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11.
Dominance-based rough set approach and knowledge reductions in incomplete ordered information system 总被引:6,自引:0,他引:6
Many methods based on the rough set to deal with incomplete information systems have been proposed in recent years. However, they are only suitable for the incomplete systems with regular attributes whose domains are not preference-ordered. This paper thus attempts to present research focusing on a complex incomplete information system—the incomplete ordered information system. In such incomplete information systems, all attributes are considered as criterions. A criterion indicates an attribute with preference-ordered domain. To conduct classification analysis in the incomplete ordered information system, the concept of similarity dominance relation is first proposed. Two types of knowledge reductions are then formed for preserving two different notions of similarity dominance relations. With introduction of the approximate distribution reduct into the incomplete ordered decision system, the judgment theorems and discernibility matrixes associated with four novel approximate distribution reducts are obtained. A numerical example is employed to substantiate the conceptual arguments. 相似文献
12.
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend
learning has led to the study of online mining of frequent itemsets (FIs). Unlike mining static databases, mining data streams
poses many new challenges. In addition to the one-scan nature, the unbounded memory requirement and the high data arrival
rate of data streams, the combinatorial explosion of itemsets exacerbates the mining task. The high complexity of the FI mining
problem hinders the application of the stream mining techniques. We recognize that a critical review of existing techniques
is needed in order to design and develop efficient mining algorithms and data structures that are able to match the processing
rate of the mining with the high arrival rate of data streams. Within a unifying set of notations and terminologies, we describe
in this paper the efforts and main techniques for mining data streams and present a comprehensive survey of a number of the
state-of-the-art algorithms on mining frequent itemsets over data streams. We classify the stream-mining techniques into two
categories based on the window model that they adopt in order to provide insights into how and why the techniques are useful.
Then, we further analyze the algorithms according to whether they are exact or approximate and, for approximate approaches, whether they are false-positive or false-negative. We also discuss various interesting issues, including the merits and limitations in existing research and substantive areas
for future research. 相似文献
13.
Given a graph with edges colored Red and Blue, we study the problem of sampling and approximately counting the number of matchings with exactly k
Red edges. We solve the problem of estimating the number of perfect matchings with exactly k
Red edges for dense graphs. We study a Markov chain on the space of all matchings of a graph that favors matchings with k
Red edges. We show that it is rapidly mixing using non-traditional canonical paths that can backtrack. We show that this chain
can be used to sample matchings in the 2-dimensional toroidal lattice of any fixed size ℓ with k
Red edges, where the horizontal edges are Red and the vertical edges are Blue.
An extended abstract appeared in J.R. Correa, A. Hevia and M.A. Kiwi (eds.) Proceedings of the 7th Latin American Theoretical Informatics Symposium, LNCS 3887, pp. 190–201, Springer, 2006.
N. Bhatnagar’s and D. Randall’s research was supported in part by NSF grants CCR-0515105 and DMS-0505505.
V.V. Vazirani’s research was supported in part by NSF grants 0311541, 0220343 and CCR-0515186.
N. Bhatnagar’s and E. Vigoda’s research was supported in part by NSF grant CCR-0455666. 相似文献
14.
Two parallel block tridiagonalization algorithms and implementations for dense real symmetric matrices are presented. Block tridiagonalization is a critical pre-processing step for the block tridiagonal divide-and-conquer algorithm for computing eigensystems and is useful for many algorithms desiring the efficiencies of block structure in matrices. For an “effectively” sparse matrix, which frequently results from applications with strong locality properties, a heuristic parallel algorithm is used to transform it into a block tridiagonal matrix such that the eigenvalue errors remain bounded by some prescribed accuracy tolerance. For a dense matrix without any usable structure, orthogonal transformations are used to reduce it to block tridiagonal form using mostly level 3 BLAS operations. Numerical experiments show that block tridiagonal structure obtained from this algorithm directly affects the computational complexity of the parallel block tridiagonal divide-and-conquer eigensolver. Reduction to block tridiagonal form provides significantly lower execution times, as well as memory traffic and communication cost, over the traditional reduction to tridiagonal form for eigensystem computations. 相似文献
15.
