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A method based on multi-feature and multi-stage verification is proposed in this paper. The direction and texture features obtained by Gabor filter are used for the first-stage verification. Then the sham dynamic features representing the writing force are used for the second-stage verification. Considering the number of samples for training is limited, the support vector machine (SVM) is selected as the classifier. The experimental results show that this method can not only increase the accuracy, but also satisfy the requirement of speed in real-time system as well. [ABSTRACT FROM AUTHOR]

This paper illustrates an algorithm for osteosarcoma segmentation, using vectorial fuzzy-connectedness segmentation, and coming up with a methodology which can be used to segment some distinct tissues of osteosarcoma such as tumor, necrosis and parosteal sarcoma from 3D vectorial images. However, fuzzy-connectedness segmentation can be successfully used only in connected regions. In this paper, some improvements have been made to segment the interested tissues which are distributed in disconnected regions. And the paper speeds up the process of segmentation by segmenting two osteosarcoma tissues simultaneously. The methology has been applied to a medical image analysis system of osteosarcoma segmentation and 3D reconstruction, which has been put into practical use in some hospitals. [ABSTRACT FROM AUTHOR]

The research work in this paper focuses on solving the critical problems in Web Service discovery such as how to locate functionality-desired Web Services and how to select the best one from large numbers of functionality-similar Web Services. The semantic description and quality description of Web Service based on ontology proposed in this paper, provides a consistent description of different kinds of Web Service, which is used as the basis of service matching. Then the matching model of Web Service is discussed in detail, which consists of semantic similarity matching according to functionality of Web Service, and semantic filtering according to quality of Web Service. Using the descriptions and matching approach, the performance of Web Service discovery can be improved by increasing the precision and recall of Web Service searching. [ABSTRACT FROM AUTHOR]

In this paper, keyword map-based relevance feedback is applied to interactive Blog search.There exists vast amount of information in the Web, from which users usually gather information without definite information needs. In particular, when exploring the Blog space, the range of user's interests is expected to be broader than usual Web browsing process. The relevance feedback techniques have been studied in the field of document retrieval, aiming to generate appropriate queries for users' information needs.Although this approach is effective when the assumption that a user has a concrete criteria on the relevance of retrieved documents holds, it could not always hold when searching Blog, which consists of vast number of short articles about various topics. Compared with the previous work on keyword map-based relevance feedback, the algorithm proposed in this paper can consider multiple topics, in which a user is interested on the keyword map. [ABSTRACT FROM AUTHOR]

Web-based information portals provide a point of access onto an integrated and structured body of information about some domain. Knowledge portals are information portals, which make an important contribution to enabling enterprise knowledge management by providing users with a consolidated, personalized user interface that allows efficient access to various types of information. Portlets are mainly ways to present contents in knowledge portals. They are a group of components, which can be involved by a portal container. However, there are lacks no interaction between those portlets. This paper discusses information integration aspects within knowledge portals and presents an approach for communicating the user context (revealing the user's information need) among portlets, utilizing ontologies technologies. [ABSTRACT FROM AUTHOR]

In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well represented using neural network, TS fuzzy system and hierarchical TS fuzzy techniques. To demonstrate the different techniques, we considered Nasdaq-100 index of Nasdaq Stock MarketSM and the S&P CNX NIFTY stock index. We analyzed 7 year's Nasdaq 100 main index values and 4 year's NIFTY index values. The parameters of the different techniques are optimized by the particle swarm optimization algorithm. This paper briefly explains how the different learning paradigms could be formulated using various methods and then investigates whether they can provide the required level of performance, which are sufficiently good and robust so as to provide a reliable forecast model for stock market indices. Experiment results reveal that all the models considered could represent the stock indices behavior very accurately. [ABSTRACT FROM AUTHOR]

The paper presents a permutation-based algorithm for predicting RNA secondary structure. It is practicable, and can be used to predict real RNA molecules. The conception of permutation is introduced, which is the start point of our algorithm. Individual is represented as a permutation of stem list. Crossover operator, mutation operator, and selection strategy are designed to be compatible with such an individual representation. At the end of the paper, a comparison between our result and that from RNAstructure is outlined. It is proved that our algorithm has achieved comparable or better result than RNAstructure. [ABSTRACT FROM AUTHOR]

