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Communities of practice need the appropriate means to collaborate in order to reach decisions by exploiting all possible knowledge resources. To address this issue, we have developed a web-based platform that enables members of such communities collaborate through carrying out well-structured argumentative discourses. Our approach comprises a variety of concepts, methods, models and techniques, deriving among others from the decision making, knowledge management and argumentation fields, and properly interweaves them with the aid of an ontology model. This paper explores the interplay of the domain-independent and domain-specific concepts coming from the above fields, and comments on their embodiment in the above platform. Our multidisciplinary approach provides the foundations for developing a platform for brainstorming and capturing of the organizational knowledge in order to augment teamwork in terms of knowledge elicitation, sharing and construction, thus enhancing decision quality. [ABSTRACT FROM AUTHOR]

In multi-agent systems, communication among agents plays an important role for cooperative behavior. In this paper, we investigate the effect of direct communication in a multi-agent system, Ant System (AS). Ant agents in AS usually perform indirect communication through pheromones. We introduce the mechanism that ants communicate directly with neighboring ants so that each ant's information can be exchanged. As experimental results, the AS with direct communication acquired better solutions than conventional AS. If the ants have excessive range of direct communications, however, the search performance becomes worse. We showed that local communications are effective in order to search solutions while striking a balance between centralization and diversification of the ants' action. For the effective search, it is important to set the range of the direct communication appropriately. [ABSTRACT FROM AUTHOR]

Human-computer interaction (HCI) has fundamentally chan- ged computing. The ubiquity of HCI can be seen in several kinds of application areas, such as text editing, hypertext, gesture recognition, and the like. Since HCI is concerned with the joint performance of tasks by humans and machine, human-computer conversational interaction plays a central role when trying to bring the computer behavior closer to the human conversational behavior. In this paper we introduce our idea of modeling computer chat based on the observed "critical" behavior of the structure of human chat. [ABSTRACT FROM AUTHOR]

Each word in a language not only has its own explicit meaning, but also can convey various impressions. In this paper, we focus on the impressions people get from news articles, and propose a method for determining impressions of these news articles. Our proposed method consists of two main parts. One part involves building an "impression dictionary" that describes the relationships among words and impressions. The other part of the method involves determining impressions of input news articles using the impression dictionary. The impressions of a news article are represented as scale values in user-specified impression scales, like "sad - glad" and "angry - pleased". Each scale value is a real number between 0 and 1, and is calculated from the words (common nouns, action nouns, verbs, adjectives, and katakana characters) extracted from an input news article using the impression dictionary. [ABSTRACT FROM AUTHOR]

In our knowledge-based society, collaboration environments define a key Knowledge Management trend. The critical step in the implementation of this step is to capture the collaboration surrounding visual reports (e.g., charts) used in decision-making. Indeed, the ability to provide an accurate and integrated visualization of the data spaces in order to support organizational decision-making is a crucial component of modern information-rich enterprises. This ability can be significantly improved through the introduction of collaborative decision support tools tailored for visualization. This paper presents the development of a class of such tools, called DIVI (Distributed Intelligent Visual Interfaces). The DIVI approach is based on the application of distributed visualization nodes and a mechanism for visual information abstraction/generalization. DIVI technology is envisioned to have a major impact on those applications requiring information to be collected from different data sources for collaborative group decision-making. Typical applications include planning systems, logistics, computer-aided medical group diagnosis, and educational services. [ABSTRACT FROM AUTHOR]

The aim of this paper is to propose a Japanese morphological error measure in order to automatically detect morphological errors when analyzing. In particular, we focused on three similarities as the measure and experimented using them. From our experimental results, it was found that the precision of one of measures was 74% and it functioned well. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a system of the weather disaster prevention in specific areas where the construction of the wire communication infrastructure is hard. This would be able to minimize the damage of men because the system has easiness of materialization with the existing wireless communication network, gets economic profits and can be set up in the back region such as a remote place, island so a person with a mobile terminal can receive a warning matter of the area he is in. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) are weather systems with vast destructive power. To give early TC warnings, accurate location of their circulation centers, or "eyes", is required. The pattern matching solution to this TC eye fix problem works by analyzing individual remote sensing images as if they are independent. Temporal information is ignored in such approach and results from individual image are only smoothed afterwards. In this paper, a TC eye fix method using genetic algorithm (GA) with temporal information is proposed. This method gives an improvement of 35% in speed and 20% in accuracy compared to the one without the use of temporal information. Our proposed method can process 6 minutes of radar data in about 10 seconds on a notebook computer, meeting practical real time constraints. It gives an average accuracy within 0.107 to 0.156 degrees in latitude/longitude on the Mercator projected map, well within the relative error of about 0.3 degrees given by different TC warning centers. [ABSTRACT FROM AUTHOR]

