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2011 IEEE 23rd International Conference on Tools with Artificial Intelligence最新文献

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Itemset Mining in Noisy Contexts: A Hybrid Approach 噪声环境下的项集挖掘:一种混合方法
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.14
Karima Mouhoubi, Lucas Létocart, C. Rouveirol
{"title":"Itemset Mining in Noisy Contexts: A Hybrid Approach","authors":"Karima Mouhoubi, Lucas Létocart, C. Rouveirol","doi":"10.1109/ICTAI.2011.14","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.14","url":null,"abstract":"A general task in data mining consists in finding all rectangles of 1 in a boolean matrix in which the order of the rows and columns is not important. However, most algorithms which have been developed to solve this task are unable to be adapted to real data that may contain noise. The effect of the noise is to shatter relevant item sets into a set of small irrelevant item sets, yielding an explosion in the number of resulting item sets. Recent algorithms that have been proposed to address this problem suffer from various limitations such as the large number of results, the execution time which remains very high and the inability to discover overlapping patterns. In this work, we propose a new heuristic approach based on a graph algorithm for the efficient extraction of item set patterns in noisy binary contexts. This method is based on maximal flow/minimal cut algorithms to find dense sub graphs of 1 in the graph associated to the boolean data matrix. To evaluate our approach, various experiments have been performed on both synthetic data and real datasets from bioinformatic applications. We have compared our results on various synthetic datasets and a gene-expression data with various methods and demontrate that i) our method is quite efficient ii) the patterns extracted by our algorithm have a better quality than the other methods.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133350031","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: 2
Equivalence Class Based Parity Reasoning with DPLL(XOR) 基于等价类的DPLL(XOR)奇偶推理
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.103
Tero Laitinen, Tommi A. Junttila, I. Niemelä
{"title":"Equivalence Class Based Parity Reasoning with DPLL(XOR)","authors":"Tero Laitinen, Tommi A. Junttila, I. Niemelä","doi":"10.1109/ICTAI.2011.103","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.103","url":null,"abstract":"The recently introduced DPLL (XOR) framework for deciding satisfiability of propositional formulas with parity constraints is studied. A new parity reasoning module, based on equivalence class manipulation, is developed and implementation techniques for it described. It is shown that the deduction power of the new module is equivalent to another one proposed earlier. Additional reasoning module independent techniques are presented. Different design choices and module integration strategies are experimentally evaluated on three stream ciphers Trivium, Grain, and Hitag2. The new approach achieves major runtime speedups on the Trivium cipher and significant reduction in the number of decisions on Grain and Hitag2 ciphers.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125991234","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
An Epidemic Model for News Spreading on Twitter 推特上新闻传播的流行模式
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.33
Saeed Abdullah, Xindong Wu
{"title":"An Epidemic Model for News Spreading on Twitter","authors":"Saeed Abdullah, Xindong Wu","doi":"10.1109/ICTAI.2011.33","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.33","url":null,"abstract":"In this paper, we describe a novel approach to understand and explain news spreading dynamics on Twitter by using well-known epidemic models. Our underlying hypothesis is that the information diffusion on Twitter is analogous to the spread of a disease. As mathematical epidemiology has been extensively studied, being able to express news spreading as an epidemic model enables us to use a wide range of tools and procedures which have been proven to be both analytically rich and operationally useful. To further emphasize this point, we also show how we can readily use one of such tools -- a procedure for detection of influenza epidemics, to detect change of trend dynamics on Twitter.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128770068","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: 60
Discrete Exponential Bayesian Networks: An Extension of Bayesian Networks to Discrete Natural Exponential Families 离散指数贝叶斯网络:贝叶斯网络在离散自然指数族中的推广
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.38
Aida Jarraya, Philippe Leray, A. Masmoudi
{"title":"Discrete Exponential Bayesian Networks: An Extension of Bayesian Networks to Discrete Natural Exponential Families","authors":"Aida Jarraya, Philippe Leray, A. Masmoudi","doi":"10.1109/ICTAI.2011.38","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.38","url":null,"abstract":"In this paper, we develop the notion of discrete exponential Bayesian network, parametrization of Bayesian networks (BNs) using more general discrete quadratic exponential families instead of usual multinomial ones. We then introduce a family of prior distributions which generalizes the Dirichlet prior classically used with discrete Bayesian network. We develop the posterior distribution for our discrete exponential BNs leading to bayesian estimations of the parameters of our models and one new scoring function extending the Bayesian Dirichlet score used for structure learning. These theoretical results are finally illustrated for Poisson and Negative Binomial BNs.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127950903","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: 5
Extracting Academic Information from Conference Web Pages 从会议网页中提取学术信息
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.164
Peng Wang, Yue You, Baowen Xu, Jianyu Zhao
{"title":"Extracting Academic Information from Conference Web Pages","authors":"Peng Wang, Yue You, Baowen Xu, Jianyu Zhao","doi":"10.1109/ICTAI.2011.164","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.164","url":null,"abstract":"Conference Web pages are the main platforms to share the conference information and organize conference events. To discover the academic knowledge from such Web pages for building academic ontologies or social networks, it is necessary to extract academic information from conference Web pages. This paper proposes an approach to extract academic information from conference Web pages. Firstly, Web pages are segmented into text blocks by analyzing the visual feature and DOM structure. Then Bayes Network is used to classify these text blocks into predefined categories, and the quality of initial classification results are improved after post-processing. Finally, the academic information is extracted from the classified text blocks. Our experimental results on the real world datasets show that the proposed method is highly effective and efficient for extracting academic information from conference Web pages, and it has average 90% precision and 89% recall.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"262 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129879207","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: 5
