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17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)最新文献

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Car license plate recognition through Hausdorff distance technique 基于豪斯多夫距离技术的汽车车牌识别
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.46
Ratree Juntanasub, N. Sureerattanan
{"title":"Car license plate recognition through Hausdorff distance technique","authors":"Ratree Juntanasub, N. Sureerattanan","doi":"10.1109/ICTAI.2005.46","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.46","url":null,"abstract":"Many researches have been done on car license plate (CLP) recognition. However, these are no sufficient number of works on Thai CLP. The existing works on Thai CLP have been focused on localization, extraction, and partial recognition (only for upper line) of the license plate. Generally, Thai CLP has 2 lines (upper and lower). The upper line presents character category in 2-position formatted, following by running number (up to 4 digits). The lower line presents province name. Recognition of the lower line is a difficult task because Thai words can be composed of 4 levels (top level, above level, base line and below level). Hence, appearance of noises in the original image easily causes misrecognition. This paper presents an approach to recognize off-line entire Thai CLP using Hausdorff distance technique (HD) for similarity measurement. The recognition rate obtained by the proposed method is 92%","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125870262","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}
引用次数: 34
Prudent semantics for argumentation frameworks 论证框架的谨慎语义
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.103
S. Coste-Marquis, C. Devred, P. Marquis
{"title":"Prudent semantics for argumentation frameworks","authors":"S. Coste-Marquis, C. Devred, P. Marquis","doi":"10.1109/ICTAI.2005.103","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.103","url":null,"abstract":"We present new prudent semantics within Dung's theory of argumentation. Under such prudent semantics, two arguments cannot belong to the same extension whenever one of them attacks indirectly the other one. We argue that our semantics lead to a better handling of controversial arguments than Dung's ones. We compare the prudent inference relations induced by our semantics w.r.t. cautiousness; we also compare them with the inference relations induced by Dung's semantics","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124947335","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}
引用次数: 86
Cooperative scheduling among time-bounded agents 限时agent间的协同调度
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.53
H. Belleili, M. Bouzid, M. Sellami
{"title":"Cooperative scheduling among time-bounded agents","authors":"H. Belleili, M. Bouzid, M. Sellami","doi":"10.1109/ICTAI.2005.53","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.53","url":null,"abstract":"This paper defines a coordination process allowing hierarchical agents equipped with multiple methods to treat efficiently arriving tasks. The aim is to find an optimal (i.e. maximizing the utility of the result) combination of methods within the time window specified by the task. Agents are resource-limited and operate under time constraints. Agents (with their chosen methods) are used in sequential levels to progressively improve the quality of a task response","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127331444","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}
引用次数: 1
Network routing based on reinforcement learning in dynamically changing networks 动态变化网络中基于强化学习的网络路由
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.91
Sara Khodayari, M. Yazdanpanah
{"title":"Network routing based on reinforcement learning in dynamically changing networks","authors":"Sara Khodayari, M. Yazdanpanah","doi":"10.1109/ICTAI.2005.91","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.91","url":null,"abstract":"In this paper we propose a reinforcement learning (RL) algorithm for packet routing in computer networks with emphasis on different traffic conditions. It is shown that routing with an RL approach, considering the traffic, can result in shorter delivery time and less congestion. A simple, but rational simulation of a computer network has also been tested and the suggested algorithm has been compared with other conventional ones. At the end, it is concluded that the suggested algorithm can perform packet routing efficiently with advantage of considering the dynamics in a real network","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127617630","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}
引用次数: 16
A Convergence Proof for the Population Based Incremental Learning Algorithm 基于种群的增量学习算法的收敛性证明
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.6
R. Rastegar, A. Hariri, M. Mazoochi
{"title":"A Convergence Proof for the Population Based Incremental Learning Algorithm","authors":"R. Rastegar, A. Hariri, M. Mazoochi","doi":"10.1109/ICTAI.2005.6","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.6","url":null,"abstract":"Here we propose a convergence proof for the population based incremental learning (PBIL). In our approach, first, we model the PBIL by the Markov process and approximate its behavior using Ordinary Differential Equation (ODE). Then we prove that the corresponding ODE doesn’t have any stable stationary points in [0,1]n, n is the number of variables, except the local maxima of the function to be optimized. Finally we show that this ODE and consequently the PBIL converge to one of these stable attractors.","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124458522","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}
引用次数: 12
A qualitative treatment of spatial data 空间数据的定性处理
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1142/S0218213007003497
Kazuko Takahashi, Takao Sumitomo
{"title":"A qualitative treatment of spatial data","authors":"Kazuko Takahashi, Takao Sumitomo","doi":"10.1142/S0218213007003497","DOIUrl":"https://doi.org/10.1142/S0218213007003497","url":null,"abstract":"This paper aims at an efficient treatment of spatial data by qualitative representation. We propose a new framework called PLCA, which provides a symbolic representation for the figure in two-dimensional plane, that focuses on the connections between regions. It is based on the simple objects: points(P), lines(L), circuit s(C) and areas(A). The entire figure is represented as a combination of these objects. Pairs of areas, circuits or lines never cross. The simple, clear data structure based on objects makes the system easy to implement and feasible. For a figure that consists of a set of regions in two-dimensional plane, there exists a corresponding consistent PLCA expression. For a consistent PLCA expression, there is a unique figure in two-dimensional plane in the sense of connection pattern, if there exists. Topological reasoning can be performed on a PLCA expression, such as judging the connection patterns of areas. We define the operations of area integration and area division on a PLCA expression. These operations preserve the consistency of the expression, and they correspond to the real actions on figures. We can add attributes to each object, such as the properties that hold on an area or that an object stands for, and make an attributed PLCA. The operations of area integration/division on an attributed PLCA corresponds to the alteration of the classification level of objects. Semantic spatial reasoning can be performed on an attributed PLCA","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"24 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115199099","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}