This paper is devoted to proposing and testing a strategy for decomposing compound signals obtained in remote sensing applications through the automatic generation of cooperating ANNs that model it. Each ANN will specialize in one of the primitives that make up the whole. The evolutionary based algorithm that is proposed for this purpose implies that the combination of networks takes place at a phenotypic operational level, this is, the architecture of the networks is not the issue, but rather function they implement. This way, a population of networks that are automatically classified into different species depending on the performance of their phenotype, and individuals of each species cooperate forming a group to obtain a complex output, in this case the signal that is required. The magnitude that reflects the difference between ANNs is their affinity vector, which must be automatically created and modified depending on the actuation of the phenotype of each individual. The main objective of this approach is to model complex functions such as multidimensional signals, which are typical of remote sensing application, providing a decomposition of them into primitive functions. [ABSTRACT FROM AUTHOR]

The work presented here is mainly concerned with the development of an intelligent resource allocation method specially focused in providing maximum satisfaction to user agents tied to resource strapped applications. One of the applications of this type of strategies is that of remote sensing in terms of energy and sensor usage. Many remote sensors or sensor arrays reside on satellites and their use must be economized, while at the same time the agency managing satellite time would like to satisfy the users as much as possible. Here we have developed a cognitive based strategy that obtains models of users and resource use in real time and uses these models to obtain strategies that are compatible with management policies. The paper concentrates in obtaining the user models. [ABSTRACT FROM AUTHOR]

On the instruction level parallelism architecture developed as EPIC, VLIW structure machine et al., the perforemance is affected by the compiler techniques. The integrated and convergent optimization techniques have been studied for their developments of the parallelism. In this paper, we develop a software pipelining technique for the improvement of the parallel processing in these machine structures. The software pipelining is a loop scheduling technique by overlapping the execution of several consecutive instructions of the program. Then, much registers are needed for the realization of the software pipelining. Here, spilling code and the rematerialization are implemented in the pipelining scheduling. Experimental results of the proposed method are compared with the conventional methos. The results show the improvements of the speedup of the parallel prosecssing in the bench marks. [ABSTRACT FROM AUTHOR]

Both bare conductors and insulated covered conductors are used in overhead distribution line systems. The difference in those conductors will affect striking distances of the conductors to lightning, lightning occurrence probabilities to the conductors and shielding effects of grounding objects on direct lightning. In this research the lightning flashover characteristics and the lightning occurrence probabilities on overhead distribution lines have been studied experimentally at a reduced scale-model. The voltage applied to electrodes in the experiment has a rise time of 1.2 microseconds and a peak to half value decay time of 50 microseconds. This paper presents the experimental data, the lightning flashover characteristics and lightning occurrence probabilities of those conductors. [ABSTRACT FROM AUTHOR]

This study includes an original corpus of engineering journals and is part of the series of E-Learning & English for Specific Purposes (ESP) researches . Purposes (ESP) researches that includes an original corpus of engineering journals. In this paper the results of a corpus study will be presented, and a sample of the ESP e-learning materials being developed for graduate students in engineering will be shown. Abstracts were chosen for the corpus this time because students are likely to read many for their research, and eventually to have to produce their own. We prepare the 40,000-word corpus that consists of 263 abstracts from mechanical and electrical engineering journals. The corpus is analyzed using Wmatrix, which gives part-of-speech tags and semantic tags, and compares the results with those of the BNC written corpus sampler. Some special features found in the analysis are frequencies in semantic tags, part-of-speech tags, difference in the use of verbal forms and multi-words. As an application of the important features, we are developing web-based materials which include the original abstracts with target items hyper-linked to various pages containing exercises, concordances, grammar explanations, a bilingual dictionary, etc. [ABSTRACT FROM AUTHOR]

A purpose of text-mining is to summarise a large collection of documents. This paper proposes a new method to view a summary of large document set. It consists of two techniques, one of which constructs classification trees using a split test called the standard-example (standard-document) split test, and the other is a method to display features in each class of documents classified in the trees. The standard-example split test is a test which divides examples by their distance (or similarity) from a standard-example which is selected by a criterion. This is the first method which applies this test to text mining. The display method exhibits representative words of document classes which emphasise their feature. [ABSTRACT FROM AUTHOR]

