F. Wang, Hakan Duman, Duong Nguyen, Simon Thompson
This paper presents a novel approach of overlapping communities generation for online support forums. Different from traditional online forums that provide the most similar or relevant information to respond to a user query, the approach proposed in this paper manages online forums and provides user support based on overlapping communities. Inspired by natural societies, a forum is deemed as a complex network in which all entities (keywords, posts and user) of an online forum are grouped into a series of communities that can share members with each other. To enable this, a kind of keyword association graph is constructed based on the co-occurrences of keywords in user posts. CPM (Clique Percolation Method) is then applied to discover closely connected cliques (core clusters) in the graph. The core keyword clusters absorb related posts and users to form communities and the communities are naturally overlapping. The communities are also extended to include other un-clustered but relevant posts and users so all entities in the forum belong to at least one community. Overlapping communities in online forums provide a useful means to support various services including recommendation, alerting and profiling customer support.
{"title":"Overlapping Communities Generation for Online Support Forums","authors":"F. Wang, Hakan Duman, Duong Nguyen, Simon Thompson","doi":"10.1109/ICAIS.2009.36","DOIUrl":"https://doi.org/10.1109/ICAIS.2009.36","url":null,"abstract":"This paper presents a novel approach of overlapping communities generation for online support forums. Different from traditional online forums that provide the most similar or relevant information to respond to a user query, the approach proposed in this paper manages online forums and provides user support based on overlapping communities. Inspired by natural societies, a forum is deemed as a complex network in which all entities (keywords, posts and user) of an online forum are grouped into a series of communities that can share members with each other. To enable this, a kind of keyword association graph is constructed based on the co-occurrences of keywords in user posts. CPM (Clique Percolation Method) is then applied to discover closely connected cliques (core clusters) in the graph. The core keyword clusters absorb related posts and users to form communities and the communities are naturally overlapping. The communities are also extended to include other un-clustered but relevant posts and users so all entities in the forum belong to at least one community. Overlapping communities in online forums provide a useful means to support various services including recommendation, alerting and profiling customer support.","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127482356","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}
Complex systems composed of many components can operate in an inappropriate way. Information about the system is obtained in time, gradually. The assessment of casualties in such situation has challenged many researchers. The present paper provides a new compact methodology for diagnostics of faults form measurements: Space of measurements is divided into symptoms. Each symptom is able to admit some faults as possible and exclude some as impossible. This concept is based on fuzzy logic approach and provides an efficient alternative to usual probabilistic oriented methodologies. These relations between symptoms and faults are stated in the mapping table as logical rules. The diagnosis information is gathered online and aggregated on the side of symptoms or on the side of faults. This paper provides and compares a set of different methods for transformation of measured information into truth rates for each fault.
{"title":"From Symptoms to Faults: Temporal Reasoning Methods","authors":"J. Kukal, K. Macek, J. Rojicek, J. Trojanová","doi":"10.1109/ICAIS.2009.33","DOIUrl":"https://doi.org/10.1109/ICAIS.2009.33","url":null,"abstract":"Complex systems composed of many components can operate in an inappropriate way. Information about the system is obtained in time, gradually. The assessment of casualties in such situation has challenged many researchers. The present paper provides a new compact methodology for diagnostics of faults form measurements: Space of measurements is divided into symptoms. Each symptom is able to admit some faults as possible and exclude some as impossible. This concept is based on fuzzy logic approach and provides an efficient alternative to usual probabilistic oriented methodologies. These relations between symptoms and faults are stated in the mapping table as logical rules. The diagnosis information is gathered online and aggregated on the side of symptoms or on the side of faults. This paper provides and compares a set of different methods for transformation of measured information into truth rates for each fault.","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"107 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125988465","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}
An adaptive strategy for knowledge-based control of sophisticated plants is considered. The domain knowledge is structured using a set of ontologies – factual ontology and functional ontologies (for tasks, problem solving methods, way to realize the methods, activities – adaptive control, monitoring). The active part of the control system is accomplished using a multiagent system. An Ant Colony Optimization is proposed for fulfilling different optimization procedures. A brief description is given for the structure, the functions and the processes of the developed multiface control system. The software realization is OWL-based for the ontologies and JADE-based for the intelligent agents. An example for adaptive control of a non-square (SITO) plant is considered.
