint of hierarchical decision steps and and a new approach to rule mining with extraction of diagnostic taxonomy from medical datasets is introduced. The key elements of this approach are calculation of the characterization set of each decision attribute (a given class) and one of the similarities between characterization sets. From the relations between similarities, tree-based taxonomy is obtained, which includes enough information for hierarchical diagnosis. The proposed method was evaluated on three medical datasets, the experimental results of which show that induced rules correctly represent experts' decision processes.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130781513","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}
Collaborative filtering (CF) systems are being widely used in E-commerce applications to provide recommendations to users regarding products that might be of interest to them. The prediction accuracy of these systems is dependent on the size and accuracy of the data provided by users. However, the lack of sufficient guidelines governing the use and distribution of user data raises concerns over individual privacy. Users often provide the minimal information that is required for accessing these E-commerce services. In this paper, we propose a framework for obfuscating sensitive information in such a way that it protects individual privacy and also preserves the information content required for collaborative filtering. An experimental evaluation of the performance of different CF systems on the obfuscated data proves that the proposed technique for privacy preservation does not impact the accuracy of the predictions. The proposed framework also makes it possible for multiple E-commerce sites to share data in a privacy preserving manner. Problems such as the cold-start scenario faced by new E-commerce vendors, and biased results due to insufficient users, are resolved by using a shared CF server. We describe a centralized CF server model in which a centralized CF server makes recommendations by consolidating the information received from multiple sources.
{"title":"Privacy Preserving Collaborative Filtering Using Data Obfuscation","authors":"Rupa Parameswaran, D. Blough","doi":"10.1109/GrC.2007.133","DOIUrl":"https://doi.org/10.1109/GrC.2007.133","url":null,"abstract":"Collaborative filtering (CF) systems are being widely used in E-commerce applications to provide recommendations to users regarding products that might be of interest to them. The prediction accuracy of these systems is dependent on the size and accuracy of the data provided by users. However, the lack of sufficient guidelines governing the use and distribution of user data raises concerns over individual privacy. Users often provide the minimal information that is required for accessing these E-commerce services. In this paper, we propose a framework for obfuscating sensitive information in such a way that it protects individual privacy and also preserves the information content required for collaborative filtering. An experimental evaluation of the performance of different CF systems on the obfuscated data proves that the proposed technique for privacy preservation does not impact the accuracy of the predictions. The proposed framework also makes it possible for multiple E-commerce sites to share data in a privacy preserving manner. Problems such as the cold-start scenario faced by new E-commerce vendors, and biased results due to insufficient users, are resolved by using a shared CF server. We describe a centralized CF server model in which a centralized CF server makes recommendations by consolidating the information received from multiple sources.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127581346","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}
Organizational memory in today's business world forms basis for organizational learning, which is the ability of an organization to gain insight and understanding from experience through experimentation, observation, analysis, and a willingness to examine both successes and failures. This basically requires consideration of different aspects of knowledge that may reside on top of a conventional information management system. Of them, representation, retrieval and production issues of meta patterns constitute to the main theme of this article. Particularly we are interested in a formal approach to handle rough concepts. We utilize rough classifiers to propose a preliminary framework based on minimal term sets with p-norms to extract meta patterns. We describe a relational rule induction approach, which is called rila. Experimental results are provided on the mutagenesis, and the KDD Cup 2001 genes data sets.
在当今的商业世界中，组织记忆构成了组织学习的基础，组织学习是指一个组织通过实验、观察、分析以及对成功和失败进行检验的意愿，从经验中获得洞察力和理解的能力。这基本上需要考虑可能驻留在传统信息管理系统之上的知识的不同方面。其中，元模式的表示、检索和生成问题构成了本文的主题。我们特别感兴趣的是处理粗糙概念的正式方法。我们利用粗糙分类器提出了一个基于p-范数最小项集的初步框架来提取元模式。我们描述了一种关系规则归纳方法，称为rila。提供了诱变和KDD Cup 2001基因数据集的实验结果。
{"title":"Production and Retrieval of Rough Classes in Multi Relations","authors":"M. Tolun, H. Sever, Abdulkadir Gorur","doi":"10.1109/GrC.2007.56","DOIUrl":"https://doi.org/10.1109/GrC.2007.56","url":null,"abstract":"Organizational memory in today's business world forms basis for organizational learning, which is the ability of an organization to gain insight and understanding from experience through experimentation, observation, analysis, and a willingness to examine both successes and failures. This basically requires consideration of different aspects of knowledge that may reside on top of a conventional information management system. Of them, representation, retrieval and production issues of meta patterns constitute to the main theme of this article. Particularly we are interested in a formal approach to handle rough concepts. We utilize rough classifiers to propose a preliminary framework based on minimal term sets with p-norms to extract meta patterns. We describe a relational rule induction approach, which is called rila. Experimental results are provided on the mutagenesis, and the KDD Cup 2001 genes data sets.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122377662","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}
2600 years ago, YinYang was born in the ancient China with the theme "Taiji (one matter) produces YinYang; YinYang produces four forms; the four forms lead to eight diagrams; and the eight diagrams can have 64 direct combinations." This theme can be called YinYang 1-2-4-8-64. An equilibrium-based scientific decoding of YinYangl-2-4-8-64 is presented which states "Equilibrium (the one matter) has two poles (YinYang); the two poles can be mapped to a bipolar lattice with four bipolar truth values (four forms); the four values lead to eight bipolar dynamic operators (eight diagrams); and the eight operators can have 64=82 direct biological or neurobiological or any dynamic combinations. " The scientific decoding results in a bipolar dynamic logic (BDL) that satisfies four pairs of dual dynamic DeMorgan's laws and a YinYang bipolar universal modus ponens. Bipolar granular neurobiological computing with BDL is introduced.