"As long as a branch of science offers an abundance of problems, so long is it alive: a lack of problems foreshadows extinction or the cessation of independent development." - David Hilbert, 1900. "The formulation of a problem is often more essential than its solution, which may be merely a matter of mathematical or experimental skill. To raise new questions, new possibilities, to regard old problems from a new angle, requires creative imagination and marks real advance in science." - Albert Einstein, 1938. This paper presents key characteristics and/or fundamental features of autonomous evolutionary information systems, the most fundamental issues in design and implementation of autonomous evolutionary information systems, our basic ideas and approaches to address the issues, and some challenges for future research. The notion of an autonomous evolutionary information system, its actual implementation, and its practical applications concern various areas including logic, automated reasoning, software engineering, and knowledge engineering, and will raise new research problems in these areas. [ABSTRACT FROM AUTHOR]

Webcasting and recording of university lectures has become common practice. While much effort has been put into the development and improvement of formats and codecs, few scientist have studied how to improve the quality of the signal before it is digitized. Lecture halls or seminar rooms are not professional recording studios. Good quality recordings require full-time technicians to setup and monitor the signals. This paper describes a tool that eases studioless voice recording by automatizing several tasks usually handled by audio technicians. The expert system measures the quality of the sound hardware used, monitors possible hardware malfunctions, prevents common user mistakes, and provides gain control and filter mechanisms. [ABSTRACT FROM AUTHOR]

As more people get using mobile phones, smartphone which is a new generation of mobile phone with computing capability earns world-wide reputation as new personal business assistant and entertainment equipment. This paper presents a synthetic character which acts as a user assistant and an entertainer in smartphone. It collects low-level information from various information sources available in smartphone, such as personal information, call log, and user input. Collected information is used for inferring high-level information with Bayesian network and determining agent's goal. This character takes a behavior appropriate to current situation using behavior selection mechanism. The proposed agent is toward a framework for integrating reactive and deliberative behavior. [ABSTRACT FROM AUTHOR]

We present in this paper an Asian Grocery server site web application developed for Smart Clients such as Desktop, Notebook, PDA and Pocket PC. The application accesses and retrieves data from an SQL Server 2000 and displays the data in both English and Vietnamese languages. Extensive testing of Smart Clients system and its applications has been performed to gather information and analyze its advantages and inadequacies found using Openwave version 7 Emulator and Microsoft Mobile Explorer version 3. [ABSTRACT FROM AUTHOR]

To accomplish the autonomous behavior of agents, several top-down and bottom-up agent learning architectures that consist of procedural and declarative knowledge have been implemented. They use mechanisms such as production rules, supervised neural networks and unsupervised neural networks to declare procedural knowledge. An efficient representation of procedural knowledge enhances learning and decision making. Inspired by the representation of rules, facts and knowledge in human memory, this paper presents a novel cognitive memory model, Episodic Associative Memory with a Neighborhood Effect (EAMwNE) as a method to define procedural knowledge. [ABSTRACT FROM AUTHOR]

In this paper, aiming at describing interrelationships and communication mechanisms among agents based on a multi-agent framework of Railway Intelligent Transportation System (RITS), we construct the model about stations and trains in the system, which is called Agent-Oriented G-Net Train Group Operation Model (AGNTOM). The framework degrades the complexity of computation and makes the distribution of simulation system easy in design. The simulated experiments prove that the model provides an effective approach for dealing with communication problems in the system. [ABSTRACT FROM AUTHOR]

This paper proposes a new so-called "minimum risk" method, to address the local minimum problem that has to be faced for the goal-oriented robot navigation in an unknown environment. This method is theoretically proved to guarantee the global convergence even in the long-wall, large concave, recursive U-shape, unstructured, cluttered, and maze-like environments. The minimum risk method adopts a strategy of multiple behaviors coordination, in which a novel path-searching behavior is developed by fuzzy logic to recommend the regional direction with minimum risk. This behavior is one of the applications of the proposed memory grid technique. The proposed method is verified by the simulation and real world tests. [ABSTRACT FROM AUTHOR]