We describe the design, implementation and experimental evaluation of new algorithms for computing the approximate factorization of multivariate polynomials with complex coefficients that contain numerical noise. Our algorithms are based on a generalization of the differential forms introduced by W. Ruppert and S. Gao to many variables, and use singular value decomposition or structured total least squares approximation and Gauss–Newton optimization to numerically compute the approximate multivariate factors. We demonstrate on a large set of benchmark polynomials that our algorithms efficiently yield approximate factorizations within the coefficient noise even when the relative error in the input is substantial (10−3). 相似文献
16.
Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated
by proposals of approximate policy iteration schemes without value functions, which focus on policy representation using classifiers
and address policy learning as a supervised learning problem. This paper proposes variants of an improved policy iteration
scheme which addresses the core sampling problem in evaluating a policy through simulation as a multi-armed bandit machine.
The resulting algorithm offers comparable performance to the previous algorithm achieved, however, with significantly less
computational effort. An order of magnitude improvement is demonstrated experimentally in two standard reinforcement learning
domains: inverted pendulum and mountain-car. 相似文献
17.
It is foreseen that more and more music objects in symbolic format and multimedia objects, such as audio, video, or lyrics,
integrated with symbolic music representation (SMR) will be published and broadcasted via the Internet. The SMRs of the flowing songs or multimedia objects will form a
music stream. Many interesting applications based on music streams, such as interactive music tutorials, distance music education, and
similar theme searching, make the research of content-based retrieval over music streams much important. We consider multiple
queries with error tolerances over music streams and address the issue of approximate matching in this environment. We propose
a novel approach to continuously process multiple queries over the music streams for finding all the music segments that are
similar to the queries. Our approach is based on the concept of n-grams, and two mechanisms are designed to reduce the heavy
computation of approximate matching. One mechanism uses the clustering of query n-grams to prune the query n-grams that are
irrelevant to the incoming data n-gram. The other mechanism records the data n-gram that matches a query n-gram as a partial
answer and incrementally merges the partial answers of the same query. We implement a prototype system for experiments in
which songs in the MIDI format are continuously broadcasted, and the user can specify musical segments as queries to monitor
the music streams. Experiment results show the effectiveness and efficiency of the proposed approach. 相似文献
18.
We consider the semilinear heat equation with globally Lipschitz non-linearity involving gradient terms in a bounded domain of R^n. In this paper, we obtain explicit bounds of the cost of approximate controllability, i.e., of the minimal norm of a control needed to control the system approximately. The methods we used combine global Carleman estimates, the variational approach to approximate controllability and Schauder's fixed point theorem. 相似文献
19.
This paper investigates the theoretical justification of intelligent digital redesign (IDR) methods based on the approximate discrete-time models. Its main purpose is to design the digital fuzzy controller achieving the minimum norm distance between the trajectories of the approximate closed-loop systems under the analog and the digital controls. It is verified that, if there exist the digital gains such that the approximate norm distance is sufficiently small, the redesigned controller makes the trajectories of the exact closed-loop systems close, or, at least, asymptotically stabilizes the plant. 相似文献
20.
Given a sequenceA of lengthM and a regular expressionR of lengthP, an approximate regular expression pattern-matching algorithm computes the score of the optimal alignment betweenA and one of the sequencesB exactly matched byR. An alignment between sequencesA=a1a2 ... aM andB=b1b2... bN is a list of ordered pairs, (i1,j1), (i2j2), ..., (it,jtt) such that ik < ik+1 and jk < jk+1. In this case the alignmentaligns symbols aik and bjk, and leaves blocks of unaligned symbols, orgaps, between them. A scoring schemeS associates costs for each aligned symbol pair and each gap. The alignment's score is the sum of the associated costs, and an optimal alignment is one of minimal score. There are a variety of schemes for scoring alignments. In a concave gap penalty scoring schemeS={, w}, a function (a, b) gives the score of each aligned pair of symbolsa andb, and aconcave function w(k) gives the score of a gap of lengthk. A function w is concave if and only if it has the property that, for allk > 1, w(k + 1) –w(k) w(k) –w(k –1). In this paper we present an O(MP(logM + log2
P)) algorithm for approximate regular expression matching for an arbitrary and any concavew.
This work was supported in part by the National Institute of Health under Grant RO1 LM04960. 相似文献