A wavelet-based fuzzy multiscale edge detection scheme (WFMED) is presented in this paper. The dyadic wavelet transform is employed to produce the multiscale representation of the image, fuzzy logic is applied in wavelet domain and it can synthesize the information of image across scales effectively, an optimal result of edge detection can be acquired. WFMED method is used to extract the edge of pulp fibre image; the paper compares the performance of WFMED to the Canny edge detector and to Mallat's algorithm. The results show the superiority of WFMED to these other methods. [ABSTRACT FROM AUTHOR]

The matching similarity measures that can be used in image target recognition are surveyed and a novel similarity measure is proposed in this paper. Two basic factors that affect the image matching performance and the merits and faults of two common types of image matching algorithm are firstly analyzed. Then, based on the systematic study of similarity measures, image matching projection similarity measure is defined by simplify the classical normalized correlation measure. An example of the application of the proposed matching similarity measure in image target recognition and position is given at the end of this paper; the experimental results show its feasibility and effectivity. [ABSTRACT FROM AUTHOR]

This paper is concerned with dynamic modeling, prediction and analysis of cell cytotoxicity. A real-time cell electronic sensing (RT-CES) system has been used for label-free, dynamic measurements of cell responses to toxicant. Cells were grown onto the surfaces of the microelectronic sensors. Changes in cell number expressed as cell index (CI) have been recorded on-line as time series. The CI data are used for dynamic modeling in this paper. The developed models are verified using data that do not participate in the modeling. Optimal multi-step ahead predictions are calculated and compared with the actual CI. A new framework for dynamic cytotoxicity system analysis is established. Through the analysis of the system impulse response, we have observed that there are considerably similarities between the impulse response curves and the raw dynamic data, but there are also some striking differences between the two, particularly in terms of the initial and final cell killing effects. It is shown that dynamic modeling has great potential in modeling cell dynamics in the presence of toxicant and predicting the response of the cells. [ABSTRACT FROM AUTHOR]

Incremental checkpointing is an cost-efficient fault tolerant technique for long running programs such as genetic algorithms. In this paper, we derive the equations for the writing granularity of incremental checkpointing and find factors associated with the time overhead and disk space for incremental checkpoint. We also verify the applicability of the derived equation and the acceptability of the factors through experiments. [ABSTRACT FROM AUTHOR]

This paper presents a new analysis method of the leakage current on contaminated polymer insulators under salt-fog conditions. The proposed method tries to combine frequency-domain information with time-domain information using the framework of the fuzzy inference engine. Experimental results show that the unified approach of different domain data using fuzzy framework is available for flashover prediction and monitoring the contamination conditions of outdoor insulator. [ABSTRACT FROM AUTHOR]

The purpose of document structure analysis is to get the document structure of the source text. Document structure is defined as 3 layers in the paper. A new model of document structure analysis — DLM is proposed. The model is composed of three layers: physical structure layer, logical structure layer and semantic structure layer, which are corresponding to the definition of the document structure. The input, output and operation of each layer are illustrated in details in the paper. The model has the feature of flexible, systematic and extendible. DLM is implemented on the Automatic Summarization System. It shows that the model is feasible and good result can be achieved. [ABSTRACT FROM AUTHOR]

Handwritten character recognition has been an intensive research for last decade. A handwritten character recognition fuzzy system with an automatically generated rule base possesses the features of flexibility, efficiency and online adaptability. A major requirement of such a fuzzy system for either online or offline handwritten character recognition is, the segmentation of individual characters into meaningful segments. Then these segments can be used for the calculation of fuzzy features and the recognition process. This paper describes a new segmentation algorithm for offline handwritten character segmentation, which segments the individual handwritten character skeletons into meaningful segments. Therefore, this algorithm is a good candidate for an offline handwritten character recognition fuzzy system. [ABSTRACT FROM AUTHOR]