{"title":"Adaptive Multiagent - Ontology System for SITO Plant Control","authors":"M. Hadjiski, V. Boishina","doi":"10.1109/ICAIS.2009.13","DOIUrl":"https://doi.org/10.1109/ICAIS.2009.13","url":null,"abstract":"An adaptive strategy for knowledge-based control of sophisticated plants is considered. The domain knowledge is structured using a set of ontologies – factual ontology and functional ontologies (for tasks, problem solving methods, way to realize the methods, activities – adaptive control, monitoring). The active part of the control system is accomplished using a multiagent system. An Ant Colony Optimization is proposed for fulfilling different optimization procedures. A brief description is given for the structure, the functions and the processes of the developed multiface control system. The software realization is OWL-based for the ontologies and JADE-based for the intelligent agents. An example for adaptive control of a non-square (SITO) plant is considered.","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133829436","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}
Multi-class approaches for SVMs are based on composition of binary SVM classifiers. Due to the numerous binary classifiers to be considered, for large training sets, this approach is known to be time expensive. In our approach, we improve time efficiency using concurrently two strategies: incremental training and reduction of trained binary SVMs. We present the exact migration conditions for the binary SVMs during their incremental training. We rewrite these conditions for the case when the regularization parameter is optimized. The obtained results are applied to a multi-class incremental / decremental SVM based on the Adaptive Directed Acyclic Graph. The regularization parameter is optimized on-line, and not by retraining the SVM with all input samples for each value of the regularization parameter.
{"title":"A Multi-class Incremental and Decremental SVM Approach Using Adaptive Directed Acyclic Graphs","authors":"H. Gâlmeanu, Răzvan Andonie","doi":"10.1109/ICAIS.2009.27","DOIUrl":"https://doi.org/10.1109/ICAIS.2009.27","url":null,"abstract":"Multi-class approaches for SVMs are based on composition of binary SVM classifiers. Due to the numerous binary classifiers to be considered, for large training sets, this approach is known to be time expensive. In our approach, we improve time efficiency using concurrently two strategies: incremental training and reduction of trained binary SVMs. We present the exact migration conditions for the binary SVMs during their incremental training. We rewrite these conditions for the case when the regularization parameter is optimized. The obtained results are applied to a multi-class incremental / decremental SVM based on the Adaptive Directed Acyclic Graph. The regularization parameter is optimized on-line, and not by retraining the SVM with all input samples for each value of the regularization parameter.","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115902535","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}
Virtual organizations in large-scale distributed environments can organize their communication in a hierarchical topology (i.e., trees). However, such topologies can be unreliable as local failures have a global impact in the organization. Hierarchical topologies need to adapt continuously to changes of the underlying environment. Pro-active and re-active self-organization can make such topologies highly robust. This paper proposes AETOS, the Adaptive Epidemic Tree Overlay Service. AETOS is a new agent-based approach for building and maintaining on-demand robust tree topologies that structure communication. Agents are pro-actively (self)-organized appropriately in a tree to minimize the effect of failures. In addition, they re-actively rewire their connections to reflect changes in the environment. The self-organization model, the control of the system and an illustrative example are discussed in this paper.
{"title":"Adaptive Agent-Based Self-Organization for Robust Hierarchical Topologies","authors":"Evangelos Pournaras, M. Warnier, F. Brazier","doi":"10.1109/ICAIS.2009.21","DOIUrl":"https://doi.org/10.1109/ICAIS.2009.21","url":null,"abstract":"Virtual organizations in large-scale distributed environments can organize their communication in a hierarchical topology (i.e., trees). However, such topologies can be unreliable as local failures have a global impact in the organization. Hierarchical topologies need to adapt continuously to changes of the underlying environment. Pro-active and re-active self-organization can make such topologies highly robust. This paper proposes AETOS, the Adaptive Epidemic Tree Overlay Service. AETOS is a new agent-based approach for building and maintaining on-demand robust tree topologies that structure communication. Agents are pro-actively (self)-organized appropriately in a tree to minimize the effect of failures. In addition, they re-actively rewire their connections to reflect changes in the environment. The self-organization model, the control of the system and an illustrative example are discussed in this paper.","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"07 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129229285","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 ambitious goals of autonomic management require complex, adaptable processing capabilities that prove extremely difficult to conceive and implement. This paper proposes a solution for the opportunistic integration of specialised autonomic management resources, so as to obtain complex, adaptable management strategies. The paper introduces an architecture that follows the proposed solution and provides a reusable framework that implements this architecture. The solution's validity is indicated by experimental results obtained by testing the framework prototype on a sample home security application.
