7493579
CLARE—a Prolog database machine
The CLAuse Retrieval Engine (CLARE) is a coprocessor system which based on two-stage filtering, for handling large sets of disc resident clauses in Prolog database applications. The overall architecture and the timing measurements of the first stage CLARE hardware are reported. The timing measurements shows that the first stage CLARE hardware can perform search operations on data transferring at a rate up to 4.5 million double bytes per second.
11611476
Conceptual graphs as schemas for semi-structured databases
As the World Wide Web grows dramatically in recent years, there is increasing interest in semi-structured data on the web. Semi-structured data are usually represented in graph format, many graph schemas have then been proposed to extract schemas from those data graphs. Conceptual graphs, which use incremental conceptual clustering method to extract schemas, have initially been proposed in 2000. In this paper, we revise the original algorithm to generate a conceptual graph by proposing some new operators in the construction process. The results have shown that with the revised algorithm the quality of the conceptual graphs has been improved in terms of query optimization.
6330846
Component-based software engineering: technologies, development frameworks, and quality assurance schemes
Component-based software development approach is based on the idea to develop software systems by selecting appropriate off-the-shelf components and then to assemble them with a well-defined software architecture. Because the new software development paradigm is very different from the traditional approach, quality assurance (QA) for component-based software development is a new topic in the software engineering community. In this paper, we survey current component-based software technologies, describe their advantages and disadvantages, and discuss the features they inherit. We also address QA issues for component-based software. As a major contribution, we propose a QA model for component-based software which covers component requirement analysis, component development, component certification, component customization, and system architecture design, integration, testing and maintenance.
13250119
Resolving Conflicting Arguments under Uncertainties
Distributed knowledge based applications in open domain rely on common sense information which is bound to be uncertain and incomplete. To draw the useful conclusions from ambiguous data, one must address uncertainties and conflicts incurred in a holistic view. No integrated frameworks are viable without an in-depth analysis of conflicts incurred by uncertainties. In this paper, we give such an analysis and based on the result, propose an integrated framework. Our framework extends definite argumentation theory to model uncertainty. It supports three views over conflicting and uncertain knowledge. Thus, knowledge engineers can draw different conclusions depending on the application context (i.e. view). We also give an illustrative example on strategical decision support to show the practical usefulness of our framework.
45209699
A Workflow Model for Chinese Business Processes
This paper proposes a new workflow model (MAWM) targeted at Chinese business processing. The cultural dependent characteristics of Chinese business processes are identified and taken into account in the MAWM model. MAWM adopts a decentralized modeling style based on the conventional business perspective on labor division and cooperation. This idea is reflected in the concept of agent-workflow. Activity-based and communication-based modeling methods are integrated in the process model. They are used to model different types of business activities. In addition, the model is formalized using Process Algebra and a simplified algorithm is proposed for safety verification of workflow processes.
8841325
Information Flow Analysis with Chinese Text
This article investigates the effectiveness of an information inference mechanism on Chinese text. The information inference derives implicit associations via computation of information flow on a high dimensional conceptual space, which is approximated by a cognitively motivated lexical semantic space model, namely Hyperspace Analogue to Language (HAL). A dictionary-based Chinese word segmentation system was used to segment words. To evaluate the Chinese-based information flow model, it is applied to query expansion, in which a set of test queries are expanded automatically via information flow computations and documents are retrieved. Standard recall-precision measures are used to measure performance. Experimental results for TREC-5 Chinese queries and People Daily’s corpus suggest that the Chinese information flow model significantly increases average precision, though the increase is not as high as those achieved using English corpus. Nevertheless, there is justification to believe that the HAL-based information flow model, and in turn our psychologistic stance on the next generation of information processing systems, have a promising degree of language independence.
8168660
Towards an integrated toolset for program understanding
This paper describes some early results of a three-year project to develop an integrated toolset for program understanding. The implemented integration architecture involves both a global repository for all tools serviced by the architecture and a software bus serving communications among tools.
33091738
SHAPES: A Novel Approach for Learning Search Heuristics in Under-Constrained Optimization Problems
Although much research in machine learning has been carried out on acquiring knowledge for problem-solving in many problem domains, little effort has been focused on learning search-control knowledge for solving optimization problems. This paper reports on the development of SHAPES, a system that learns heuristic search guidance for solving optimization problems in intractable, under-constrained domains based on the Explanation-Based Learning (EBL) framework. The system embodies two new and novel approaches to machine learning. First, it makes use of explanations of varying levels of approximation as a mean for verifying heuristic-based decisions, allowing heuristic estimates to be revised and corrected during problem-solving. The provision of such a revision mechanism is particularly important when working in intractable and under-constrained domains, where heuristics tend to be highly over-generalized, and hence at times will give rise to incorrect results. Second, it employs a new linear and quadratic programming-based weight-assignment algorithm formulated to direct search toward optimal solutions under best-first search. The algorithm offers a direct method for assigning rule strengths and, in so doing, avoids the need to address the credit-assignment problem faced by other iterative weight-adjustment methods.
12653936
On Using Longuet-Higgins Equation in Pose Estimation Framework by Lowe
12936831
On designing an experiment to evaluate a reverse engineering tool
The Rigi reverse engineering system is designed to analyze and summarize the structure of large software systems. Two contrasting approaches are available for visualizing software structures in the Rigi graph editor. The first approach displays the structures through multiple, individual windows. The second approach, simple hierarchical multi-perspective (SHriMP) views, employs fisheye views of nested graphs. The paper describes the design of an experiment to evaluate these alternative user interfaces. Various results from a preliminary pilot study to test the experiment design are reported.
13225873
Model reconstruction and pose acquisition using extended Lowe's method
Finding the pose and structure of an unknown object from an image sequence has many applications in graphics, virtual reality, and multimedia processing. In this paper, we address this problem by using a two-stage iterative method. Starting from an initial guess of the structure, the first stage estimates the pose of the object. The second stage uses the estimated pose information to refine the structure. This process is repeated until the difference between the observed data and data re-projected from the estimated model is minimized. This method is a variation of the classical bundle adjustment method, but is faster in execution and is simpler to implement. We used the Kanade-Lucas-Tomasi feature tracker for obtaining the image features. Synthetic and real data have been tested with good results.