The Experts below are selected from a list of 267 Experts worldwide ranked by ideXlab platform
Nizar Bouguila - One of the best experts on this subject based on the ideXlab platform.
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A study of spam filtering using support vector machines
Artificial Intelligence Review, 2010Co-Authors: Ola Amayri, Nizar BouguilaAbstract:Electronic mail is a Major Revolution taking place over traditional communication systems due to its convenient, economical, fast, and easy to use nature. A Major bottleneck in electronic communications is the enormous dissemination of unwanted, harmful emails known as spam emails . A Major concern is the developing of suitable filters that can adequately capture those emails and achieve high performance rate. Machine learning (ML) researchers have developed many approaches in order to tackle this problem. Within the context of machine learning, support vector machines (SVM) have made a large contribution to the development of spam email filtering. Based on SVM, different schemes have been proposed through text classification approaches (TC). A crucial problem when using SVM is the choice of kernels as they directly affect the separation of emails in the feature space. This paper presents thorough investigation of several distance-based kernels and specify spam filtering behaviors using SVM. The Majority of used kernels in recent studies concern continuous data and neglect the structure of the text. In contrast to classical kernels, we propose the use of various string kernels for spam filtering. We show how effectively string kernels suit spam filtering problem. On the other hand, data preprocessing is a vital part of text classification where the objective is to generate feature vectors usable by SVM kernels. We detail a feature mapping variants in TC that yield improved performance for the standard SVM in filtering task. Furthermore, to cope for realtime scenarios we propose an online active framework for spam filtering. We present empirical results from an extensive study of online, transductive, and online active methods for classifying spam emails in real time. We show that active online method using string kernels achieves higher precision and recall rates.
Ola Amayri - One of the best experts on this subject based on the ideXlab platform.
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A study of spam filtering using support vector machines
Artificial Intelligence Review, 2010Co-Authors: Ola Amayri, Nizar BouguilaAbstract:Electronic mail is a Major Revolution taking place over traditional communication systems due to its convenient, economical, fast, and easy to use nature. A Major bottleneck in electronic communications is the enormous dissemination of unwanted, harmful emails known as spam emails . A Major concern is the developing of suitable filters that can adequately capture those emails and achieve high performance rate. Machine learning (ML) researchers have developed many approaches in order to tackle this problem. Within the context of machine learning, support vector machines (SVM) have made a large contribution to the development of spam email filtering. Based on SVM, different schemes have been proposed through text classification approaches (TC). A crucial problem when using SVM is the choice of kernels as they directly affect the separation of emails in the feature space. This paper presents thorough investigation of several distance-based kernels and specify spam filtering behaviors using SVM. The Majority of used kernels in recent studies concern continuous data and neglect the structure of the text. In contrast to classical kernels, we propose the use of various string kernels for spam filtering. We show how effectively string kernels suit spam filtering problem. On the other hand, data preprocessing is a vital part of text classification where the objective is to generate feature vectors usable by SVM kernels. We detail a feature mapping variants in TC that yield improved performance for the standard SVM in filtering task. Furthermore, to cope for realtime scenarios we propose an online active framework for spam filtering. We present empirical results from an extensive study of online, transductive, and online active methods for classifying spam emails in real time. We show that active online method using string kernels achieves higher precision and recall rates.
John W Vinson - One of the best experts on this subject based on the ideXlab platform.
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a Major Revolution in texas
Health Affairs, 1997Co-Authors: John W VinsonAbstract:The future of charity care in Texas is uncertain, despite recent legislation regulating nonprofit hospitals.
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A ‘Major Revolution’ In Texas
Health Affairs, 1997Co-Authors: John W VinsonAbstract:The future of charity care in Texas is uncertain, despite recent legislation regulating nonprofit hospitals.
Danièle Revel - One of the best experts on this subject based on the ideXlab platform.
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The market structure of shale gas drilling in the United States
2014Co-Authors: Danièle RevelAbstract:The market structure of shale gas drilling in the United States / Zhongmin Wang & Qing Xue. Washington : Resources dfor the Future, September 2014, 11 p. (RFF Discussion Paper 14-31) http://www.rff.org/RFF/Documents/RFF-DP-14-31.pdf Abstract (© RFF) : This paper provides the first empirical study of the market structure of the shale gas drilling industry in the United States. Modern shale gas drilling, which is a Major Revolution in the energy industry, was highly concentrated during its expe...
B. D. Pant - One of the best experts on this subject based on the ideXlab platform.
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Design principles and considerations for the 'ideal' silicon piezoresistive pressure sensor: A focused review
Microsystem Technologies, 2014Co-Authors: S. Santosh Kumar, B. D. PantAbstract:Over the past four decades, the field of silicon piezoresistive pressure sensors has undergone a Major Revolution in terms of design methodology and fabrication processes. Cutting edge fabrication technologies have resulted in improved precision in key factors like dimensions of diaphragm and placement of piezoresistors. Considering the unique nature of each sensor and the trade-offs in design, it is not feasible to follow a standard design approach. Thus, it is useful to derive the specific design from a number of important factors to arrive at the ‘ideal’ design. In this paper, we critically review and analyze the various design considerations and principles for silicon piezoresistive pressure sensor. We also report the effect of these considerations on the sensor output taking help of various CAD tools. Keeping in view the accuracy of state-of-the-art fabrication tools and the stringent demands of the present day market, it has become important to include many of these design aspects. Modelling using analytical expressions for thin plates has also been looked into as it gives a quick guideline and estimation of critical parameters before detailed finite element method analysis. Wherever possible, fabrication imperfections and their effects have been discussed. Dependency of piezoresistive coefficients on temperature and doping concentration, the effect of clamping condition of diaphragms and fabrication using wet bulk micromachining is also analyzed. Silicon-on-insulator based sensors along with innovative design strategies, and future trends have also been discussed. This paper will serve as a quick and comprehensive guide for pressure sensor developers.