A failure detection method based on fuzzy comprehensive evaluation for integrated navigation systems was presented in this paper. By using fuzzy comprehensive evaluation, this method judged the measured data of every subsystem of a Kalman filter comprehensively in order to determine their states. This method overcame some shortcomings of conventional failure detection methods. At last, the contrastive experiment among this method, chi-square test and the method of data change rate has indicated that chi-square test could recognize the larger outliers, but couldn't detect the lesser, that the method of data change rate couldn't deal with the longtime continuous failures, and that the method based on fuzzy comprehensive evaluation could recognize all of the failures. So it was a quite practical method. [ABSTRACT FROM AUTHOR]

The process detecting and measuring granule named granular analysis is very important in mineral analysis. Classical methods for granular analysis are based on Matheron's sieving method. However, these methods are not adequate for mineral microscope image analysis. First, it is not an easy job to choose proper element structure for sieving process. Second, these traditional methods cannot exactly locate the position of each grain in the image. Third, the running cost of these methods on PC is too high to implement an online application. This paper proposes a granular analysis model based on improved watershed which is called varying-ladder watershed. The improved watershed overcomes the over-segment problem by adjusting the ladder height among successive steps and quickly segments the whole image into regions of different textures. Experiments show that using the proposed method gets accurate and detailed results and gains high computational performance. [ABSTRACT FROM AUTHOR]

Frequent itemsets play an essential role in many data mining tasks that try to find interesting patterns from databases. A new algorithm based on the lattice theory and bitmap index for mining frequent itemsets is proposed in this paper. Firstly, the algorithm converts the origin transaction database to an itemsets-lattice (which is a directed graph) in the preprocessing, where each itemset vertex has a label to represent its support. So we can change the complicated task of mining frequent itessets in the database to a simpler one of searching vertexes in the lattice, which can speeds up greatly the mining process. Secondly, Support counting in the association rules mining requires a great I/O and computing cost. A bitmap index technique to speed up the counting process is employed in this paper. Saving the intact bitmap usually has a big space requirement. Each bit vector is partitioned into some blocks, and hence every bit block is encoded as a shorter symbol. Therefore the original bitmap is impacted efficiently. At the end experimental and analytical results are presented. [ABSTRACT FROM AUTHOR]

This paper presents a formal method for representing and recognizing scenario patterns with rich internal temporal aspects. A scenario is presented as a collection of time-independent fluents, together with the corresponding temporal knowledge that can be relative and/or with absolute values. A graphical representation for temporal scenarios is introduced which supports consistence checking as for the temporal constraints. In terms of such a graphical representation, graph-matching algorithms/methodologies can be directly adopted for recognizing scenario patterns. [ABSTRACT FROM AUTHOR]

The paper uses Bark wavelet filter instead of the FIR filter as front-end processor of speech recognition system. Bark wavelet divides frequency band based on critical band and its bandwidths are equal in Bark domain. By selecting suitable parameters, Bark wavelet can overcome the disadvantage of dyadic wavelet and M-band wavelet dividing frequency band based on octave. The paper gave the concept and parameter setting method of Bark wavelet. For signals that are filtered by Bark wavelet, ZCPA features with noise-robust are extracted and used in speech recognition. And recognition network uses HMM. The results show the recognition rates of the system in noise environments are improved. [ABSTRACT FROM AUTHOR]

As one key step of the automatic fingerprint identification system (AFIS), fingerprint image segmentation can decrease the affection of the noises in the background region and handing time of the subsequence algorithms and improve the performance of the AFIS. Markov Chain Monte Carlo (MCMC) method has been applied to medicine image segmentation for decade years. This paper introduces the MCMC method into fingerprint image segmentation and brings forward the fingerprint image segmentation algorithm based on MCMC. Firstly, it generates a random sequence of closed curves as Markov Chain, which is regarded as the boundary between the fingerprint image region and the background image region and uses the boundary curve probability density function (BCPDF) as the index of convergence. Then, it is simulated by Monte Carlo method with BCPDF as parameter, which is converged to the maximum. Lastly, the closed curve whose BCPDF value is maximal is regarded as the ideal boundary curve. The experimental results indicate that the method is robust to the low-quality finger images. [ABSTRACT FROM AUTHOR]