{"title":"A Scientific Decoding of YinYang1-2-4-8-64 for Equilibrium-Based Granular Computing","authors":"Wen-Ran Zhang, J. Zhan","doi":"10.1109/GrC.2007.24","DOIUrl":"https://doi.org/10.1109/GrC.2007.24","url":null,"abstract":"2600 years ago, YinYang was born in the ancient China with the theme \"Taiji (one matter) produces YinYang; YinYang produces four forms; the four forms lead to eight diagrams; and the eight diagrams can have 64 direct combinations.\" This theme can be called YinYang 1-2-4-8-64. An equilibrium-based scientific decoding of YinYangl-2-4-8-64 is presented which states \"Equilibrium (the one matter) has two poles (YinYang); the two poles can be mapped to a bipolar lattice with four bipolar truth values (four forms); the four values lead to eight bipolar dynamic operators (eight diagrams); and the eight operators can have 64=82 direct biological or neurobiological or any dynamic combinations. \" The scientific decoding results in a bipolar dynamic logic (BDL) that satisfies four pairs of dual dynamic DeMorgan's laws and a YinYang bipolar universal modus ponens. Bipolar granular neurobiological computing with BDL is introduced.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127918679","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}
The aim of granular computing is to obtain feasible approximate solutions satisfied enough with least complexity. The logic reasoning process using extension method actually implies the ideal of granular computing. This paper uses the relation-element as the measure of granulation and applies granular computing to the reasoning process of the extension criminal reconnaissance system to reduce the complexity of the extension inference.
{"title":"Application of Granular Computing in Extension Criminal Reconnaissance System","authors":"Chen Yunhua, Yu Yongquan, Zeng Bi, Wang Minghui","doi":"10.1109/GRC.2007.39","DOIUrl":"https://doi.org/10.1109/GRC.2007.39","url":null,"abstract":"The aim of granular computing is to obtain feasible approximate solutions satisfied enough with least complexity. The logic reasoning process using extension method actually implies the ideal of granular computing. This paper uses the relation-element as the measure of granulation and applies granular computing to the reasoning process of the extension criminal reconnaissance system to reduce the complexity of the extension inference.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114795759","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}
The purpose of workflow mining is to build proper model based on event-based logs and to support the analysis and design of workflow models. The workflow mining technology had become a hot research field among computer application from the late 1990's. Firstly, the definition and research significance of the workflow mining are presented. Then, we made an overview of the current workflow mining technologies including the origin of workflow mining, the mining of the workflow models, the mining of the workflow performance and the improvement in workflow models based on the workflow mining technology. Finally, the facing challenge and the development direction of workflow mining are presented.
{"title":"Overview of Workflow Mining Technology","authors":"Chunqin Gu, Huiyou Chang, Yang Yi","doi":"10.1109/GrC.2007.86","DOIUrl":"https://doi.org/10.1109/GrC.2007.86","url":null,"abstract":"The purpose of workflow mining is to build proper model based on event-based logs and to support the analysis and design of workflow models. The workflow mining technology had become a hot research field among computer application from the late 1990's. Firstly, the definition and research significance of the workflow mining are presented. Then, we made an overview of the current workflow mining technologies including the origin of workflow mining, the mining of the workflow models, the mining of the workflow performance and the improvement in workflow models based on the workflow mining technology. Finally, the facing challenge and the development direction of workflow mining are presented.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125467174","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}
Chang Liu, Hui Wang, S. McClean, Jun Liu, Shengli Wu
Natural language processing (NLP) techniques are believed to have the potential to aid information retrieval (IR) in terms of retrieval accuracy. In this paper we report a proof of concept study on a new approach to NLP-based IR that we propose. Documents and queries are represented as syntactic parse trees, which are generated by a natural language parser. Based on this tree structured representation of documents and queries, the matching between a document and a query is executed on their tree representations, with tree comparison as the key operation. An IR experiment is designed to test if this approach is feasible. Experimental results show that this approach is promising and has the potential to outperform the standard bag of words approach to information retrieval, especially in response to long queries.