{"title":"Creating Complex, Adaptable Management Strategies via the Opportunistic Integration of Decentralised Management Resources","authors":"Y. Maurel, A. Diaconescu, P. Lalanda","doi":"10.1109/ICAIS.2009.23","DOIUrl":"https://doi.org/10.1109/ICAIS.2009.23","url":null,"abstract":"The ambitious goals of autonomic management require complex, adaptable processing capabilities that prove extremely difficult to conceive and implement. This paper proposes a solution for the opportunistic integration of specialised autonomic management resources, so as to obtain complex, adaptable management strategies. The paper introduces an architecture that follows the proposed solution and provides a reusable framework that implements this architecture. The solution's validity is indicated by experimental results obtained by testing the framework prototype on a sample home security application.","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115129734","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}
Gene expression microarrays are the most commonly available source of high-throughput biological data. Each microarray experiment is supposed to measure the gene expression levels of a set of genes in a number of different experimental conditions or time points. Integration of results from different microarray experiments to the specific analysis is an important and yet challenging problem. Direct integration of microarrays is often ineffective because of the diverse types of experiment specific variations. In this paper, we propose a new hybrid method, which is specially suited for integration analysis of time series expression data across different experiments. The proposed algorithm utilizes Dynamic Time Warping (DTW) distance in order to measure the similarity between time expression profiles. First for each considered time series dataset a quadratic distance matrix that contains the DTW distances calculated between the expression profiles of each gene pair is built. Then using a hybrid aggregation algorithm the obtained DTW distance matrices are transformed into a single matrix, consisting of one overall DTW distance per each gene pair. The values of the resulting matrix can be interpreted as the consensus DTW distances supported by all the experiments. These may be further analyzed and help find the relationship among the genes. The proposed method is validated on gene expression time series data coming from two independent studies examining the global cell-cycle control of gene expression in fission yeast Schizosaccharomyces pombe.
基因表达微阵列是高通量生物数据最常见的来源。每个微阵列实验都应该测量一组基因在多个不同实验条件或时间点的基因表达水平。将不同微阵列实验的结果整合到具体分析中是一个重要而又具有挑战性的问题。微阵列的直接集成往往是无效的，因为不同类型的实验特定的变化。本文提出了一种新的混合方法，该方法特别适用于不同实验时间序列表达式数据的积分分析。该算法利用动态时间翘曲(Dynamic Time Warping, DTW)距离来度量时间表达轮廓之间的相似性。首先，为每个考虑的时间序列数据集建立一个二次距离矩阵，该矩阵包含每个基因对表达谱之间计算的DTW距离。然后使用混合聚合算法将得到的DTW距离矩阵转化为单个矩阵，每个基因对包含一个总DTW距离。结果矩阵的值可以解释为所有实验支持的一致DTW距离。这些可能会被进一步分析，并有助于发现基因之间的关系。该方法在两项独立研究的基因表达时间序列数据上得到了验证，这些研究检测了分裂酵母Schizosaccharomyces pombe基因表达的整体细胞周期控制。
{"title":"A Hybrid DTW Based Method for Integration Analysis of Time Series Data","authors":"V. Boeva, E. Kostadinova","doi":"10.1109/ICAIS.2009.18","DOIUrl":"https://doi.org/10.1109/ICAIS.2009.18","url":null,"abstract":"Gene expression microarrays are the most commonly available source of high-throughput biological data. Each microarray experiment is supposed to measure the gene expression levels of a set of genes in a number of different experimental conditions or time points. Integration of results from different microarray experiments to the specific analysis is an important and yet challenging problem. Direct integration of microarrays is often ineffective because of the diverse types of experiment specific variations. In this paper, we propose a new hybrid method, which is specially suited for integration analysis of time series expression data across different experiments. The proposed algorithm utilizes Dynamic Time Warping (DTW) distance in order to measure the similarity between time expression profiles. First for each considered time series dataset a quadratic distance matrix that contains the DTW distances calculated between the expression profiles of each gene pair is built. Then using a hybrid aggregation algorithm the obtained DTW distance matrices are transformed into a single matrix, consisting of one overall DTW distance per each gene pair. The values of the resulting matrix can be interpreted as the