In this paper, we implement hand gesture recognition system using union of fuzzy algorithm and Relational Database Management System (hereafter, RDBMS) module for Post PC (the embedded-ubiquitous environment using blue-tooth module, embedded i.MX21 board and note-book computer for smart gate). The learning and recognition model due to the RDBMS is used with input variable of fuzzy algorithm (fuzzy max-min composition), and recognize user's dynamic gesture through efficient and rational fuzzy reasoning process. The proposed gesture recognition interface consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data, 2) RDBMS module to segment significant gestures from inputted data, and 3) fuzzy max-min recognition module to recognize significant gesture of continuous, dynamic gestures and extensity of recognition. Experimental result shows the average recognition rate of 98.2% for significant dynamic gestures. [ABSTRACT FROM AUTHOR]

Recently, Biometrics-based personal identification is regarded as an effective method of person's identity with recognition automation and high performance. In this paper, the palmprint recognition method based on Hu invariant moment is proposed. And the low-resolution (75dpi) palmprint image (135×135 Pixel) is used for the small scale database of the effectual palmprint recognition system. The proposed system is consists of two parts: firstly, the palmprint fixed equipment for the acquisition of the correctly palmprint image and secondly, the algorithm of the efficient processing for the palmprint recognition. [ABSTRACT FROM AUTHOR]

Text classification can greatly improve the performance of information retrieval and information filtering, but high dimensionality of documents baffles the applications of most classification approaches. This paper proposed a Difference-Similitude Matrix (DSM) based method to solve the problem. The method represents a pre-classified collection as an item-document matrix, in which documents in same categories are described with similarities while documents in different categories with differences. Using the DSM reduction algorithm, simpler and more efficient than rough set reduction, we reduced the dimensionality of document space and generated rules for text classification. [ABSTRACT FROM AUTHOR]

It is very difficult to evaluate the performance of computer vision algorithms at present. We argue that visual cognition theory can be used to challenge this task. Following are the reasons: (1) Human vision system is so far the best and the most general vision system; (2) The human eye and camera surely have the same mechanism from the perspective of optical imaging; (3) Computer vision problem is similar to human vision problem in theory; (4) The main task of visual cognition theory is to investigate the principles of human vision system. In this paper, we first illustrate why vision cognition theory can be used to characterize the performance of computer vision algorithms and discuss how to use it. Then from the perspective of computer science we summarize some of important assumptions of visual cognition theory. Finally, many cases are introduced, which show that our method can work reasonably well. [ABSTRACT FROM AUTHOR]

SAGE data can be used to learn classification models to aid cancer classification. In this paper, maximum entropy models are built for SAGE data classification by estimating the conditional distribution of the class variable given the samples. In experiments we compare accuracy and precision to SVMs (one of the most effective classifiers in performing accurate cancer diagnosis from microarray gene expression data) and show that maximum entropy is better. The results indicate that maximum entropy is a promising technique for SAGE data classification. [ABSTRACT FROM AUTHOR]

This paper reports a new document retrieval method using non-relevant documents. From a large data set of documents, we need to find documents that relate to human interesting in as few iterations of human testing or checking as possible. In each iteration a comparatively small batch of documents is evaluated for relating to the human interesting. The relevance feedback needs a set of relevant and non-relevant documents to work usefully. However, the initial retrieved documents, which are displayed to a user, sometimes don't include relevant documents. In order to solve this problem, we propose a new feedback method using information of non-relevant documents only. We named this method non-relevance feedback document retrieval. The non-relevance feedback document retrieval is based on One-class Support Vector Machine. Our experimental results show that this method can retrieve relevant documents using information of non-relevant documents only. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to use the auto segmentation with morphological technique to find out predictable region of interest (ROI), especially the center and margin area of the tumor. The proposed method has employed moving average method for detecting edge of tumor after estimating the corresponding center using the aid of medical domain knowledge. In our re-search, after computing distance between center and edge of tumor we get factual and numerical data of tumor to calculate multi-deviation and circularity test. It is useful to construct tumor profiling by splitting up the lesion into 4 divisions with the mean of multi-standard deviation (benign: 13.7, malignancies: 38.32) and 8 divisions with the mean of multi-standard deviation (benign: 3.36, malignancies: 15.29) with equal segments. We used K-means algorithm to make classification between benign and malignance tumor. This technique has been fully validated by using more than 100 ultrasound images of the patients and found to be accurate with 90% degree of confidence. This study will help the physicians and radiologist to improve the efficiency in accurate detection of the image and appropriate diagnosis of the cancer tumor. [ABSTRACT FROM AUTHOR]