This paper presents a new algorithm for feature generation, which is approximately derived based on geometrical interpretation of the Fisher linear discriminant analysis. In a field of pattern recognition or signal processing, the principal component analysis (PCA) is often used for data compression and feature extraction. Furthermore, iterative learning algorithms for obtaining eigenvectors have been presented in pattern recognition and image analysis. Their effectiveness has been demonstrated on computational time and pattern recognition accuracy in many applications. However, recently the Fisher linear discriminant (FLD) analysis has been used in such a field, especially face image analysis. The drawback of FLD is a long computational time in compression of large-sized between-class and within-class covariance matrices. Usually FLD has to carry out minimization of a within-class variance. However in this case the inverse matrix of the within-class covariance matrix cannot be obtained, since data dimension is higher than the number of data and then it includes many zero eigenvalues. In order to overcome this difficulty, a new iterative feature generation method, a simple FLD is introduced and its effectiveness is demonstrated. [ABSTRACT FROM AUTHOR]

This paper proposes a method for cyclic gestures recognition of a partner robot based on computational intelligence. The mobile robot used as a partner robot must make decisions suitable to the human intention in the facing environment. Therefore, it is necessary to recognize the gesture used as a tool for human communication. The proposed method is composed of a fuzzy spiking neural network, a self-organizing map, and a steady-state genetic algorithm. Experimental results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The proportional differentiated service (PDS) model has been developed to provide a controllable, consistent, and scalable quality of service (QoS) model. The PDS model enables network operators to get a control knob for the convenient management of services and resources even in a large-scale network. In this paper, we provide an analysis of RED with multiple class-based queues for supporting PDS among different classes using M/M/1/K queueing model and is also verified how to set the main control parameter, maxp, of RED for PDS using ns-2 simulator. [ABSTRACT FROM AUTHOR]

In this paper, we aim for construction of high-speed and high-accurate system using Fast Fourier Transform (FFT) for feature extraction, Simple-PCA (SPCA) for feature compression, and a neural network (NN) for recognition. In particular, we present a novel method based on Canonical Discriminant Analysis (CDA) to improve recognition accuracy for EMG. From results of computer simulation, it is shown that our approach is effective for improvement in recognition accuracy. [ABSTRACT FROM AUTHOR]

In scenes of an outdoor environment, depth recovery by matching a pair of stereo images is not very successful due to the strong effect of noise and changing illumination. In contrast, the surface normal is relatively robust against the influence of noise or changing illumination compared to other frequently used features. In this paper, we propose a two-step approach to solve the 3-D depth recovery problem. In the first step, we use the intensity feature to execute a rough comparison. We then use the surface normal vector, which is a much more discriminating feature, as the search basis for the second step. In addition, the 3-D invariant nature of a surface normal improves the accuracy of the stereo image matching results. The maps reconstructed in our experiments on images of outdoor scenes show that our approach is indeed more efficient and accurate than conventional methods. [ABSTRACT FROM AUTHOR]

This paper presents an innovative implementation method of the broadside antenna by using adaptive array antenna. Compared with the conventional ones, its performance can be improved because it is possible to null the interfering signals adjustably and at the same time maximize the main lobe towards the array normal. Thus the optimal radiation pattern can be obtained. The conventional broadside array only can make a main lobe toward the array normal, but it can not cancel the interferences. So, it is easy to be seen for the significance of this proposed method. In many applications, it is required to have the maximum radiation of an array directed toward the array normal. An optimal radiation pattern design for an adaptive broadside array antenna is not only to derive the maximum power radiation at the array normal direction but also to suppress interference by placing nulls at the directions of the interfering sources. The signal to interference ratio (SIR) can be maximized. Memetic algorithm is used for the search of the optimal weighting of array factor of the optimal radiation pattern by amplitude-position perturbations. [ABSTRACT FROM AUTHOR]

An antenna array is often used as an adaptive antenna. In this paper, the pattern nulling of a linear array for interference cancellation is derived by phase-only perturbations using genetic algorithms. This design for radiation pattern nulling of an adaptive antenna can suppress multiple interferences by placing nulls at the directions of the interfering sources, i.e., to increase the Signal Interference Ratio (SIR). One example is provided to justify the proposed phase-only perturbations approach based on genetic algorithms. The simulation results show that optimizing interference cancellation of adaptive linear array has been achieved by phase-only perturbations using genetic algorithms. [ABSTRACT FROM AUTHOR]

