27445105
Minimal cover-automata for finite languages
Abstract A cover-automaton A of a finite language L⊆Σ ∗ is a finite deterministic automaton (DFA) that accepts all words in L and possibly other words that are longer than any word in L . A minimal deterministic finite cover automaton (DFCA) of a finite language L usually has a smaller size than a minimal DFA that accept L . Thus, cover automata can be used to reduce the size of the representations of finite languages in practice. In this paper, we describe an efficient algorithm that, for a given DFA accepting a finite language, constructs a minimal deterministic finite cover-automaton of the language. We also give algorithms for the boolean operations on deterministic cover automata, i.e., on the finite languages they represent.
14075162
Synchronization Expressions: Characterization Results and Implementation
Synchronization expressions are defined as restricted regular expressions that specify synchronization constraints between parallel processes and their semantics is defined using the synchronization languages. In this paper we survey results on synchronization languages, in particular, various approaches to obtain a characterization of this language family using closure under a set of rewriting rules. Also, we discuss the use and implementation of synchronization expressions in a programming language designed for a parallel or distributed computing environment.
206058077
Synchronization Expressions with Extended Join Operation
Synchronization expressions are high level constructs used for specifying minimal synchronization constraints of parallel processes. Their semantics is defined by the corresponding synchronization language. The original definition of synchronization expressions [12, 13] forces the languages to be closed under rewriting rules that, for instance, do not preserve regularity. Here we propose an extension of the syntactic definition of synchronization expressions, and an appropriate modification of their semantics. The extended definition has the advantage that it allows us to eliminate the less well motivated transformations (rewriting rules) describing properties of synchronization languages. We show that the modified rewriting rules preserve regularity of the languages. Also, we obtain a characterization of finite synchronization languages as the family consisting of languages satisfying the start-termination property and closed under three types of simple rewriting rules.
10375023
A Pumping Lemma for Deterministic Context-Free Languages
Abstract In this paper, we introduce a new pumping lemma and a new iteration theorem for deterministic context-free languages (DCFLs). As application of the lemma, several languages are shown not to be deterministic context-free by using this lemma. An iteration theorem for DCFLs has already been introduced by Harrison in [3]. However, the result presented in this paper is different from his. Instead of considering the pumping property of individual words, we consider the pumping property of pairs of words. The latter approach seems more natural to the DCFLs (LR(1) languages). The pumping lemma introduced in this paper also appears to be easier to understand and use. We conjecture that there exist languages that can be shown not to be DCFLs by this new result but cannot be shown by the existing one. In Section 1, we introduce the basic notations used in this paper. In Section 2, we state our pumping lemma (without a proof) and show two applications of the lemma. In Section 3, a left-part theorem for LR ( k ) grammars is introduced, which is crucial to the proof of the pumping lemma and interesting on its own right. In the last section, we prove the lemma and extend it to an iteration theorem.
5352244
Minimal Cover-Automata for Finite Languages
A cover-automaton A of a finite language L ⊆ Σ * is a finite automaton that accepts all words in L and possibly other words that are longer than any word in L. A minimal deterministic cover automaton of a finite language L usually has a smaller size than a minimal DFA that accept L. Thus, cover automata can be used to reduce the size of the representations of finite languages in practice. In this paper, we describe an efficient algorithm that, for a given DFA accepting a finite language, constructs a minimal deterministic finite cover- automaton of the language. We also give algorithms for the boolean operations on deterministic cover automata, i.e., on the finite languages they represent.
10900126
Measures of Nondeterminism for Pushdown Automata
D. Vermeir and W. Savitch (Fund. Inform.4 (1981), 401-418) introduced two measures of nondeterminism for pushdown automata and showed interestingly that the second measure, which we refer to as the depth measure, yields an infinite hierarchy of language families between the deterministic context-free and general context-free languages. However, the proof given in op. cit. for this hierarchy theorem was incorrect. In this paper, using a pumping result for deterministic context-free languages we give a new proof for the strictness of the depth hierarchy. We introduce the monadic depth measure which is also shown to give rise to an infinite hierarchy of language families. Furthermore, we show that the monadic hierarchy is shifted by at most one level from the unrestricted depth hierarchy.
13007604
Extracting Content Structure for Web Pages Based on Visual Representation
A new web content structure based on visual representation is proposed in this paper. Many web applications such as information retrieval, information extraction and automatic page adaptation can benefit from this structure. This paper presents an automatic top-down, tag-tree independent approach to detect web content structure. It simulates how a user understands web layout structure based on his visual perception. Comparing to other existing techniques, our approach is independent to underlying documentation representation such as HTML and works well even when the HTML structure is far different from layout structure. Experiments show satisfactory results.
14253919
Object-Specific Figure-Ground Segregation
We consider the problem of segmenting an image into foreground and background, with foreground containing solely objects of interest known a priori. We propose an integration model that incorporates both edge detection and object part detection results. It consists of two parallel processes: low-level pixel grouping and high-level patch grouping. We seek a solution that optimizes a joint grouping criterion in a reduced space enforced by grouping correspondence between pixels and patches. Using spectral graph partitioning, we show that a near global optimum can be found by solving a constrained eigenvalue problem. We report promising experimental results on a dataset of 15 objects under clutter and occlusion.
8514244
A nonparametric hierarchical bayesian framework for information filtering
Information filtering has made considerable progress in recent years. The predominant approaches are content-based methods and collaborative methods. Researchers have largely concentrated on either of the two approaches since a principled unifying framework is still lacking. This paper suggests that both approaches can be combined under a hierarchical Bayesian framework. Individual content-based user profiles are generated and collaboration between various user models is achieved via a common learned prior distribution. However, it turns out that a parametric distribution (e.g. Gaussian) is too restrictive to describe such a common learned prior distribution. We thus introduce a nonparametric common prior, which is a sample generated from a Dirichlet process which assumes the role of a hyper prior. We describe effective means to learn this nonparametric distribution, and apply it to learn users' information needs. The resultant algorithm is simple and understandable, and offers a principled solution to combine content-based filtering and collaborative filtering. Within our framework, we are now able to interpret various existing techniques from a unifying point of view. Finally we demonstrate the empirical success of the proposed information filtering methods.
14436503
Implementing a Model Checker for LEGO
Interactive theorem proving provides a general approach to modelling and verification of both hardware and software systems but requires significant human efforts to deal with many tedious proofs. To be effectively used in practice, we need some automatic tools such as model checkers to deal with those tedious proofs. In this paper, we formalise a verification system of both CCS and an imperative language in the proof development system LEGO which can be used to verify both finite and infinite problems. Then a model checker, LegoMC, is implemented to generate LEGO proof terms for finite-state problems automatically. Therefore people can use LEGO to verify a general problem with some of its finite sub-problems verified by LegoMC. On the other hand, this integration extends the power of model checking to verify more complicated and infinite models as well.
38593151
Performance Comparison of a Deterministic and a Stochastic Method for Image Classification
In this paper, we compare the performances of two methods that we proposed for image classification. The first method is a stochastic approach which uses a Markov random field modelization. An optimization technique based on the game theory is used for the maximization of the a posteriori probability of the classes. The second method is a deterministic one which uses a feed-forward neural network. A novel learning method called projection learning is employed to train the neural network. The performances of these two methods are compared through their applications to image classification. The advantages and disadvantages of both methods, as well as possibilities to improve them are discussed.