In this paper, an intelligent power management scheme for embedded systems with wireless applications is proposed to reduce the power consumption of the overall system. The proposed method is based on the feedback of the extreme channel state indicator that is designed to detect the extremely bad channel condition. The considerable power reduction is achieved by turning off modules within the embedded system related to the information transmissions under such an unreliable channel condition. A simple extreme channel state detector is also proposed. [ABSTRACT FROM AUTHOR]

In this paper, we develop a security design metric that can be used at system design time to build more secure systems. This metric is based on the system-wide approach and adopt a reliability model and scenario testing technique to produce a feedback cycle. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel wavelet transform based on the polar coordinates for datamining applications. In general, the Harr wavelet transform has been popularly used for data decomposition. However, the Harr wavelet transform shows the poor performance for the locally distributed data which are clustered around certain values, since it uses the averages as representatives for data decomposition. The proposed wavelet transform is based on the the polar coordinates which is not affected by the averages and is more suitable than the Harr wavelet transform for data decomposition of the locally distributed data. [ABSTRACT FROM AUTHOR]

Any development of electronic business entails some level risks. Reasonable risk analysis can enhance the chance of successful electronic business project implementation. In this paper, related risk assessment indexes associated with electronic business development are put forward from the aspect of technology, organization and environment. At the same time, a risk assessment model is proposed by using of fuzzy set and grey theory and its effectiveness and feasibility are tested in a practical example. The model can assist the decision-makers to understand the current risks more intensively and assess the overall risks in a more exact way. [ABSTRACT FROM AUTHOR]

Instead of using a plan library, the recognizer introduced in this paper uses a compact structure called flexible to represent goals, actions and states of the world. This method doesn't suffer the problem of acquisition and hand-coding a larger plan library as traditional methods do. The recognizer also extends classical methods in two directions. First, using flexible goals and actions via fuzzy sets, the recognizer can recognize goals even when the agent has not enough domain knowledge. Second, the recognizer offers a method for assessment of various plan hypothesis and eventual selection good ones. Since the recognizer is domain independent the method can be adapted in almost every domain. Empirical and theoretical results also show the method is efficiency and scalability. [ABSTRACT FROM AUTHOR]

XML queries are often expanded based on ontology for broad and in-depth search. But, queries generated from ontology itself are not specific to target documents. Accordingly, the overall search efficiency will deteriorate with those superfluous queries that are not succinct to the target. We suggest an ontology reduction algorithm where the target DTD is matched to ontology such that queries can be minimally expanded. The matched and reduced ontology is successively reusable for the document of a kind. This target-fitted query expansion method is expected to be more efficient than conventional methods in query processing. [ABSTRACT FROM AUTHOR]

The fault diagnosis on diesel engine is a difficult problem due to the complex structure of the engine and the presence of multi-excite sources. A new kind of fault diagnosis system based on Rough Set Theory and Support Vector Machine is proposed in the paper. Integrating the advantages of Rough Set Theory in effectively dealing with the uncertainty information and Support Vector Machine's greater generalization performance. The diagnosis of a diesel demonstrated that the solution can reduce the cost and raise the efficiency of diagnosis, and verified the feasibility of engineering application. [ABSTRACT FROM AUTHOR]

It is difficult to build a gene regulatory network directly. So the main interest focuses on the gene-gene regulation relationship mining, which reveals an active or repressive action from one gene to another. The previous methods, such as Event Method,Edge Detection Method,q-cluster method, didn't solve the gene regulatory relationship with a great succeed. In this paper, we propose a new method by introducing several more relational techniques. The results demonstrate the complete and detailed information between the genes.The data set and software will be available upon request. [ABSTRACT FROM AUTHOR]

Protein folds prediction is one of the most important problems in computational biology. In previous works, local optimization algorithms were used mostly. A new global optimization algorithm is presented in this paper. Compared with previous works, our algorithm obtains much lower energy states in all examples with a lower complexity. [ABSTRACT FROM AUTHOR]