The ubiquity of chance discovery can be seen in many areas of application, fundamentally when there are events that are difficult to find or predict. In this paper, we present our idea of applying a chance discovery tool, the KeyGraph, for identifying relationship of co-occurrence between the utterances of the interlocutors during a chat section. [ABSTRACT FROM AUTHOR]

The first part of the paper illustrates that at the roots of the chance discovery there is a process of disembodiment of mind that exhibits a new perspective on the cognitive mechanisms underling the emergence of scenarios productive for opportunities and risks. I will further illustrate the centrality to chance discoverability of the disembodiment of mind from the point of view of the cognitive interplay between internal and external representations. I consider this interplay critical in analyzing the relation between chance discovery and dynamical interactions with the environment. To the aim of explaining these relationships I conclude stressing the importance I attribute to the role of model-based and manipulative abduction, and of external representations and epistemic mediators. [ABSTRACT FROM AUTHOR]

Chance discovery is a research topic that emerges in recent years. To discover chances, a double helix model emphasizing human-computer interactions and a visual analysis tool named as KeyGraph have been proposed. In this paper, the mechanism of the double helix model is re-interpreted from the viewpoint of decision-making. The manipulation results of the double helix model are thus mapped to the objective space of the decision-making problem. In such a case, identifying the chance path to a "heaven" which is full of satisficing solutions becomes the key to success for the context of decision-making. A context of designing creative cell phones by using interactive genetic algorithms (IGA) has been discussed. To recognize the chance paths for IGA, an on-chance operator which evolves the individuals based on the historical data is massively used. The pilot experimental results, including satisfaction investigation, are all promising. [ABSTRACT FROM AUTHOR]

Since OFDM method uses Fast Fourier Transform(FFT) algorithm,, it can make the size of circuits smaller and also can vary transmission capacity by adaptive changing the number of subcarrier. Therefore, OFDM method may be applied as digital broadcasting and physical layer transmission mode of intelligent system. In this paper, we analyzes how a synchronization error affects receiving system when using a adaptive coded OFDM(Orthogonal Frequency Division Multiplexing) transmission method in wireless LAN channel environment in which we can efficiently transmit wide-band information data. As a result, in OFDM system, we could see that the higher a frequency offset is, the worse performance will be, and we could see that there was performance improvement by applying adaptive coding technique in OFDM system in order to reach (BER=10-3). However, when we use 64QAM(64Quadrature Amplitude Modulation), there was a huge influence between carriers by frequency offset at 0.05, 0.1. [ABSTRACT FROM AUTHOR]

In power network, low frequency oscillation become a major concern for many years. In order to depress low frequency oscillation, the power system stabilizer parameters must be adjusted when there are changes in power network conditions. This paper presents the application of neural network to tune the power network stabilizer parameters. For training neural network, generator real power and reactive power are chosen as the input signals and the output are the desired power network stabilizer parameters. A popular type of neural network, the multi-layer perceptron with error-back-propagation training method, is employed. The neural network, once trained, can yield proper power network stabilizer parameters under any generator loading conditions. Simulation results show that the neural network based power system stabilizer yield better dynamic performance than conventional power system stabilizers in the sense of having large damping in responds to a step disturbance. [ABSTRACT FROM AUTHOR]

In this paper, digital watermarking scheme that is intelligent and effective in protecting a copyright of image data under image transformation such as scaling, rotation, and JPEG lossy compression is proposed. Especially, the proposed scheme is a robust algorithm for mobile content service. It means that the proposed watermarking is robustness to protect impulse noise attacks. The watermark and inserted watermark are very different from each other. The original watermark is recomposed using the code granted to a copyrighter or customer. The proposed algorithm is an extension of spread-spectrum watermarking algorithm that obtains the convolution value of PN sequence. Correlator and decision circuit in our algorithm are required. Because just a little watermark is embedded in the original image, this decision circuit plays an important role for detecting this watermark and then the intelligent method for the decision must be required. Degradation of image quality between original image and watermarked image in order to confirm required invisibility in the digital watermarking system and watermark robustness to protect various attacks from the outside are analyzed using the value of PSNR and recovered rate of watermark image. The experimental result shows that image quality is less degraded as the PSNR of 93.75 dB. It is also observed that excellent watermark detection is achieved under an image transformation and JPEG lossy compression, and watermark can be effectively detected in case of the image inserted impulse noise, which PSNR is 7.97 dB. [ABSTRACT FROM AUTHOR]

