31629768
Belief revision and possibilistic logic for adaptive information filtering agents
Prototypes of adaptive information agents have been developed to alleviate the problem of information overload on the Internet. However, the explanatory power and the learning autonomy of these agents are weak. A logic based framework for the development of information agents is appealing since semantic relationships among information objects can be captured and reasoned about. This sheds light on better explanatory power and higher learning autonomy of information agents. The paper illustrates how the AGM belief revision and possibilistic logic can be applied to develop the learning and the filtering components of adaptive information filtering agents. Their impact on the agents' learning autonomy and explanatory power is also discussed.
16840924
Improving Transliteration with Precise Alignment of Phoneme Chunks and Using Contextual Features
Automatic transliteration of foreign names is basically regarded as a diminutive clone of the machine translation (MT) problem. It thus follows IBM's conventional MT models under the source-channel framework. Nonetheless, some parameters of this model dealing with zero-fertility words in the target sequences, can negatively impact transliteration effectiveness because of the inevitable inverted conditional probability estimation. Instead of source-channel, this paper presents a direct probabilistic transliteration model using contextual features of phonemes with a tailored alignment scheme for phoneme chunks. Experiments demonstrate superior performance over the source-channel for the task of English-Chinese transliteration.
690242
Improving Quality of Email Categorization with Tournament Methods
The tournament text classification methods are proposed in this article to perform the task of email categorization, in which the essence is to break down the multi-class categorization process into a set of binary classification tasks. We implement the methods of elimination and Round Robin tournament to classify emails within 15 folders. Substantial experiments are conducted to compare the effectiveness and robustness of the tournament methods against the n-way classification method and the voting method. The experimental results show that the tournament methods outperform the n-way method by 11.7% and the voting method by 4.1% regarding precision, and the Round Robin performs slightly better than the Elimination tournament on average.
37472111
Extending the superimposed codeword indexing scheme to handle incomplete information
In order to use Prolog as a basis for database applications, techniques are required for rapid retrieval of clauses from large data sets. Various researchers have contributed to the development of indexing strategies for this purpose. One such strategy is known as superimposed codeword+mask bits (SCW+MB). One extension of Prolog which is useful in the development of deductive databases is the ability to handle incomplete information. A form of incomplete information based on sets has been introduced and used in a deductive database system. In order to provide efficient access to clauses containing incomplete information, existing strategies need to be adapted accordingly. This paper presents an extension to the SCW+MB algorithm to cover incomplete information, and describes how this can be realized in hardware.
12876616
A Design of Temporal Event Extraction from Chinese Financial News
This paper presents an information system for Chinese Information Extraction from Financial news (CHIEF). The ultimate target of the system is to extract information concerning the occurrence time and places of the financial activities in the different companies from a local Hong Kong newspaper, namely (Tao Kung Pao). To facilitate event extraction purpose, two groups of templates were defined, i.e. the company related and company restructuring templates. They are used to select the desired information for each type of financial activities, such as (bankruptcy) or (merge). Each specific event is then represented using a frame-based knowledge structure. Two types of slots are embedded in each frame: they are the activity- and time-related slots. Based on these slots, multiple activities are interconnected according to their entity relations, temporal relations or the deduced relations. Effectively, CHIEF is a question-answering system designed for handling the company related queries, event based queries, temporal queries and complex queries in a finance domain.
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.
13460900
Reconstruction of sculpture from its profiles with unknown camera positions
Profiles of a sculpture provide rich information about its geometry, and can be used for shape recovery under known camera motion. By exploiting correspondences induced by epipolar tangents on the profiles, a successful solution to motion estimation from profiles has been developed in the special case of circular motion. The main drawbacks of using circular motion alone, namely the difficulty in adding new views and part of the object always being invisible, can be overcome by incorporating arbitrary general views of the object and registering its new profiles with the set of profiles resulting from the circular motion. We describe a complete and practical system for producing a three-dimensional (3D) model from uncalibrated images of an arbitrary object using its profiles alone. Experimental results on various objects are presented, demonstrating the quality of the reconstructions using the estimated motion.
11319559
On inserting program understanding technology into the software change process
Program understanding technologies can be applied effectively in the analysis phase of a software change process. The analysis phase naturally follows a goal driven metaprocess. Described are issues involved with inserting program understanding technology into existing practice and into such a metaprocess. The implied processes of program understanding and reverse engineering tools play an important role. These issues pose major problems for the acceptance of redocumentation tools such as Rigi, an evolvable reverse engineering tool. An example using Rigi and its analysis methodology for change impact analysis is considered.
8164588
Reconstruction and Motion Estimation from Apparent Contours under Circular Motion
In thispaperweaddresstheproblemof recoveringstructureandmotionfrom thecontoursof a smooth-curvedsurface.A novel andsimplertechniquefor computingthestructureof anobjectfrom its profilesis introduced.Experimentswith real datashow encouragingresults,which are comparableto thoseobtainedfrom muchmore sophisticatedtechniques.Furthermore,a new methodfor motion estimationfrom sequencesof profilesis proposed. Preliminaryresultsdemonstratethefeasibilityof thealgorithm.
19534046
Animating the Evolution Process of Genetic Algorithms
This paper reports the work on the development of an animation system for visualising the optimisation process of the Genetic Algorithm. The description on the requirements and structure of the system is presented. The developed system is applied to visualise some six testing cases. Sequences of animation shots of the evolution process for solving the Branin RCOS problem and the Schaffer-6 problem are presented. In the latter example, the effect of a solution acceleration technique is also demonstrated. The method of building the visualisation system can be applied to other evolutionary computation techniques.
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.