Proceedings 12th IEEE Internationals Conference on Tools with Artificial Intelligence. ICTAI 2000

15-15 Nov. 2000

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  • Proceedings 12th IEEE Internationals Conference On Tools With Artificial Intelligence

    Publication Year: 2000, Page(s):iii - ix
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    Freely Available from IEEE
  • Proceedings 12th IEEE Internationals Conference on Tools with Artificial Intelligence. ICTAI 2000

    Publication Year: 2000
    Request permission for commercial reuse | PDF file iconPDF (878 KB)
    Freely Available from IEEE
  • About the use of local consistency in solving CSPs

    Publication Year: 2000, Page(s):104 - 107
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (385 KB)

    Local consistency is often a suitable paradigm for solving constraint satisfaction problems. We show how search algorithms could be improved, thanks to a smart use of two filtering techniques (path consistency and singleton arc consistency). We propose a possible way to get benefits from using a partial form of path consistency (PC) during the search. We show how local treatment based on singleton... View full abstract»

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  • Intelligent content-based retrieval

    Publication Year: 2000, Page(s):262 - 265
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (360 KB)

    This paper deals with the challenge of extending classical image retrieval by including visual rules. The visual rules are extracted automatically from classes of images. They contribute to making the retrieval process more accurate. The visual-rules extraction is based on symbolic representations of image descriptors. The symbolic representations are the results of color and texture clustering. View full abstract»

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  • Author index

    Publication Year: 2000, Page(s):426 - 427
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    Freely Available from IEEE
  • GA Tree: genetically evolved decision trees

    Publication Year: 2000, Page(s):203 - 206
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (332 KB)

    We use genetic algorithms to evolve classification decision trees. The performance of the system is measured on a set of standard discretized concept learning problems and compared (very favorably) with the performance of two known algorithms (C4.5, OneR) View full abstract»

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  • An assumptive logic programming methodology for parsing

    Publication Year: 2000, Page(s):11 - 18
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (508 KB)

    We show how several novel tools in logic programming for AI (namely, continuation based linear and timeless assumptions, and datalog grammars) can assist us in producing terse treatments of difficult language processing phenomena. As a proof of concept, we present a concise parser for datalog grammars (logic grammars where strings are represented with numbered word boundaries rather than as lists ... View full abstract»

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  • The probably approximately correct (PAC) population size of a genetic algorithm

    Publication Year: 2000, Page(s):199 - 202
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (284 KB)

    Probably approximately correct learning, PAC-learning, is a framework for the study of learnability and learning machines. In this framework, learning is induced through a set of examples. The size of this set is such that with probability greater than 1-δ the learning machine shows an approximately correct behavior with error no greater than ε. The authors use the PAC framework to deri... View full abstract»

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  • Multi-resolution on compressed sets of clauses

    Publication Year: 2000, Page(s):2 - 10
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (728 KB)

    The paper presents a system based on new operators for handling sets of propositional clauses represented by means of ZBDDs (zero-suppressed binary decision diagrams). The high compression power of such data structures allows efficient encodings of structured instances. A specialized operator for the distribution of sets of clauses is introduced and used for performing multi-resolution on clause s... View full abstract»

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  • A genetic algorithm-based system for generating test programs for microprocessor IP cores

    Publication Year: 2000, Page(s):195 - 198
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (316 KB)

    The current digital systems design trend is quickly moving toward a design-and-reuse paradigm. In particular, intellectual property cores are becoming widely used. Since the cores are usually provided as encrypted gate-level netlist, they raise several testability problems. The authors propose an automatic approach targeting processor cores that, by resorting to genetic algorithms, computes a test... View full abstract»

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  • Fuzzy cellular automata: from theory to applications

    Publication Year: 2000, Page(s):320 - 323
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (372 KB)

    In this paper we present a fuzzified cellular automata structure called fuzzy cellular automata. We begin our paper with a fuzzified entity called fuzzy automaton, then we present basics of cellular automata and finally we define fuzzy cellular automata. At the end we present some simulation results from the field of fire spread in homogeneous nature environment View full abstract»

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  • Using latent semantic analysis to identify similarities in source code to support program understanding

    Publication Year: 2000, Page(s):46 - 53
    Cited by:  Papers (28)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (708 KB)

    The paper describes the results of applying Latent Semantic Analysis (LSA), an advanced information retrieval method, to program source code and associated documentation. Latent semantic analysis is a corpus based statistical method for inducing and representing aspects of the meanings of words and passages (of natural language) reflective in their usage. This methodology is assessed for applicati... View full abstract»

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  • Automated reasoning on monotonic constraints

    Publication Year: 2000, Page(s):401 - 404
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (340 KB)

    We study the properties of monotonic parts of (continuous) constraints. We design a general framework to reason about them : directions can be abstracted by signs, which capture significant information on the location of solutions. We show that this formalism is appropriate to study the relative position of solution sets. Efficient algorithms are proposed to diagnose the behaviour of some consiste... View full abstract»

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  • Combining various algorithms to solve the ship berthing problem

    Publication Year: 2000, Page(s):370 - 375
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (264 KB)