In this paper, we propose reliability and capacity enhancement algorithms for high data rate wireless personal area network (HDR-WPAN) system using an intelligent coordination scheme. Conventional system (i.e., IEEE802.15.3, HDR-WPAN) supports maximum 55Mbps transmission rate at 15MHz bandwidth. Proposed intelligent coordination scheme is a modification of HDR-WPAN specification to enhance the reliability and transmission rate using an adaptive modulation and bandwidth expansion method. The proposed system is analyzed through a computer simulation in respect of reliability, transmission rate, and power spectrum density (PSD). From the results, the proposed system has maximum 110Mbps data rate and reliability of 10-5 at E0/N0 = 21dB in indoor radio channel when we employ a TCM-128QAM at 25MHz bandwidth. [ABSTRACT FROM AUTHOR]

In this paper, it is discussed how to search the previous reports, which serve as useful references. Usefulness depends on the scopes or aims. In order to express the scope or the knowledge to achieve aims, ontology is applied. Even if the objects are identical, the expressions of various task ontologies might be different from each other. The ontologies can be linked via the common parts of the object. By utilizing the links effectively, similar items can be searched. As an example scenario, search problem of useful previous reports about similar machines for on-line support was shown. [ABSTRACT FROM AUTHOR]

The intelligent dual-reactor with the current controlled inverter, which was operated based on the current controlled algorithm, was suggested in this paper. It could limit the fault current from the fault accident as well as compensate the reactive power of the grid, irrespective of the non-linear load type or its variation. The suggested equipment consisted of the dual-reactor with a power switch and the full bridge inverter. The operation of this equipment could be divided into the normal state and the short-circuit state. The operational characteristics of the proposed intelligent dual-reactor connected with the current controlled inverter for both the normal state and the short-circuit state were analyzed from the simulation results. Keyword:dual-reactor, current controlled inverter, fault current, reactive power [ABSTRACT FROM AUTHOR]

Problems like poor security, transfer delay or packet loss occur while building network systems that are applied with TCP/IP integrate with data network systems. To solve this problem, this paper proposes the Separated Ethernet, which can give logically separation and priority to the system, and by using the OPNET Modeler simulator, we will verify its performances. [ABSTRACT FROM AUTHOR]

Determining physical location of indoor objects is one of the key issues in ubiquitous computing. Although there are many proposals to provide physical location tracking, those have some restrictions such as a dependence on the type and size of objects and a trade-off between position accuracy and the number of sensing devices. In this paper we present a hierarchical approach to conquer these restrictions using mobile detectors. We describe a system called MobiTra that estimates the position of indoor any and all objects using mobile detectors' detection histories. The effect of position estimation is evaluated through prototype testbed and simulation. [ABSTRACT FROM AUTHOR]

Many clustering methods are not suitable for high-dimensional data mining applications because of the so-called ‘curse of dimensionality' and the limitation of available memory. In this paper, we propose a new cell-based clustering method for the high-dimensional data mining applications. The proposed clustering method provides efficient cell creation and cell insertion algorithms using a space-partitioning technique, as well as makes use of a filtering-based index structure using an approximation technique. In addition, we compare the performance of our cell-based clustering method with the CLIQUE method which is well known as an efficient grid-based clustering method for high-dimensional data. The experimental results show that our clustering method achieves better performance on cluster construction time and retrieval time. Keywords: Cell-based clustering methods, high-dimensional data mining [ABSTRACT FROM AUTHOR]

In recent days, mining information from large databases has been recognized by many researchers and many data mining techniques and systems have been developed. In this study, a software (DMAP), which uses Apriori algorithm, was developed. Apriori is an influential algorithm that used in data mining. The name of the algorithm is based on the fact that the algorithm uses prior knowledge of frequent item set properties. The software is used for discovering the social status of the diabetics. A diabetic database that belongsto faculty of medicine of Kocaeli University has been used. The software was executed on a database which has records of 66 patients for test purpose. In the literature, diabetic databases have been often analyzed by rough sets. In this paper, Apriori algorithm, which has been usually used for the market basket analysis, was used for analyzing a diabetic database. [ABSTRACT FROM AUTHOR]

Incremental association mining refers to the maintenance and utilization of the knowledge discovered in the previous mining operation for later association mining. In paper, we propose a notion called maximal itemset based on which large itemsets with dynamic minimum support can be identified easily. When new transactions are inserted into a database, the maximal itemsets of the new database can be generated from previous maximal itemsets and new transactions. [ABSTRACT FROM AUTHOR]