{"title":"Syntactic Information Retrieval","authors":"Chang Liu, Hui Wang, S. McClean, Jun Liu, Shengli Wu","doi":"10.1109/GrC.2007.113","DOIUrl":"https://doi.org/10.1109/GrC.2007.113","url":null,"abstract":"Natural language processing (NLP) techniques are believed to have the potential to aid information retrieval (IR) in terms of retrieval accuracy. In this paper we report a proof of concept study on a new approach to NLP-based IR that we propose. Documents and queries are represented as syntactic parse trees, which are generated by a natural language parser. Based on this tree structured representation of documents and queries, the matching between a document and a query is executed on their tree representations, with tree comparison as the key operation. An IR experiment is designed to test if this approach is feasible. Experimental results show that this approach is promising and has the potential to outperform the standard bag of words approach to information retrieval, especially in response to long queries.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125571939","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}
In this paper, a new method, named granular dynamic time warping is proposed. This method is based on the granular approach of information granulation and has the characteristics of dynamic time warping approach. Thus it can be used to cluster time series with different lengths on the granular level. To cluster time series, this method first builds the corresponding granular time series, and then does the clustering on the granular time series. With this method, higher efficiency will be achieved in clustering time series, which is a goal pursued in clustering of large amount of time series. We also illustrate the prior performance of the new method with experiments.
{"title":"Clustering Time Series with Granular Dynamic Time Warping Method","authors":"Fusheng Yu, Keqiang Dong, Fei Chen, Yongke Jiang, Wenyi Zeng","doi":"10.1109/GrC.2007.34","DOIUrl":"https://doi.org/10.1109/GrC.2007.34","url":null,"abstract":"In this paper, a new method, named granular dynamic time warping is proposed. This method is based on the granular approach of information granulation and has the characteristics of dynamic time warping approach. Thus it can be used to cluster time series with different lengths on the granular level. To cluster time series, this method first builds the corresponding granular time series, and then does the clustering on the granular time series. With this method, higher efficiency will be achieved in clustering time series, which is a goal pursued in clustering of large amount of time series. We also illustrate the prior performance of the new method with experiments.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"24 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125929196","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}
Xiayu Zhang, Yongquan Yu, Baixing Chen, Feng Ye, Tan Xingxing
Load balancing is a classical problem and a research hotspot of Web intelligence. DNS load balancing is the pioneer load balancing technology. But the existing DNS dynamic load balancing strategies have shortages. This paper puts forward a new load balancing method, which is to connect extension theory with load balancing. Extension engineering method is initially proposed by Prof. Cai Wen. It has been successfully used in various applications. In this paper, we use the operation of matter-element theory, extension set, and dependent function in extension theory as well as the membership degree of fuzzy math to set up an extension-based dynamic load balancing model of heterogeneous server cluster. It is proved by experiment that the load balancing strategy is more effective, dynamic, steady-going and in real time by using this new model.
{"title":"An Extension-Based Dynamic Load Balancing Model of Heterogeneous Server Cluster","authors":"Xiayu Zhang, Yongquan Yu, Baixing Chen, Feng Ye, Tan Xingxing","doi":"10.1109/GrC.2007.67","DOIUrl":"https://doi.org/10.1109/GrC.2007.67","url":null,"abstract":"Load balancing is a classical problem and a research hotspot of Web intelligence. DNS load balancing is the pioneer load balancing technology. But the existing DNS dynamic load balancing strategies have shortages. This paper puts forward a new load balancing method, which is to connect extension theory with load balancing. Extension engineering method is initially proposed by Prof. Cai Wen. It has been successfully used in various applications. In this paper, we use the operation of matter-element theory, extension set, and dependent function in extension theory as well as the membership degree of fuzzy math to set up an extension-based dynamic load balancing model of heterogeneous server cluster. It is proved by experiment that the load balancing strategy is more effective, dynamic, steady-going and in real time by using this new model.","PeriodicalId":259430,"journal":{"name":"2007 IEEE International Conference on Granular Computing (GRC 2007)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125810133","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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