this paper proposes a new algorithm to improve learning performance in support vector machine by using the Kernel Relaxation and the dynamic momentum. Compared withthe static momentum, the dynamic momentum is simulta...
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Assessing the similarity between objects is a prerequisite for many datamining techniques. this paper introduces a novel approach to learn distance functions that maximizes the clustering of objects belonging to the ...
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this paper extends the idea of weighted distance functions to kernels and support vector machines. Here, we focus on applications that rely on sliding a window over a sequence of string data. For this type of problems...
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ISBN:
(纸本)0780390911
this paper extends the idea of weighted distance functions to kernels and support vector machines. Here, we focus on applications that rely on sliding a window over a sequence of string data. For this type of problems it is argued that a symbolic, context-based representation of the data should be preferred over a continuous, real format as this is a much more intuitive setting for working with (weighted) distance functions. It is shown how a weighted string distance can be decomposed and subsequently used in different kernel functions and how these kernel functions correspond to inner products between real vectors. As a case-study named entity recognition is used with information gain ratio as a weighting scheme.
According to the sizes of the attribute set and the information table, the information tables are categorized into three types of Rough Set problems, patternrecognition/machinelearning problems, and Statistical Mode...
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ISBN:
(纸本)3540286535
According to the sizes of the attribute set and the information table, the information tables are categorized into three types of Rough Set problems, patternrecognition/machinelearning problems, and Statistical Model Identification problems. In the first Rough Set situation, what we have seen is as follows: 1) the "granularity" should be taken so as to divide equally the unseen tuples out of the information table, 2) the traditional "Reduction" sense accords withthe above insistence, and 3) the "stable" subsets of tuples, which are defined through a "Galois connection" between the subset and the corresponding attribute subset, may play an important role to capture some characteristics that can be read from the given information table. We show these with some illustrative examples.
Imitation has been regarded as one of the key technologies indispensable for communication since mirror neuron [1] made a big sensation not only in physiology but also in other disciplines such as cognitive science, a...
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ISBN:
(纸本)0780392256
Imitation has been regarded as one of the key technologies indispensable for communication since mirror neuron [1] made a big sensation not only in physiology but also in other disciplines such as cognitive science, and even robotics as well. Unlike a simple copy of human motion trajectories, imitation may include more important role of human motion recognition. that is, observing other's behavior may recall the self motion through the mirror system, and this might be considered as the key component of recognition, communication and even language acquisition [2]. It is an interesting question;in what point imitation faculty is effective for communication learning? if a robot can imitate normal motions of a human partner, is it easy to read mind of the partner for the robot? this paper is the first step to those questions. In this paper, we aim at building a human-robot communication system and propose an observation-to- motion mapping system as the first step towards the final goal, learning natural communication. this system enables a humanoid platform to imitate the observed human motion, that is, a mapping from observed human motion data to its own motor commands. To realize this capability, we suppose a human partner who kindly imitates the robot motion, and the system associates bothdata of the robot somatosensory information (the set of joint angles) and observed human motions imitated from the robot motions, each of which is self-organized onto two dimensional maps using the isometric feature mapping (ISOMAP) algorithm [3] for data reduction, respectively, beforehand. A neural network is utilized for this association based on which the humanoid can imitate human motions. this system is applied to interaction rule learning with a human partner who knows the rule and reacts to the humanoid action according to them. On the other hand, the humanoid does not know the rule at the beginning but gradually learns the rule by using its own reaction rule: to just imita
Withthe rapid increase of the PDF riles in Internet, how to manage and search PDF files efficiently and quickly has become an urgent problem to be solved. the most important step of solving this problem is to extract...
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ISBN:
(纸本)0780390911
Withthe rapid increase of the PDF riles in Internet, how to manage and search PDF files efficiently and quickly has become an urgent problem to be solved. the most important step of solving this problem is to extract information from the PDF files. this paper presents a new method for extracting information from PDF files. It first parses PDF files to get text and format information and injects tags into text information to transform it into semi-structured text, and finally, one pattern match algorithm based on tree model is applied to obtain the solution. A further experiment proved this method was effective.
Clustering methods provide users with methods to summarize and organize the huge amount of data in order to help them find what they are looking for. However, one of the drawbacks of clustering algorithms is that the ...
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One of the most significant issues facing the datamining community is that of low-quality data. Real-world datasets are often inundated with various types of data integrity issues, particularly noisy data. In respons...
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Many systems attempt to forecast user navigation in the Internet through the use of past behavior, preferences and environmental factors. Most of these models overlook the possibility that users may have many diverse ...
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the accuracy of the rules produced by a concept learning system can be hindered by the presence of errors in the data. Although these errors are most commonly attributed to random noise, there also exist "ill-def...
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ISBN:
(纸本)3540298967
the accuracy of the rules produced by a concept learning system can be hindered by the presence of errors in the data. Although these errors are most commonly attributed to random noise, there also exist "ill-defined" attributes that are too general or too specific that can produce systematic classification errors. We present a computer program called Newton which uses the fact that ill-defined attributes create an ordered error pattern among the instances to compute hypotheses explaining the classification errors of a concept in terms of too general or too specific attributes. Extensive empirical testing shows that Newton identifies such attributes with a prediction rate over 95%.
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