Effective XML Classification Using Content and Structural Information via Rule Learning 通过规则学习使用内容和结构信息的有效XML分类
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.24
G. Costa, R. Ortale, E. Ritacco
{"title":"Effective XML Classification Using Content and Structural Information via Rule Learning","authors":"G. Costa, R. Ortale, E. Ritacco","doi":"10.1109/ICTAI.2011.24","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.24","url":null,"abstract":"We propose a new approach to XML classification, that uses a particular rule-learning technique for the induction of interpretable classification models. These separate the individual classes of XML documents by looking at the presence within the XML documents themselves of certain features, that provide information on their content and structure. The devised approach induces classifiers with outperforming effectiveness in comparison to several established competitors.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127606477","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
Redundancy Elimination in Highly Parallel Solutions of Motion Coordination Problems 运动协调问题高度并行解的冗余消除
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1142/S0218213013600026
Pavel Surynek
{"title":"Redundancy Elimination in Highly Parallel Solutions of Motion Coordination Problems","authors":"Pavel Surynek","doi":"10.1142/S0218213013600026","DOIUrl":"https://doi.org/10.1142/S0218213013600026","url":null,"abstract":"Problems of coordinated motion of multiple entities are addressed in this paper. These problems are dealt on the abstract level where they can be viewed as a task of constructing a spatial-temporal plan for a set of identical mobile entities. The entities are moving in a certain environment and they need to reach given goal positions starting from initial ones. The most abstract formal representations of coordinated motion problems are known as \"pebble motion on a graph\" and \"multi-robot path planning\". The existent state-of-the-art algorithms for pebble motion and multi-robot problems were suspected of generating solutions containing redundancies and this hypothesis eventually confirmed. It this paper, we present several techniques for identifying and eliminating redundancies from solutions generated by these algorithms. An extensive experimental evaluation was performed and it showed that the quality of generated solutions can be improved up to the order of magnitude. We also identify parameters characterizing instances of problems where the improvement is expectable.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121181231","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
Scale Assignment for Imbalanced Points 不平衡点的尺度分配
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.37
Qi Li
{"title":"Scale Assignment for Imbalanced Points","authors":"Qi Li","doi":"10.1109/ICTAI.2011.37","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.37","url":null,"abstract":"Imbalance oriented candidate selection was introduced as an alternative of non-maximum suppression, aiming to improve the localization accuracy. To distinguish interest points detected via non-maximum suppression, we call interest points detected via imbalance oriented selection imbalanced points. Scale assignment for imbalanced points is not straightforward because of a dilemma of involving non-maximum suppression -- The scale space theory, a popular scale assignment scheme, requests non-maximum suppression to detect extreme points from scale spaces, while imbalanced points are expected to be free of non-maximum suppression in order to maintain the localization accuracy. In this paper, we propose a bypass scheme that circumvents the above dilemma by establishing an association between an imbalanced point and a certain interest point with a known scale (e.g., key points). We justify the proposed bypass scheme theoretically and experimentally. For example, our results show that epipolar geometry estimated via imbalanced points with bypass scales is more consistent with ground truth than key points.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121275234","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: 3
Weighted Constraint Satisfaction Problems with Min-Max Quantifiers 最小-最大量词的加权约束满足问题
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.121
Jimmy Ho-man Lee, Terrence W.K. Mak, Justin Yip
{"title":"Weighted Constraint Satisfaction Problems with Min-Max Quantifiers","authors":"Jimmy Ho-man Lee, Terrence W.K. Mak, Justin Yip","doi":"10.1109/ICTAI.2011.121","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.121","url":null,"abstract":"Soft constraints are functions returning costs, and are essential in modeling over-constrained and optimization problems. We are interested in tackling soft constrained problems with adversarial conditions. Aiming at generalizing the weighted and quantified constraint satisfaction frameworks, a Quantified Weighted Constraint Satisfaction Problem (QWCSP) consists of a set of finite domain variables, a set of soft constraints, and a min or max quantifier associated with each of these variables. We formally define QWCSP, and propose a complete solver which is based on alpha-beta pruning. QWCSPs are useful special cases of QCOP/QCOP+, and can be solved as a QCOP/QCOP+. Restricting our attention to only QWCSPs, we show empirically that our proposed solving techniques can better exploit problem characteristics than those developed for QCOP/QCOP+. Experimental results confirm the feasibility and efficiency of our proposals.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"308 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123236424","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: 6
Feature Filtering for Instance-Specific Algorithm Configuration 针对特定实例算法配置的特征过滤
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.132
Christian Kroer, Y. Malitsky
{"title":"Feature Filtering for Instance-Specific Algorithm Configuration","authors":"Christian Kroer, Y. Malitsky","doi":"10.1109/ICTAI.2011.132","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.132","url":null,"abstract":"Instance-Specific Algorithm Configuration (ISAC) is a novel general technique for automatically generating and tuning algorithm portfolios. The approach has been very successful in practice, but up to now it has been committed to using all the features it was provided. However, traditional feature filtering techniques are not applicable, requiring multiple computationally expensive tuning steps during the evaluation stage. To this end, we show three new evaluation functions that use precomputed runtimes of a collection of untuned solvers to quickly evaluate subsets of features. One of our proposed functions even shows how to generate such an effective collection of solvers when only one highly parameterized solver is available. Using these new functions, we show that the number of features used by ISAC can be reduced to less than a quarter of the original number while often providing significant performance gains. We present numerical results on both SAT and CP domains.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117354566","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: 22
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