基于概念扩充的中文文本过滤模型

1 前言今天,以因特网为主体的信息高速公路仍在不断普及和发展,因特网上蕴涵的海量信息远远超过人们的想象,面对这样的信息汪洋大海,人们往往感到束手无策,无所适从,出现所谓的“信息过载”问题。如何帮助人们有效地选择和利用所感兴趣的信息,同时保证人们在信息选择方面的个人隐私权利?这已成为学术界和企业界所十分关注的焦点。因此,信息过滤技术应     

基于连通域的模板匹配法用于字符识别的算法研究

文章介绍了一种用于字符识别的基于连通域的模板匹配算法.该算法是在传统的模板匹配法的基础上,运用了重心重叠等处理方法,并且对字符块进行连通域处理后再实施匹配,最后利用最大相似法得出识别结果.该算法在光学仪器读数图象的动态识别中取得了良好的识别效果.     

简单模式的一种匹配方法

模式匹配是包括LFC在内的大多数函数式语言都具有的特点。文章在LFC语言现有的模式匹配实现方法的基础上,结合常用的模式匹配树的构造思想,设计了一种模式匹配方法。这种模式匹配方法通过计算给定模式集合的扩展集合来构造模式匹配树。虽然在最坏情况下,该方法与LFC现有实现的空间复杂度一样,但当函数定义是部分构造式,而定义中的非项模式覆盖了较多项时,这种模式匹配方法可以避免LFC语言现有实现中较大的编码空间。这个方法略作修改即可用于复杂的嵌套模式,是一种通用的模式匹配方法。     

基于工程特征类的预算工程量自适应提取方法研究

提出一种基于施工图的建筑CAD与预算编制集成方法,通过对施工图逻辑结构和反映预算工程量的各类图形信息特点进行分析,提出了工程特征类信息的概念,采用模板和模式识别技术实现了多层构造类预算工程量的自动提取和定额自动套取,并在基于通用设计平台的概预算一体化系统中得到应用。     

A survey of approaches to automatic schema matching

Schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing, and semantic query processing. In current implementations, schema matching is typically performed manually, which has significant limitations. On the other hand, previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains. We present a taxonomy that covers many of these existing approaches, and we describe the approaches in some detail. In particular, we distinguish between schema-level and instance-level, element-level and structure-level, and language-based and constraint-based matchers. Based on our classification we review some previous match implementations thereby indicating which part of the solution space they cover. We intend our taxonomy and review of past work to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component. Received: 5 February 2001 / Accepted: 6 September 2001 Published online: 21 November 2001     

Parametric Sequence Alignment with Constraints

Approximate matching techniques based on string alignment are important tools for investigating similarities between strings, such as those representing DNA and protein sequences. We propose a constraint based approach for parametric sequence alignment which allows for more general string alignment queries where the alignment cost can itself be parameterized as a query with some initial constraints. Thus, the costs need not be fixed in a parametric alignment query unlike the case in normal alignment. The basic dynamic programming string edit distance algorithm is generalized to a naive algorithm which uses inequalities to represent the alignment score. The naive algorithm is rather costly and the remainder of the paper develops an improvement which prunes alternatives where it can and approximates the alternatives otherwise. This reduces the number of inequalities significantly and strengthens the constraint representation with equalities. We present some preliminary results using parametric alignment on some general alignment queries.     

Designing Agent-Based Electronic Employment Markets

Two modes of matching people with jobs prevail at present: 1) hierarchical planning and 2) distributed markets. Each has strengths and limitations, but few systems have been designed to take advantage of strengths corresponding to both. With evolving information technology, however, the job-matching process could be accomplished far more equitably and efficiently using web-based markets within the firm, and intelligent agents offer excellent potential to help both potential employees and employers find one another in a distributed, electronic marketplace. But realizing this potential goes well beyond simply changing the rules of internal job matching or making agent technology available to job searchers. Rather, the corresponding markets and technologies must be designed, together, to mutually accomplish the desired results (e.g., efficient and effective matching) and conform to necessary properties (e.g., market clearing). Through the research described in this paper, we draw from Game Theory results to assess the feasibility of using two-sided matching algorithms to address this market-design problem. We also draw from current agent research to address the information technology dimension of the problem by implementing a proof-of-concept multi-agent system to enact, automate and support the corresponding market solution. This paper integrates the key economic and technological elements required to design robust electronic employment markets. And the corresponding research provides new knowledge and insight into co-development of the requisite economic markets and agent technologies.     

Qualitative Scene Interpretation Using Planar Surfaces

Our aim is to provide an autonomous vehicle moving into an indoor environment with a visual system to perform a qualitative 3D structure reconstruction of the surrounding environment by recovering the different planar surfaces present in the observed scene.The method is based on qualitative detection of planar surfaces by using projective invariant constraints without the use of depth estimates. The goal is achieved by analyzing two images acquired by observing the scene from two different points of view. The method can be applied to both stereo images and motion images.Our method recovers planar surfaces by clustering high variance interest points whose cross ratio measurements are preserved in two different perspective projections. Once interest points are extracted from each image, the clustering process requires to grouping corresponding points by preserving the cross ratio measurements.We solve the twofold problem of finding corresponding points and grouping the coplanar ones through a global optimization approach based on matching of high relational graphs and clustering on the corresponding association graph through a relaxation labeling algorithm.Through our experimental tests, we found the method to be very fast to converge to a solution, showing how higher order interactions, instead to giving rise to a more complex problem, help to speed-up the optimization process and to reach at same time good results.     

Efficient Algorithms for Image Template and Dictionary Matching

Given a large text image and a small template image, the Template Matching Problem is that of finding every location within the text which looks like the pattern. This problem, which has received attention for low-level image processing, has been formalized by defining a distance metric between arrays of pixels and finding all subarrays of the large image which are within some threshold distance of the template. These so-called metric methods tends to be too slow for many applications, since evaluating the distance function can take too much time. We present a method for quickly eliminating most positions of the text from consideration as possible matches. The remaining candidate positions are then evaluated one by one against the template for a match. We are still guaranteed to find all matching positions, and our method gives significant speed-ups. Finally, we consider the problem of matching a dictionary of templates against a text. We present methods which are much faster than matching the templates individually against the input image.     

The Geometry and Matching of Lines and Curves Over Multiple Views

This paper describes the geometry of imaged curves in two and three views. Multi-view relationships are developed for lines, conics and non-algebraic curves. The new relationships focus on determining the plane of the curve in a projective reconstruction, and in particular using the homography induced by this plane for transfer from one image to another. It is shown that given the fundamental matrix between two views, and images of the curve in each view, then the plane of a conic may be determined up to a two fold ambiguity, but local curvature of a curve uniquely determines the plane. It is then shown that given the trifocal tensor between three views, this plane defines a homography map which may be used to transfer a conic or the curvature from two views to a third. Simple expressions are developed for the plane and homography in each case.A set of algorithms are then described for automatically matching individual line segments and curves between images. The algorithms use both photometric information and the multiple view geometric relationships. For image pairs the homography facilitates the computation of a neighbourhood cross-correlation based matching score for putative line/curve correspondences. For image triplets cross-correlation matching scores are used in conjunction with line/curve transfer based on the trifocal geometry to disambiguate matches. Algorithms are developed for both short and wide baselines. The algorithms are robust to deficiencies in the segment extraction and partial occlusion.Experimental results are given for image pairs and triplets, for varying motions between views, and for different scene types. The methods are applicable to line/curve matching in stereo and trinocular rigs, and as a starting point for line/curve matching through monocular image sequences.