Currently vast amounts of textual information exist in large repositories such as Web. To processes such a huge amount of information, automatic text summarization has been of great interests. Unlike many approaches which focus on sentence or paragraph extraction, in this research, we introduce a method to make extractions based on three factors of Readability, Cohesion and Topic relation. We use Harmony Search-based sentence selection to make such a summary. Once the summary is created, it is evaluated using a fitness function based on those three factors. The evaluation of the algorithm on a test collection is also presented in the paper. Our results indicate that the extracted summaries by our proposed scheme have better precision and recall than the other approaches.
{"title":"Text summarization with harmony search algorithm-based sentence extraction","authors":"Ehsan Shareghi, Leila Sharif Hassanabadi","doi":"10.1145/1456223.1456272","DOIUrl":"https://doi.org/10.1145/1456223.1456272","url":null,"abstract":"Currently vast amounts of textual information exist in large repositories such as Web. To processes such a huge amount of information, automatic text summarization has been of great interests. Unlike many approaches which focus on sentence or paragraph extraction, in this research, we introduce a method to make extractions based on three factors of Readability, Cohesion and Topic relation. We use Harmony Search-based sentence selection to make such a summary. Once the summary is created, it is evaluated using a fitness function based on those three factors. The evaluation of the algorithm on a test collection is also presented in the paper. Our results indicate that the extracted summaries by our proposed scheme have better precision and recall than the other approaches.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127387494","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}
Software systems are increasingly expected to continue operating at run-time with minimal human interaction. They should consequently be equipped with self-adaptation capabilities in order to adapt themselves in response to changes in their execution conditions. While most of the research in this area focuses on individual parts of an adaptive system, our work leverages on this research but tackles the problem where interdependent and distributed adaptations are concurrently performed. In this paper, we approach behavioural changes of component-based systems in two steps. First, we propose a process to individually adapt one component at a time. Second, we elaborate a coordination protocol to maintain globally consistent state when implementing distributed adaptations. Motivated by the potential benefits of using formalisms, we construct a formal model of our protocol using Coloured Petri Nets in order for an adaptive system to be trusted after adaptation. We verify key behavioural properties and conduct CTL model checking to assess the correctness of the model and thereby the correctness of the protocol.
{"title":"Towards modelling and analysis of a coordination protocol for dynamic software adaptation","authors":"N. Kacem, A. Kacem, M. Jmaiel, K. Drira","doi":"10.1145/1456223.1456325","DOIUrl":"https://doi.org/10.1145/1456223.1456325","url":null,"abstract":"Software systems are increasingly expected to continue operating at run-time with minimal human interaction. They should consequently be equipped with self-adaptation capabilities in order to adapt themselves in response to changes in their execution conditions. While most of the research in this area focuses on individual parts of an adaptive system, our work leverages on this research but tackles the problem where interdependent and distributed adaptations are concurrently performed. In this paper, we approach behavioural changes of component-based systems in two steps. First, we propose a process to individually adapt one component at a time. Second, we elaborate a coordination protocol to maintain globally consistent state when implementing distributed adaptations. Motivated by the potential benefits of using formalisms, we construct a formal model of our protocol using Coloured Petri Nets in order for an adaptive system to be trusted after adaptation. We verify key behavioural properties and conduct CTL model checking to assess the correctness of the model and thereby the correctness of the protocol.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133806635","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}
Even if they have proven to be relevant on traditional transactional databases, data mining tools are still inefficient on some kinds of databases. In particular, databases containing discrete values or having a value for each item, like gene expression data, are especially challenging. On such data, existing approaches either transform the data to classical binary attributes, or use discretisation, including fuzzy partition to deal with the data. However, binary mapping of such databases drives to a loss of information and extracted knowledge is not exploitable for end-users. Thus, powerful tools designed for this kind of data are needed. On the other hand, existing fuzzy approaches hardly take gradual notions into account, or are not scalable enougth to tackle the problem. In this paper, we thus propose a heuristic in order to extract tendencies, in the form of gradual association rules. A gradual rule can be read as "The more X and the less Y, then the more V and the less W". Instead of using fuzzy sets, we apply our method directly on valued data and we propose an efficient heuristic, thus reducing combinatorial complexity and scalability. Experiments on synthetic datasets show the interest of our method.