Negotiation is an important function for e-commerce system to be efficient. However, negotiation is complicated, time-consuming and difficulty for participants to reach an agreement. This paper aims to establish an automated negotiation mechanism based on fuzzy method in order to alleviate the difficulty of negotiation. This automated negotiation is performed by autonomous agents that use fuzzy logic and issue-trading strategies in finding mutually-agreed contracts. [ABSTRACT FROM AUTHOR]

The business environment is full of uncertainties. Investing in various asset classes may lower the risk of overall portfolio and increase the potential for greater returns. In this paper, we propose a bi-objective mixed asset portfolio selection model involving projects as well as securities. Furthermore, based on fuzzy decision theory, a fuzzy mixed projects and securities portfolio selection model is also proposed. A numerical example is given to illustrate the behavior of the proposed fuzzy mixed asset portfolio selection model. [ABSTRACT FROM AUTHOR]

A fuzzy Dead Reckoning (DR) algorithm for distributed interactive applications is proposed in this paper. Since fixed threshold cannot adequately handle the dynamic relationships between moving entities, some multi-level threshold DR algorithms were proposed in the past few years. In these algorithms the level of threshold is adaptively adjusted based on the distance between entities. The proposed fuzzy DR algorithm is based on multi-level threshold DR algorithm and takes all properties of entity (e.g. position, size and view angle etc.) into consideration when adjusting the level of threshold. This algorithm employs fuzzy correlation degree to measure the relationships between entities and determine the level of threshold for DR algorithm. Fuzzy consistent relation is used to distribute weight for each property. Simulation results indicate that fuzzy DR algorithm can achieve a considerable reduction in the number of state update messages while maintaining adequate accuracy in extrapolation. [ABSTRACT FROM AUTHOR]

In this paper, fusion of the mechanism modeling and the fuzzy modeling, a component content soft-sensor, which is composed of the equilibrium calculation model for multi-component rare earth extraction and the error compensation model of fuzzy system, is proposed to solve the problem that the component content in countercurrent rare-earth extraction process is hardly measured on line. An industry experiment in the extraction Y process by HAB using this hybrid soft-sensor proves its effectiveness. [ABSTRACT FROM AUTHOR]

This paper presents an "one fit all" solution for any field's text Word Sense Disambiguation(WSD), with a Sense Rank AALest algorithm derived from the Adapted of Lesk's dictionary-based WSD algorithm. AALesk brings a score for different relationship during gloss comparing, which makes WSD not only based on statistical calculate by process in a semantic way. Rather than simply disambiguate one word's sense one time, our solution considers the whole sentence environment and uses a Sense Rank algorithm to speed up the whole procedure. Sense Rank weights different sense combination according to their importance score. All these contribute to the accuracy and effective of the solution. We evaluated our solution by using the English lexical sample data from the SENSEVAL-2 word sense disambiguation exercise and attains a good result. Additionally, the independence of system components also make our solution adaptive for different field's requirement and can be easily improved it's accuracy by changing its core algorithm AALesk's parameter setting. [ABSTRACT FROM AUTHOR]

Data integration system usually runs on unpredictable and volatile environments. Query cost model should be update with the changes of the environment. In this paper, we tackle this problem by evolving the cost model so that it can adapt to the environment change and keep up-to-date. Firstly, the factors causing the system environment to change are analyzed and different methods are proposed to deal with these changes. Then an architecture for evolving a cost model in dynamic environment is proposed. Our experimental results show the architecture of evolving a cost model in dynamic environment can well capture changes of environment and keep cost models up-to-date. [ABSTRACT FROM AUTHOR]

QoS (Quality of Service) routing is a key network function for the transmission and distribution of digitized audio/video across next-generation high-speed networks. It has two objectives: finding routes that satisfy the QoS constraints and making efficient use of network resources. The complexity involved in the networks may require the consideration of multiple constraints to make the routing decision. In this paper, we propose a novel approach using fuzzy logic technique to QoS routing that allows multiple constraints to be considered in a simple and intuitive way. Simulation shows that this fuzzy routing algorithm is efficient and promising. [ABSTRACT FROM AUTHOR]