consensus DTW distances supported by all the experiments. These may be further analyzed and help find the relationship among the genes. The proposed method is validated on gene expression time series data coming from two independent studies examining the global cell-cycle control of gene expression in fission yeast Schizosaccharomyces pombe.","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126372069","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 recent years a swarm-based optimization methodology called Particle Swarm Optimization (PSO) has developed. If one wants to apply PSO one has to specify several parameters as well as to select a neighborhood topology. Several topologies being widely used can be found in literature. This raises the question, which one fits best to your application at hand. To get rid of this topology selection problem, a new concept called Polymorphic Particle Swarm Optimization (PolyPSO) is proposed. PolyPSO generalizes the standard update rule by a polymorphic update rule. The mathematical expression of this polymorphic update rule can be changed on symbolic level. This polymorphic update rule is an adaptive update rule changing symbols based on accumulative histograms and roulette-wheel sampling. PolyPSO is applied to four typical benchmark functions known from literature. In most cases it outperforms the other PSO variants under consideration. Since PolyPSO performs not worse it can be used as alternative to solve this way the topology selection problem.
{"title":"Particle Swarm Optimization with Polymorphic Update Rules","authors":"Christian Veenhuis","doi":"10.1109/ICAIS.2009.30","DOIUrl":"https://doi.org/10.1109/ICAIS.2009.30","url":null,"abstract":"In recent years a swarm-based optimization methodology called Particle Swarm Optimization (PSO) has developed. If one wants to apply PSO one has to specify several parameters as well as to select a neighborhood topology. Several topologies being widely used can be found in literature. This raises the question, which one fits best to your application at hand. To get rid of this topology selection problem, a new concept called Polymorphic Particle Swarm Optimization (PolyPSO) is proposed. PolyPSO generalizes the standard update rule by a polymorphic update rule. The mathematical expression of this polymorphic update rule can be changed on symbolic level. This polymorphic update rule is an adaptive update rule changing symbols based on accumulative histograms and roulette-wheel sampling. PolyPSO is applied to four typical benchmark functions known from literature. In most cases it outperforms the other PSO variants under consideration. Since PolyPSO performs not worse it can be used as alternative to solve this way the topology selection problem.","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129805528","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 : 2009-09-24DOI: 10.1007/978-3-642-16236-7_4
K. Matsui, Haruo Sato
{"title":"A Comparison of Genotype Representations to Acquire Stock Trading Strategy Using Genetic Algorithms","authors":"K. Matsui, Haruo Sato","doi":"10.1007/978-3-642-16236-7_4","DOIUrl":"https://doi.org/10.1007/978-3-642-16236-7_4","url":null,"abstract":"","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122943543","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 work a novel training algorithm is proposed for the formation of topology preserving maps. In the proposed algorithm the weights are updated incrementally by using a higher-order difference equation, which implements a low pass digital filter. It is shown that by suitably choosing the filter the learning process can adaptively follow a specific dynamic.
{"title":"A Learning Algorithm for Self-Organizing Maps Based on a Low-Pass Filter Scheme","authors":"M. Tucci, Marco Raugi","doi":"10.1109/ICAIS.2009.15","DOIUrl":"https://doi.org/10.1109/ICAIS.2009.15","url":null,"abstract":"In this work a novel training algorithm is proposed for the formation of topology preserving maps. In the proposed algorithm the weights are updated incrementally by using a higher-order difference equation, which implements a low pass digital filter. It is shown that by suitably choosing the filter the learning process can adaptively follow a specific dynamic.","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114405459","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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