{"title":"Fast extraction of gradual association rules: a heuristic based method","authors":"Lisa Di-Jorio, Anne Laurent, M. Teisseire","doi":"10.1145/1456223.1456268","DOIUrl":"https://doi.org/10.1145/1456223.1456268","url":null,"abstract":"Even if they have proven to be relevant on traditional transactional databases, data mining tools are still inefficient on some kinds of databases. In particular, databases containing discrete values or having a value for each item, like gene expression data, are especially challenging. On such data, existing approaches either transform the data to classical binary attributes, or use discretisation, including fuzzy partition to deal with the data. However, binary mapping of such databases drives to a loss of information and extracted knowledge is not exploitable for end-users. Thus, powerful tools designed for this kind of data are needed. On the other hand, existing fuzzy approaches hardly take gradual notions into account, or are not scalable enougth to tackle the problem.\u0000 In this paper, we thus propose a heuristic in order to extract tendencies, in the form of gradual association rules. A gradual rule can be read as \"The more X and the less Y, then the more V and the less W\". Instead of using fuzzy sets, we apply our method directly on valued data and we propose an efficient heuristic, thus reducing combinatorial complexity and scalability. Experiments on synthetic datasets show the interest of our method.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114478914","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}
Christopher Malon, Matthew L. Miller, Harold Christopher Burger, E. Cosatto, H. Graf
Histological analysis on stained biopsy samples requires recognizing many kinds of local and structural details, with some awareness of context. Machine learning algorithms such as convolutional networks can be powerful tools for such problems, but often there may not be enough training data to exploit them to their full potential. In this paper, we show how convolutional networks can be combined with appropriate image analysis to achieve high accuracies on three very different tasks in breast and gastric cancer grading, despite the challenge of limited training data. The three problems are to count mitotic figures in the breast, to recognize epithelial layers in the stomach, and to detect signet ring cells.
{"title":"Identifying histological elements with convolutional neural networks","authors":"Christopher Malon, Matthew L. Miller, Harold Christopher Burger, E. Cosatto, H. Graf","doi":"10.1145/1456223.1456316","DOIUrl":"https://doi.org/10.1145/1456223.1456316","url":null,"abstract":"Histological analysis on stained biopsy samples requires recognizing many kinds of local and structural details, with some awareness of context. Machine learning algorithms such as convolutional networks can be powerful tools for such problems, but often there may not be enough training data to exploit them to their full potential. In this paper, we show how convolutional networks can be combined with appropriate image analysis to achieve high accuracies on three very different tasks in breast and gastric cancer grading, despite the challenge of limited training data. The three problems are to count mitotic figures in the breast, to recognize epithelial layers in the stomach, and to detect signet ring cells.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114976540","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, we exploit the synergies between Information Retrieval and E-learning by describing the design of a system that uses "Information Retrieval" in the context of the Web and "E-learning". With the exponential growth of the web, we noticed that the "general-purpose" of web applications started to diminish and more domain-specific or personal aspects started to rise, e.g., the trend of personalized web pages, a user's history of browsing and purchasing, and topical/focused search engines. The huge explosion of the amount of information on the web makes it difficult for online students to find specific information with a specific media format unless a prior analysis has been made. In this paper, we present a metadata domain-driven search engine that indexes text, powerpoint, audio, video, podcast, and vodcast lectures. These lectures are stored in a prototype "HyperManyMedia" E-learning web-based platform. Each lecture in this platform has been tagged with metadata using the domain-knowledge of these resources.
