this paper presents a novel method to predict the trends of topics on Twitter based on MACD (Moving Average Convergence-Divergence),which is one of the simplest and most effective momentum indicator in technique analy...
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this paper presents a novel method to predict the trends of topics on Twitter based on MACD (Moving Average Convergence-Divergence),which is one of the simplest and most effective momentum indicator in technique analysis of *** MACD turns two trend-following indicators,moving averages,into a momentum oscillator by subtracting the longer moving average from the shorter moving *** a result,we monitor the key words of topics on Twitter,and use the longer moving average and the shorter moving average to track their longer and shorter trends,***,we redefine the trends momentum with two moving averages according to the developmental characteristics of topics on Twitter,and use it to predict the *** results show that the proposed method is very simple and effective.
this study applies Chaos theory to investigate the seizure detection of epilepsy withthree groups of data （Groups H,S and E）,showing the electroencephalography （EEG） changes of *** three groups,Group H （normal s...
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this study applies Chaos theory to investigate the seizure detection of epilepsy withthree groups of data （Groups H,S and E）,showing the electroencephalography （EEG） changes of *** three groups,Group H （normal state）,Group S （during seizures） and Group E （after seizures）,contain 100 series of EEG signals *** detected data are processed by chaotic theory to transform the signals to four parameters with Delay Time （τ）,Embedding Dimension （dm）,Correlation Dimension （CD） value,and Largest Lyapunov Exponent （LLE）.Furthermore,well-known classification software for datamining,termed See5 based on entropy theory,is used to find out the classification rules for the EEG signals of epilepsy patients.
this study proposes two kinds of Evolutionary datamining (EvoDM) algorithms to the insurance fraud *** is GA-Kmeans by combining K-means algorithm with genetic algorithm (GA).the other is MPSO-Kmeans by combining K-m...
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this study proposes two kinds of Evolutionary datamining (EvoDM) algorithms to the insurance fraud *** is GA-Kmeans by combining K-means algorithm with genetic algorithm (GA).the other is MPSO-Kmeans by combining K-means algorithm with Momentum-type Particle Swarm Optimization (MPSO).the dataset used in this study is composed of 6 attributes with 5000 instances for car insurance *** 5000 instances are divided into 4000 training data and 1000 test *** different initial cluster centers for each attribute are set by means of (a) selecting the centers randomly from the training set and (b) averaging all data of training set ***,the proposed GA-Kmeans and MPSO-Kmeans are employed to determine the optimal weights and final cluster centers for attributes,and the accuracy of prediction for test set is computed based on the optimal weights and final cluster *** show that the presented two EvoDM algorithms significantly enhance the accuracy of insurance fraud prediction when compared the results to that of pure K-means algorithm.
Based on the features such as high convergence rate and global optimization of Support Vector machine (SVM) which follows structure risk minimization principle, a method of fire detection is proposed, in which the sha...
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Based on the features such as high convergence rate and global optimization of Support Vector machine (SVM) which follows structure risk minimization principle, a method of fire detection is proposed, in which the shape of bright areas are analyzed by SVM and results are produced. After collecting images of fire and interference source under different conditions, datas of shape features are extracted. Many of them are used as training set and delivered to SVM;the other data are used as test set for patternrecognition. Fire experiments show that trained SVM with RBF kernel and SMO algorithm can recognize images with 94.32% accuracy rate.
Assessment is an important and widely used element of the taught ***-Assisted Assessment （CAA） systems are helping teachers by automatic marking of assessments of low-stake high volume exams （e.g.,school level）.Fo...
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Assessment is an important and widely used element of the taught ***-Assisted Assessment （CAA） systems are helping teachers by automatic marking of assessments of low-stake high volume exams （e.g.,school level）.For accurate and efficient marking of the exams,these systems require either training on pre-marked data or creating detailed representation of templates of the model *** of these reasons,CAA systems are not adequate for high-stake low volume assessments （e.g.,university level）.As compared to fully automatic assessment approaches,semi-automatic approaches are ***-Computer Collaborative Assessment （HCCA） is one such approach that involves human marker in the marking *** clusters short text answers and then present these clusters to the human marker for *** of long text answers is problematic because of problems pose by natural *** this research,we suggest automatic summarization as a means to reduce noise and length of the text answers to improve clustering of answers and hence marking.
the overview presents the development and application of Hierarchical Temporal Memory (HTM). HTM is a new machinelearning method which was proposed by Jeff Hawkins in 2005. It is a biologically inspired cognitive met...
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the overview presents the development and application of Hierarchical Temporal Memory (HTM). HTM is a new machinelearning method which was proposed by Jeff Hawkins in 2005. It is a biologically inspired cognitive method based on the principle of how human brain works. the method invites hierarchical structure and proposes a memory-prediction framework, thus making it able to predict what will happen in the near future. this overview mainly introduces the developing process of HTM, as well as its principle, characteristics, advantages and applications in vision, image processing and robots movement, some potential applications by using HTM , such as thinking process, are also put forward.
Education is acknowledged to be the primary vehicle for improving the economic well-being of people [1,6]. Textbooks have a direct bearing on the quality of education imparted to the students as they are the primary c...
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ISBN:
(纸本)9783642217869
Education is acknowledged to be the primary vehicle for improving the economic well-being of people [1,6]. Textbooks have a direct bearing on the quality of education imparted to the students as they are the primary conduits for delivering content knowledge [9]. they are also indispensable for fostering teacher learning and constitute a key component of the ongoing professional development of the teachers [5,8].
the problem of reconstructing dependencies from empirical data became very important in a very large range of applications. Procedures used to solve this problem are known as “Methods of machinelearning&...
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ISBN:
(纸本)9783642217869
the problem of reconstructing dependencies from empirical data became very important in a very large range of applications. Procedures used to solve this problem are known as “Methods of machinelearning” [1,3]. these procedures include methods of regression reconstruction, inverse problems of mathematical physics and statistics, machinelearning in patternrecognition (for visual and abstract patterns represented by sets of features) and many others. Many web network control problems also belong to this field. the task is to reconstruct the dependency between input and output data as precisely as possible using empirical data obtained from experiments or statistical observations.
In this paper we consider the problem of structured document recognition. the document recognition system is proposed. this system incorporates a recognition module based on methods of structured image recognition, a ...
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ISBN:
(纸本)9783642217869
In this paper we consider the problem of structured document recognition. the document recognition system is proposed. this system incorporates a recognition module based on methods of structured image recognition, a graph document model and a method of document model generalization. the machinelearning component makes the process of document model construction easier and less time-consuming.
Nowadays, classification is one of the many fields in datamining, also known as Knowledge Discovery in databases, which aims at extracting information from large data volumes. In order to achieve this, datamining us...
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