Frequency-based mining of association rules sometimes suffers rule quality problems. In this paper, we introduce a new measure called surprisal that estimates the informativeness of transactional instances and attributes. We eliminate noisy and uninformative data using the surprisal first, and then generate association rules of good quality. Experimental results show that the surprisal-based pruning improves quality of association rules in question item response datasets significantly. [ABSTRACT FROM AUTHOR]

Rough set theory has been widely used in knowledge acquisition. However, In conventional application of rough set to numeric data, data must be pre-classified. In this paper, a different approach is introduced to deal with numeric data. We develop a mining algorithm based on fuzzy sets and tolerance rough set model, which offers a way of relating data in their semantics. [ABSTRACT FROM AUTHOR]

In this paper, we develop a knowledge representation model for the intelligent retrieval of legal cases, which provides effective legal case management. Examples are taken from the domain of accident compensation. A new set of sub-elements for legal case representation has been developed to extend the traditional representation elements of issues and factors. In our model, an issue may need to be further decomposed into sub-issues, and factors are categorized into pro-claimant, pro-responder and neutral factors. These extensions can effectively reveal the factual relevance between legal cases. Based on the knowledge representation model, we propose the IPN algorithm for intelligent legal case retrieval. Experiments and statistical analysis have been conducted to demonstrate the effectiveness of the proposed representation model and the IPN algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes an OCR post-processing approach based on multi-knowledge, which integrates language knowledge and candidate distance information given by the OCR engine. In this approach, statistical language model and semantic lexicon are combined, and candidate distance information is used to reduce the size of the search space. The experimental results show that this approach is very effective. After post-processing, the recognition accuracy rate on the test set increases from 58.45% to 83.73%, which means 60.84% error reduction. [ABSTRACT FROM AUTHOR]

Ontology evolution in the Model Driven Semantic Web can be looked as a process of model transformations, so a model transformation based conceptual framework for ontology evolution is presented in this paper. The applications of model transformations in every phase of ontology evolution process are descript respectively. The framework combines technologies of ontology evolution, ontology definition metamodel and model transformations, and it can be looked as a method for ontology evolution in the Model Driven Semantic Web. [ABSTRACT FROM AUTHOR]

In this paper, we describe the Fine-to-Coarse Scale Method in which the knowledge of cartographic patterns into small-scale map aids to recognize the corresponding patterns into large-scale map of the same territory. This approach exploits the user's experience providing the knowledge domain in the form of the prescribed feature-attribute set. The cartographic patterns are presented in raster maps. A map is composed by thematic layers that contain cartographic patterns. The knowledge to recognize cartographic objects in raster fine scale maps is based on the information about the objects of the coarse scale map. These recognized objects are removed from the map, reaching a simplified representation of the map. Then, the rest of objects are recognized as new cartographic material in this simplified map. The goal of these representations is to obtain a GIS database. [ABSTRACT FROM AUTHOR]

In constructing a knowledge-based system, knowledge acquisition plays a critical role. It is the most time-consuming phase and has been recognized as the bottleneck in the development of a knowledge-based system. This paper describes a matrix representation and mapping (MRM) approach to facilitate the knowledge acquisition process in building the knowledge bases. The MRM approach involves six consecutive steps: knowledge sources identification, taxonomic tree generation, identification of linkages between conditions and conclusions sets, generation of sub-clauses to form IF and THEN clauses, identification of logical interrelationship among sub-clauses and rule generation. The proposed approach has established an integral and complete process for knowledge acquisition. [ABSTRACT FROM AUTHOR]

An ontology consists of a set and definition of concepts that presents the characteristics of a given domain and relationship between the elements. This paper proposes a semiautomatic method to construct a domain ontology using the results of text analysis and applies it to a document retrieval system. An experiment domain used to construct an ontology was selected by the pharmacy field in which the types of ontology appeared in a document were analyzed. By using these results, a processing method of the terminologies, which are combined with some specific nouns of suffices, and uses the semantic relation to construct an ontology. In order to present usefulness for retrieving a document using the hierarchical relations in an ontology, this study compares a typical keyword based retrieval method with an ontology based retrieval method, which uses related information in an ontology for a related feedback. As a result, the latter shows the improvement of precision and recall. [ABSTRACT FROM AUTHOR]