{"title":"Metadata domain-knowledge driven search engine in \"HyperManyMedia\" E-learning resources","authors":"Leyla Zhuhadar, O. Nasraoui, R. Wyatt","doi":"10.1145/1456223.1456298","DOIUrl":"https://doi.org/10.1145/1456223.1456298","url":null,"abstract":"In this paper, we exploit the synergies between Information Retrieval and E-learning by describing the design of a system that uses \"Information Retrieval\" in the context of the Web and \"E-learning\". With the exponential growth of the web, we noticed that the \"general-purpose\" of web applications started to diminish and more domain-specific or personal aspects started to rise, e.g., the trend of personalized web pages, a user's history of browsing and purchasing, and topical/focused search engines. The huge explosion of the amount of information on the web makes it difficult for online students to find specific information with a specific media format unless a prior analysis has been made. In this paper, we present a metadata domain-driven search engine that indexes text, powerpoint, audio, video, podcast, and vodcast lectures. These lectures are stored in a prototype \"HyperManyMedia\" E-learning web-based platform. Each lecture in this platform has been tagged with metadata using the domain-knowledge of these resources.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116457929","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}
Value-sensing means to feel associated with the content of one's awareness, as defined in the literature of educational psychology, as a particular dimension of human awareness. It is meaningful to extend this concept to the aspect of creativity in business. The "value" here can be dealt with as a new variable business workers create from interaction with the dynamic environment, on which they redesign the market sustainably. Data mining and data visualization can provide tools for aiding marketers'/designers' sensitivity of emerging values of consumers. This leads to the finding of essential scenarios corresponding to useful strategies for the designing and marketing of products.
{"title":"Chance discovery as value sensing by data based meta cognition","authors":"Y. Ohsawa","doi":"10.1145/1456223.1456227","DOIUrl":"https://doi.org/10.1145/1456223.1456227","url":null,"abstract":"Value-sensing means to feel associated with the content of one's awareness, as defined in the literature of educational psychology, as a particular dimension of human awareness. It is meaningful to extend this concept to the aspect of creativity in business. The \"value\" here can be dealt with as a new variable business workers create from interaction with the dynamic environment, on which they redesign the market sustainably. Data mining and data visualization can provide tools for aiding marketers'/designers' sensitivity of emerging values of consumers. This leads to the finding of essential scenarios corresponding to useful strategies for the designing and marketing of products.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127405767","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 DDoS attack is one of the existing security problems of online service. The current defense mechanism is very weak, because of the inherent TCP/IP protocol problems. This paper focuses on the overload protection mechanism for Router. We use the physical topology to do the simulation and propose the Bypass Guardian System (BGS) that can prevent the Distributed Denial of Service (DDoS) attack. This system can detect attack traffic and then redirect the traffic to the system itself. At the same time, the BGS can also monitor the traffic, filtering redirection, and proxy server.
{"title":"A novel approach in securing DDoS attack","authors":"Yi-Tung F. Chan, C. Shoniregun, G. Akmayeva","doi":"10.1145/1456223.1456240","DOIUrl":"https://doi.org/10.1145/1456223.1456240","url":null,"abstract":"The DDoS attack is one of the existing security problems of online service. The current defense mechanism is very weak, because of the inherent TCP/IP protocol problems. This paper focuses on the overload protection mechanism for Router. We use the physical topology to do the simulation and propose the Bypass Guardian System (BGS) that can prevent the Distributed Denial of Service (DDoS) attack. This system can detect attack traffic and then redirect the traffic to the system itself. At the same time, the BGS can also monitor the traffic, filtering redirection, and proxy server.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115320039","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}
I. Rodriguez, K. Guennoun, K. Drira, C. Chassot, M. Jmaiel
Architectural adaptation is important for handling self- configuring properties of autonomic distributed systems. It can be achieved by model-based management of dynamic architectures. Describing dynamic architectures includes defining rules for reconfiguration management. Within this research context, several works have been conducted using formal specification to handle this complexity. Graph and graph rewriting-based approaches showed, through many studies, their appropriateness to tackle architectural adaptation problems. However, scalability of such approaches remains an open issue and has been rarely explored. In this paper, we investigate this issue. We introduce a graph-based general approach for handling of dynamic architectures, and we illustrate it within a scenario of collaboration support in Crisis Management Systems. We elaborate the formal models for dynamic architecture management. Using the French Grid GRID5000, we conducted an experimental study to assess the scalability of the elaborated models.