    The Ship Berthing Problem (SBP) belongs to the category of NP-complete problems. In this paper we discuss the methods of representing the SBP with the use of a directed acyclic graph and the use of a acyclic list to represent valid solutions for the SBP. We then propose and investigate the performance of several variants of the randomized local search, Tabu search and genetic algorithm for solving... View full abstract»

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  • A heuristic search based factoring tool

    Publication Year: 2000, Page(s):298 - 301
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (456 KB)

    Factoring is believed to be a difficult task. Although factoring is of interest in its own right, the security of RSA cryptography, among other cryptographic systems, is dependent on the difficulty of factoring the product of large primes. We show how to cast the problem of factoring integers as a state-based search to which the techniques of AI may be applied. Using small primes as operators, goa... View full abstract»

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  • A knowledge based system: an object case approach

    Publication Year: 2000, Page(s):190 - 193
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (364 KB)

    We propose an object based system to represent domain knowledge and to store it in libraries for reuse, following a case based paradigm. Our tool is generic enough to model any problem which requires a legal qualification. This kind of problem requires cooperation between several knowledge domains (e.g., medical practice and legal evaluation). The proposed case model captures the necessary expert'... View full abstract»

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  • Parallel mining of association rules with a Hopfield type neural network

    Publication Year: 2000, Page(s):90 - 93
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (312 KB)

    Association rule mining (ARM) is one of the data mining problems receiving a great deal of attention in the database community. The main computation step in an ARM algorithm is frequent itemset discovery. In this paper, a frequent itemset discovery algorithm based on the Hopfield model is presented View full abstract»

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  • Reverse mapping of referral links from storage hierarchy for Web documents

    Publication Year: 2000, Page(s):216 - 219
    Cited by:  Patents (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (328 KB)

    Due to the lack of back-pointers, information about the referral parent(s) of a given Web page is not usually available to Web surfers. This significantly reduces the effectiveness of Web surfing and information discovery. We propose a mechanism to locate the referral parent(s) for a given fragment of a Web document (in terms of an URL address) from the client side. The basic idea is to explore th... View full abstract»

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  • A visualization tool for interactive learning of large decision trees

    Publication Year: 2000, Page(s):28 - 35
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (916 KB)

    Decision tree induction is certainly among the most applicable learning techniques due to its power and simplicity. However learning decision trees from large datasets, particularly in data mining, is quite different from learning from small or moderately sized datasets. When learning from large datasets, decision tree induction programs often produce very large trees. How to efficiently visualize... View full abstract»

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  • Consistency checking for Euclidean spatial constraints: a dimension graph approach

    Publication Year: 2000, Page(s):333 - 342
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (776 KB)

    In this paper, we address the problem of consistency checking for Euclidean spatial constraints. A dimension graph representation is proposed to maintain the Euclidean spatial constraints among objects. The basic idea is to project the spatial constraints on both X and Y dimensions, and to construct a dimension graph on each dimension. Using a dimension graph representation transforms the problem ... View full abstract»

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  • History checking of temporal fuzzy logic formulas for monitoring behavior-based mobile robots

    Publication Year: 2000, Page(s):312 - 319
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (652 KB)

    Behavior-based robot control systems have shown remarkable success for controlling robots evolving in real world environments. However, they can fail in different manners due to their distributed control and their local decision making. In this case, monitoring can be used to detect failures and help to recover from them. In this work, we present an approach for specifying monitoring knowledge and... View full abstract»

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  • Knowledge pruning in decision trees

    Publication Year: 2000, Page(s):40 - 43
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (320 KB)

    We propose a novel pruning method of decision trees based on domain knowledge, semantic hierarchies among classes, which is used to generate decision trees by relaxing the levels of hierarchies for both height and width of the trees. We develop the algorithm, and the effectiveness is examined by UCI Machine Learning Repository: On Car Evaluation and Nursery. We can generate the decision trees cons... View full abstract»

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  • DGPS/INS integration using neural network methodology

    Publication Year: 2000, Page(s):114 - 121
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (392 KB)

    This paper presents an INS/DGPS land vehicle navigation system using a neural network methodology. The network setup is developed based on a mathematical model to avoid excessive training. The proposed method uses a KF-based backpropagation training rule, which achieves the optimal training criterion. The North and East travel distances are used as desired targets to train the two decoupled neural... View full abstract»

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  • An approach to incremental SVM learning algorithm

    Publication Year: 2000, Page(s):268 - 273
    Cited by:  Papers (9)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (384 KB)

    The classification algorithm that is based on a support vector machine (SVM) is now attracting more attention, due to its perfect theoretical properties and good empirical results. In this paper, we first analyze the properties of the support vector (SV) set thoroughly, then introduce a new learning method, which extends the SVM classification algorithm to the incremental learning area. The theore... View full abstract»

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  • Using Bayesian classifier in relevant feedback of image retrieval

    Publication Year: 2000, Page(s):258 - 261
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (380 KB)

    Relevance feedback is a powerful technique in content-based image retrieval (CBIR) and has been an active research area for the past few years. In this paper, we propose a new relevance feedback approach based on a Bayesian classifier, and it treats positive and negative feedback examples with different strategies. For positive examples, a Bayesian classifier is used to determine the distribution ... View full abstract»

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