引用次数: 8
Immune clone algorithm for mining association rules on dynamic databases 动态数据库关联规则挖掘的免疫克隆算法
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.75
Hongwei Mo, Lifang Xu
{"title":"Immune clone algorithm for mining association rules on dynamic databases","authors":"Hongwei Mo, Lifang Xu","doi":"10.1109/ICTAI.2005.75","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.75","url":null,"abstract":"The paper seeks to generate large itemsets in a dynamic transaction database using immune clone algorithm. Intra transactions, inter transactions and distributed transactions are considered for mining association rules. The time of complexity of DMARICA (dynamic mining of association rules using immune clone algorithm) is analyzed, with fast updata (FUP) algorithm for intra transactions and e-apriori for inter transactions. The problem of mining association rules in the distributed environment is explored by distributed DMARICA (DDMARICA). The study shows that DMARICA outperforms both FUP and e-apriori in terms of execution time and scalability, without comprising the quality or completeness of rules generated. DMARICA is also compared with DMARG(dynamic mining of association rules using genetic algorithm). And it has better performance than that of DMARG","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128913090","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}
引用次数: 7
Web prediction using online support vector machine 基于在线支持向量机的网页预测
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.128
Zhili Zhang, Changgeng Guo, Shu Yu, Deyu Qi, Songqian Long
{"title":"Web prediction using online support vector machine","authors":"Zhili Zhang, Changgeng Guo, Shu Yu, Deyu Qi, Songqian Long","doi":"10.1109/ICTAI.2005.128","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.128","url":null,"abstract":"In this paper, a SVM-based online learning algorithm is proposed and applied to the problem of Web prediction. A method to construct an online LS-SVM multi-class learning model has been presented. This method is able to capture the inherent sequentiality of Web visits and successfully predict the future accesses. The experimental results show the effective performance of our method","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128596915","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}
引用次数: 11
A new temporal CSP framework handling composite variables and activity constraints 一个新的时态CSP框架处理复合变量和活动约束
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.14
Malek Mouhoub, Amrudee Sukpan
{"title":"A new temporal CSP framework handling composite variables and activity constraints","authors":"Malek Mouhoub, Amrudee Sukpan","doi":"10.1109/ICTAI.2005.14","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.14","url":null,"abstract":"A well known approach to managing the numeric and the symbolic aspects of time is to view them as constraint satisfaction problems (CSPs). Our aim is to extend the temporal CSP formalism in order to include activity constraints and composite variables. Indeed, in many real life applications the set of variables involved by the temporal constraint problem to solve is not known in advance. More precisely, while some temporal variables (called events) are available in the initial problem, others are added dynamically to the problem during the resolution process via activity constraints and composite variables. Activity constraints allow some variables to be activated (added to the problem) when activity conditions are true. Composite variables are defined on finite domains of events. We propose in this paper two methods based respectively on constraint propagation and stochastic local search (SLS) for solving temporal constraint problems with activity constraints and composite variables. We call these problems conditional and composite temporal constraint satisfaction problems (CCTCSPs). Experimental study we conducted on randomly generated CCTCSPs demonstrates the efficiency of our exact method based on constraint propagation in the case of middle constrained and over constrained problems while the SLS based method is the technique of choice for under constrained problems and also in case we want to trade search time for the quality of the solution returned (number of solved constraints)","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130282925","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}
引用次数: 14
Adaptive spam filtering using dynamic feature space 使用动态特征空间的自适应垃圾邮件过滤
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.28
Yan Zhou, M. Mulekar, Praveen Nerellapalli
{"title":"Adaptive spam filtering using dynamic feature space","authors":"Yan Zhou, M. Mulekar, Praveen Nerellapalli","doi":"10.1109/ICTAI.2005.28","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.28","url":null,"abstract":"Unsolicited bulk e-mail, also known as spam, has been an increasing problem for the e-mail society. This paper presents a new spam filtering strategy that 1) uses a practical entropy coding technique, Huffman coding, to dynamically encode the feature space of e-mail collections over time and, 2) applies an online algorithm to adaptively enhance the learned spam concept as new e-mail data becomes available. The contributions of this work include a highly efficient spam filtering algorithm in which the input space is radically reduced to a single-dimension input vector, and an adaptive learning technique that is robust to vocabulary change, concept drifting and skewed data distribution. We compare our technique to several existing off-line learning techniques including support vector machine, naive Bayes, k-nearest neighbor, C4.5 decision tree, RBFNetwork, boosted decision tree and stacking, and demonstrate the effectiveness of our technique by presenting the experimental results on the e-mail data that is publicly available","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128089301","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}
引用次数: 28
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