{"title":"Implementing a rule-driven approach for architectural self configuration in collaborative activities using a graph rewriting formalism","authors":"I. Rodriguez, K. Guennoun, K. Drira, C. Chassot, M. Jmaiel","doi":"10.1145/1456223.1456322","DOIUrl":"https://doi.org/10.1145/1456223.1456322","url":null,"abstract":"Architectural adaptation is important for handling self- configuring properties of autonomic distributed systems. It can be achieved by model-based management of dynamic architectures. Describing dynamic architectures includes defining rules for reconfiguration management. Within this research context, several works have been conducted using formal specification to handle this complexity. Graph and graph rewriting-based approaches showed, through many studies, their appropriateness to tackle architectural adaptation problems. However, scalability of such approaches remains an open issue and has been rarely explored. In this paper, we investigate this issue. We introduce a graph-based general approach for handling of dynamic architectures, and we illustrate it within a scenario of collaboration support in Crisis Management Systems. We elaborate the formal models for dynamic architecture management. Using the French Grid GRID5000, we conducted an experimental study to assess the scalability of the elaborated models.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121683929","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 paper deals with synthesis of automatic control system for an undersea robotic vehicle. Command signals are generated by an autopilot consisting of three fuzzy controllers. A horizontal motion is regarded and the way-point line of sight scheme is incorporated to following a desired path. A method of power distribution in a multi-thruster propulsion system of the undersea robot is also presented. It concentrates on finding an optimal thrust allocation and directs towards minimisation of energy expenditures necessary to obtain required control. An illustrative example is provided to demonstrate correctness and quality of the approach.
{"title":"Fuzzy control of undersea robotic vehicle in plane motion","authors":"J. Garus","doi":"10.1145/1456223.1456234","DOIUrl":"https://doi.org/10.1145/1456223.1456234","url":null,"abstract":"The paper deals with synthesis of automatic control system for an undersea robotic vehicle. Command signals are generated by an autopilot consisting of three fuzzy controllers. A horizontal motion is regarded and the way-point line of sight scheme is incorporated to following a desired path. A method of power distribution in a multi-thruster propulsion system of the undersea robot is also presented. It concentrates on finding an optimal thrust allocation and directs towards minimisation of energy expenditures necessary to obtain required control. An illustrative example is provided to demonstrate correctness and quality of the approach.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125263733","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 most acute problem for misuse detection method is its inability to detect new kinds of attacks. A better detection method, which uses a new learning strategy, is proposed to solve this problem. A Concept Hierarchy Generation for attack Labels (CHGL) applying relevant feature subset codes clustering, makes common machine learning algorithms learn attack profiles on high concept levels. And that will enable the system detect more attack instances. Experimental results show the advantage of this new method.
{"title":"Improving performance of intrusion detection system by applying a new machine learning strategy","authors":"Tao Zou, Yimin Cui, Minhuan Huang, Cui Zhang","doi":"10.1145/1456223.1456238","DOIUrl":"https://doi.org/10.1145/1456223.1456238","url":null,"abstract":"The most acute problem for misuse detection method is its inability to detect new kinds of attacks. A better detection method, which uses a new learning strategy, is proposed to solve this problem. A Concept Hierarchy Generation for attack Labels (CHGL) applying relevant feature subset codes clustering, makes common machine learning algorithms learn attack profiles on high concept levels. And that will enable the system detect more attack instances. Experimental results show the advantage of this new method.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131523763","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：