9th IEEE International Conference on Cognitive Informatics (ICCI'10), 2010
With the growth of the Web2.0, e-commerce has become very popular in use, many websites offer the... more With the growth of the Web2.0, e-commerce has become very popular in use, many websites offer the opportunity to make sales online and give the opportunity to get own an online review about objects, persons, and products. New opportunities and challenges arise as people can now actively use information technologies to seek and understand other people's opinions (sentiments) when to
2014 6th International Conference of Soft Computing and Pattern Recognition (SoCPaR), 2014
ABSTRACT The domain of Healthcare is characterized by difficulty, dynamism and variety. In the 21... more ABSTRACT The domain of Healthcare is characterized by difficulty, dynamism and variety. In the 21st century healthcare represents different challenges (the increasing cost of care and the growing of populations). For that, Agent Technology can provide better healthcare than the traditional medical system. In the hospital, several types of medical problems can be solved by agents. As examples of problems, which emerge in the hospital, we mention: collaboration between hospital wards, elaborations of diagnostics, the collection of information about patients etc. The adaptation of cooperative Multi Agent System (MAS) can solve these problems. In this regard, this study proposes a general architecture that integrates Swarm Intelligence into Multi Agent healthcare System in order to make care as efficient as possible.
Journal of Systems and Information Technology, 2013
ABSTRACT Purpose ‐ Despite the actual prevalence of diverse types of multimedia information, rese... more ABSTRACT Purpose ‐ Despite the actual prevalence of diverse types of multimedia information, research on video news is still in an early stage. Improving the accessibility of video news seems worth investigating, therefore, the purpose of this paper is to present a new combination mode of video news text clustering and selection. This method is useful for sorting out and classifying various types of news videos and media texts based on sentiment analysis. Design/methodology/approach ‐ A novel system is proposed, whereby video news are identified and categorized into good or bad ones via the authors' suggested Hidden Markov Model (HMM) and Support Vector Machine (SVM) hybrid learning method. Actually, an exploratory video news sentiment analysis case study, conducted on various news databases, has proven that the feature-selection-combining method, encompassing the Information Gain (IG), Mutual Information (MI) and CHI-statistic (CHI), performs the best classification, which testifies and highlights the designed framework's value. Findings ‐ In fact, the system turns out to be applicable to several areas, especially video news, where annotation and personal perspectives affect the accuracy aspect. Research limitations/implications ‐ The present work shows the way for further research pertaining to the personal attitudes and the application of different linguistic techniques during the classification. Originality/value ‐ The achieved results are so promising, encouraging and satisfactory, that they highlight the originality and efficiency of the authors' approach as an effective tool enabling to secure an easy access to video news and multi-media texts.
International Journal on Artificial Intelligence Tools, 2013
ABSTRACT The recent years have been marked by a rapid growth in the World Wide Web 2.0 applicatio... more ABSTRACT The recent years have been marked by a rapid growth in the World Wide Web 2.0 applications such as blog posts, forums, mailing lists, and product-review websites. As a result, a special sentiment analysis field has sprung up relevant to the issue of people's responses to the diversity of available subjects. Hence, one might well wonder: how do people feel and react when dealing with certain topics? In this paper, a new automatic sentiment-processing model has been advanced, whereby the current problems faced by the prevalent existing models can be deciphered and more properly treated. The suggested approach consists in developing a multi-agent system based on a thorough linguistic analysis, meanwhile highlighting the major contributions provided by such a study in combination with the syntactic, semantic, and subjective analyses. Actually, the newly-devised framework enables to resolve the ambiguities and complexities of the natural evaluative language and to strengthen, as well as consolidate, the results achieved at the various analysis stages thereof.
9th IEEE International Conference on Cognitive Informatics (ICCI'10), 2010
With the growth of the Web2.0, e-commerce has become very popular in use, many websites offer the... more With the growth of the Web2.0, e-commerce has become very popular in use, many websites offer the opportunity to make sales online and give the opportunity to get own an online review about objects, persons, and products. New opportunities and challenges arise as people can now actively use information technologies to seek and understand other people's opinions (sentiments) when to
2014 6th International Conference of Soft Computing and Pattern Recognition (SoCPaR), 2014
ABSTRACT The domain of Healthcare is characterized by difficulty, dynamism and variety. In the 21... more ABSTRACT The domain of Healthcare is characterized by difficulty, dynamism and variety. In the 21st century healthcare represents different challenges (the increasing cost of care and the growing of populations). For that, Agent Technology can provide better healthcare than the traditional medical system. In the hospital, several types of medical problems can be solved by agents. As examples of problems, which emerge in the hospital, we mention: collaboration between hospital wards, elaborations of diagnostics, the collection of information about patients etc. The adaptation of cooperative Multi Agent System (MAS) can solve these problems. In this regard, this study proposes a general architecture that integrates Swarm Intelligence into Multi Agent healthcare System in order to make care as efficient as possible.
Journal of Systems and Information Technology, 2013
ABSTRACT Purpose ‐ Despite the actual prevalence of diverse types of multimedia information, rese... more ABSTRACT Purpose ‐ Despite the actual prevalence of diverse types of multimedia information, research on video news is still in an early stage. Improving the accessibility of video news seems worth investigating, therefore, the purpose of this paper is to present a new combination mode of video news text clustering and selection. This method is useful for sorting out and classifying various types of news videos and media texts based on sentiment analysis. Design/methodology/approach ‐ A novel system is proposed, whereby video news are identified and categorized into good or bad ones via the authors' suggested Hidden Markov Model (HMM) and Support Vector Machine (SVM) hybrid learning method. Actually, an exploratory video news sentiment analysis case study, conducted on various news databases, has proven that the feature-selection-combining method, encompassing the Information Gain (IG), Mutual Information (MI) and CHI-statistic (CHI), performs the best classification, which testifies and highlights the designed framework's value. Findings ‐ In fact, the system turns out to be applicable to several areas, especially video news, where annotation and personal perspectives affect the accuracy aspect. Research limitations/implications ‐ The present work shows the way for further research pertaining to the personal attitudes and the application of different linguistic techniques during the classification. Originality/value ‐ The achieved results are so promising, encouraging and satisfactory, that they highlight the originality and efficiency of the authors' approach as an effective tool enabling to secure an easy access to video news and multi-media texts.
International Journal on Artificial Intelligence Tools, 2013
ABSTRACT The recent years have been marked by a rapid growth in the World Wide Web 2.0 applicatio... more ABSTRACT The recent years have been marked by a rapid growth in the World Wide Web 2.0 applications such as blog posts, forums, mailing lists, and product-review websites. As a result, a special sentiment analysis field has sprung up relevant to the issue of people's responses to the diversity of available subjects. Hence, one might well wonder: how do people feel and react when dealing with certain topics? In this paper, a new automatic sentiment-processing model has been advanced, whereby the current problems faced by the prevalent existing models can be deciphered and more properly treated. The suggested approach consists in developing a multi-agent system based on a thorough linguistic analysis, meanwhile highlighting the major contributions provided by such a study in combination with the syntactic, semantic, and subjective analyses. Actually, the newly-devised framework enables to resolve the ambiguities and complexities of the natural evaluative language and to strengthen, as well as consolidate, the results achieved at the various analysis stages thereof.
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