Withthe available resources on the Internet becoming plentiful, a large amount of harmful information is permeating in and has been influencing people's normal work and living seriously. therefore, some harmful d...
详细信息
ISBN:
(纸本)0769518346
Withthe available resources on the Internet becoming plentiful, a large amount of harmful information is permeating in and has been influencing people's normal work and living seriously. therefore, some harmful data stream must be recognized and filtered out effectively. After analyzing some harmful contents in Internet information stream, we present a new method, which recognizes specific information by machinelearning (ML). We extracted key information from a number of corpuses through ML method to obtain the part of speech (POS) Transfer-Form for key information by learning from corpuses, which is based on the same pronunciation matching of key information. Further more, the testing value of key information will be obtained in real corpus to examine the likelihood between matching rules from information streams and those learnt from corpuses through the average value of POS transfer probability of key information. therefore, the testing value for the whole real data stream will be obtained the experiment proved that the method was efficient for recognizing certain Internet harmful information.
In this paper, we synthesize the main findings of three repeat purchase modelling case studies using real-life direct marketing data. Historically, direct marketing - more recently, targeted web marketing - has been o...
详细信息
ISBN:
(纸本)9729805067
In this paper, we synthesize the main findings of three repeat purchase modelling case studies using real-life direct marketing data. Historically, direct marketing - more recently, targeted web marketing - has been one of the most popular domains for the exploration of the feasibility and the viable use of novel business intelligence techniques. Many a data mining technique has been field tested in the direct marketing domain. this can be explained by the (relatively) low-cost availability of recency, frequency, monetary (RFM) and several other customer relationship data, the (relatively) well-developed understanding of the task and the domain, the clearly identifiable costs and benefits, and because the results can often be readily applied to obtain a high return on investment. the purchase incidence modelling cases reported on in this paper were in the first place undertaken to trial run state-of-the-art supervised Bayesian learning multilayer perceptron (MLP) and least squares support vector machine (LS-SVM) classifiers. For each of the cases, we also aimed at exploring the explanatory power (relevance) of the available RFM and other customer relationship related variable operationalizations for predicting purchase incidence in the context of direct marketing.
In this paper, methods of choosing a vehicle out of an image are explored. Digital images are taken from a monocular camera. Image processing techniques are applied to each single frame picture to create the feature v...
详细信息
ISBN:
(纸本)0819441937
In this paper, methods of choosing a vehicle out of an image are explored. Digital images are taken from a monocular camera. Image processing techniques are applied to each single frame picture to create the feature vector. Finally the resulting features are used to classify whether there is a car in the picture or not using support vector machines. the result are compared to those obtained using a neural network. A discussion on techniques to enhance the feature vector and th results from bothlearningmachines will be included.
Support vector machines (SVM) are learning algorithms derived from statistical learningtheory. the SVM approach was originally developed for binary classification problems. In this paper SVM architectures for multi-c...
详细信息
Support vector machines (SVM) are learning algorithms derived from statistical learningtheory. the SVM approach was originally developed for binary classification problems. In this paper SVM architectures for multi-class classification problems are discussed, in particular we consider binary trees of SVMs to solve the multi-class problem. Numerical results for different classifiers on a benchmark data set of handwritten digits are presented.
Support vector machines (SVM) are learning algorithms derived from statistical learningtheory. the SVM approach was originally developed for binary classification problems. In this paper SVM architectures for multi-c...
详细信息
the proceedings contain 198 papers. the topics discussed include: where is the intelligence in machine vision?;radial-basis-function networks: learning and applications;dimensionality reduction techniques for multivar...
ISBN:
(纸本)0780364007
the proceedings contain 198 papers. the topics discussed include: where is the intelligence in machine vision?;radial-basis-function networks: learning and applications;dimensionality reduction techniques for multivariate data classification, interactive visualization, and analysis-systematic feature selection vs. extraction;integrating community services- a common infrastructure proposal;communication-support for ongoing conversations in users' background knowledge;change in human behaviors based on affiliation needs - toward the design of a social guide agent system;consumer communication on the net-findings from consumer interviews;learning incremental syntactic structures with recursive neural networks;computational capabilities of linear recursive networks;a generalized regression neural network for logo recognition;and a proposal of fuzzy modeling with dimensionality reduction incorporating fuzzy inference method.
the proceedings contain 198 papers. the topics discussed include: where is the intelligence in machine vision?;radial-basis-function networks: learning and applications;dimensionality reduction techniques for multivar...
ISBN:
(纸本)0780364007
the proceedings contain 198 papers. the topics discussed include: where is the intelligence in machine vision?;radial-basis-function networks: learning and applications;dimensionality reduction techniques for multivariate data classification, interactive visualization, and analysis-systematic feature selection vs. extraction;integrating community services- a common infrastructure proposal;communication-support for ongoing conversations in users' background knowledge;change in human behaviors based on affiliation needs - toward the design of a social guide agent system;consumer communication on the net-findings from consumer interviews;learning incremental syntactic structures with recursive neural networks;computational capabilities of linear recursive networks;a generalized regression neural network for logo recognition;and a proposal of fuzzy modeling with dimensionality reduction incorporating fuzzy inference method.
In machine diagnostics it is difficult to collect for learning all possible operating modes of machine functioning. Some operating modes will usually be missing. In these circumstances, it is important to know which m...
详细信息
In machine diagnostics it is difficult to collect for learning all possible operating modes of machine functioning. Some of the operating modes are often missing. In these circumstances, it is important to know which ...
详细信息
ISBN:
(纸本)0769507506
In machine diagnostics it is difficult to collect for learning all possible operating modes of machine functioning. Some of the operating modes are often missing. In these circumstances, it is important to know which modes (subclasses) are the most valuable for successful machine diagnosis. It is also of interest to investigate the usefulness of noise injection to cover the missing operating modes in the data. In this paper, we study the importance of selecting different operating modes of a water-pump and using them for learning in both 2-class and 4-class problems. We show that the operating modes representing different running speeds are more valuable than those representing machine loads. We also demonstrate that the 2-nearest neighbours directed noise injection is useful when filing in missing operating modes in the data.
暂无评论