Protein active sites control nearly all protein functions and determine the interactions upon which biological pathways and cellular networks are built. Characterization of the active sites in a protein would therefore lead to new methods of controlling proteins and ultimately controlling cells. This paper uses evolutionary trace method to analyze the binding sites of G Protein and finally give an example of 1A80. Results show that the method can be helpful in understanding how proteins carry out certain biological functions. [ABSTRACT FROM AUTHOR]

Web page classification is an important research direction of web mining. In the paper, a SVM method of web page classification is presented. It include four steps: (1) using analysis module to extract the core text and structural tags from a web page; (2) adopting the improved VSM model to generate the initial feature vectors based on the core text of web page; (3) adjusting weights of the selected features based on structural tags in web page to generate the base SVM classifier; (4) combining the base classifiers produced by iteration based on Boosting mechanism to obtain the target SVM classifier. The experiment of web page classification shows that the approach presented is efficient. [ABSTRACT FROM AUTHOR]

This paper presents an investigation into the use of the delay coordinate embedding technique with multi-input multi-output (MIMO) adaptive-network-based-fuzzy-inference system (ANFIS) to learn and predict the continuation of chaotic signals ahead in time. Based on the average mutual information and global false nearest neighbors techniques, the optimal values of the embedding dimension and the time delay are selected to construct the trajectory on the phase space. The MANFIS technique is trained by gradient descent algorithm. First, the parameter set of the membership functions is generated with the embedded phase space vectors using the back-propagation algorithm. Second, fine-tuned membership functions that make the prediction error as small as possible are built. The model is tested with both periodic and the Mackey-Glass chaotic time series. Moving root-mean-square error is used to monitor the error along the prediction horizon. [ABSTRACT FROM AUTHOR]

Clustering results often critically depend on density and similarity, and its complexity often changes along with the augment of sample dimensionality. In this paper, we refer to classical shared nearest neighbor clustering algorithm (SNN), and provide a high-dimensional shared nearest neighbor clustering algorithm (DSNN). This DSNN is evaluated using a freeway traffic data set, and experiment results show that DSNN settles many disadvantages in SNN algorithm, such as outliers, statistic, core points, computation complexity etc, also attains better clustering results on multi-dimensional data set than SNN algorithm. [ABSTRACT FROM AUTHOR]

Cross-lingual text retrieval (CLTR) concerns the retrieval of documents across languages. To allow multilingual term matching, a multilingual thesaurus is needed. However, a multilingual thesaurus encoding exact translation equivalent is insufficient for effective CLTR since relevant documents are often indexed by cross-lingual related terms. In this paper, a novel approach for automatically constructing a multilingual thesaurus based on fuzzy set theory is proposed. By introducing a degree of relatedness between multilingual terms using the concept of membership degree, partial match of cross-lingual related terms is facilitated. Development of a fuzzy multilingual news retrieval system using the proposed approach is presented. [ABSTRACT FROM AUTHOR]

In this paper, we propose the effective similarity measures on which the similarity-based pattern retrieval is based. Both data sequences and query sequences are partitioned into segments, and the query processing is based upon the comparison of the features between data and query segments, instead of scanning all data elements of entire sequences. We conduct experiments on multidimensional data sequences that are generated by extracting features from video streams, and show the effectiveness of the proposed measures. [ABSTRACT FROM AUTHOR]

Sunspots are dark areas that grow and decay on the lowest level of the Sun that are visible from the Earth. Short-term predictions of solar activity are essential to help plan missions and to design satellites that will survive for their useful lifetimes. This paper presents a parallel-structure fuzzy system (PSFS) for prediction of sunspot number time series. The PSFS consists of a multiple number of component fuzzy systems connected in parallel. Each component fuzzy system in the PSFS predicts future data independently based on its past time series data with different embedding dimension and time delay. An embedding dimension determines the number of inputs of each component fuzzy system and a time delay decides the interval of inputs of the time series. According to the embedding dimension and the time delay, the component fuzzy system takes various input-output pairs. The PSFS determines the final predicted value as an average of all the outputs of the component fuzzy systems in order to reduce error accumulation effect. [ABSTRACT FROM AUTHOR]