this paper analyzes the effect of momentum on steepest descent training for quadratic performance functions. Some global convergence conditions of the steepest descent algorithm are obtained by directly analyzing the ...
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the proceedings contain 44 papers. the topics discussed include: a learning material for physics experiment with high-accuracy using computer vision technique;automatic classification of remarks in werewolf BBS;a rapi...
ISBN:
(纸本)9781538633021
the proceedings contain 44 papers. the topics discussed include: a learning material for physics experiment with high-accuracy using computer vision technique;automatic classification of remarks in werewolf BBS;a rapid incremental frequent pattern mining algorithm for uncertain data;global and local bursts detection in streaming data;two-mode three-way dominance points model for periodic dissimilarity;an intelligent noninvasive taste detection app for watermelons;automated risk identification of CMMI project planning using ontology;and depth recognition in 3D translucent stereoscopic imaging of medical volumes by means of a glasses-free 3d display.
We propose a novel algorithm for computing asymmetric word similarity (AWS) using mass assignment based on fuzzy sets of words. Words in documents are considered similar if they appear in similar contexts. However, th...
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A data mining procedure for automatic determination of fuzzy decision tree structure using a genetic program is discussed. A genetic program is an algorithm that evolves other algorithms or mathematical expressions. M...
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Mobile mining is about finding useful knowledge from the raw data produced by mobile users. the mobile environment consists of a set of static device and mobile device. Previous works in mobile data mining include fin...
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Teachers tend to set the free-text questions for testing the comprehensive ability of students. that leads to the increasing attention to the intelligent auto-grading system for easing the grading load on examiners. I...
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ISBN:
(纸本)9781538660058
Teachers tend to set the free-text questions for testing the comprehensive ability of students. that leads to the increasing attention to the intelligent auto-grading system for easing the grading load on examiners. In this paper, we present a novel automatic essay scoring system based on Natural Language Processing and Deep learning technologies. In particular, the proposed system encodes an essay as sequential embeddings and harnesses a bi-directional LSTM to catch the semantic information. Meanwhile, the system constructs the attention for each essay so that the network can learn to focus on the valid information correctly in an article, which can also provide the reasonable evidence of the predictive result. the dataset for training and testing is the public essay set available in the automated Student Assessment Prize on Kaggle. the study shows that our system achieves state-of-the-art performance in grade prediction, and more importantly, our intelligent auto-grading system can focus on the critical words and sentences, analyze the logical semantic relationship of the context and predict the interpretable grades.
the fusion system designing of multiple classifiers, which is based on the radial basis probabilistic neural network (RBPNN), is discussed in this paper. By means of the proposed design method, the complex structure o...
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the MOGA is used as automatic calibration method for a wide range of water and environmental simulation models. the task of estimating the entire Pareto set requires a large number of fitness evaluations in a standard...
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Imbalance data constitutes a great difficulty for most algorithms learning classifiers. However, as recent works claim, class imbalance is not a problem in itself and performance degradation is also associated with ot...
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ISBN:
(纸本)9783319108407;9783319108391
Imbalance data constitutes a great difficulty for most algorithms learning classifiers. However, as recent works claim, class imbalance is not a problem in itself and performance degradation is also associated with other factors related to the distribution of the data as the presence of noisy and borderline examples in the areas surrounding class boundaries. this contribution proposes to extend SMOTE with a noise filter called Iterative-Partitioning Filter (IPF), which can overcome these problems. the properties of this proposal are discussed in a controlled experimental study against SMOTE and its most well-known generalizations. the results show that the new proposal performs better than exiting SMOTE generalizations for all these different scenarios.
OLAP systems depend heavily on the materialization of multidimensional structures to speed-up queries, whose appropriate selection constitutes the cube selection problem. However, the recently proposed distribution of...
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ISBN:
(纸本)9783642153808
OLAP systems depend heavily on the materialization of multidimensional structures to speed-up queries, whose appropriate selection constitutes the cube selection problem. However, the recently proposed distribution of OLAP structures emerges to answer new globalization's requirements, capturing the known advantages of distributed databases. But this hardens the search for solutions, especially due to the inherent heterogeneity, imposing an extra characteristic of the algorithm that must be used: adaptability. Here the emerging concept known as hyper-heuristic can be a solution. In fact, having an algorithm where several (meta-)heuristics may be selected under the control of a heuristic has an intrinsic adaptive behavior. this paper presents a hyper-heuristic polymorphic algorithm used to solve the extended cube selection and allocation problem generated in M-OLAP architectures.
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