Pub Date : 2013-12-01DOI: 10.1109/RAICS.2013.6745481
R. Hari, C. P. Roopesh, M. Wilscy
In video summarization, a short video clip is made from lengthy video without losing its semantic content using significant scenes containing important frames, called keyframes. This process finds importance in video content management systems. The proposed method involves automatic summarization of motion picture based on human face. In this method, those frames within which the appearances of an actor or actress, selected by the user, occurs are treated as keyframes. In the first step, the video is segmented into shots by Mutual Information. Then it detects the available faces in the frames of each shot using the local Successive Mean Quantization Transform (SMQT) features and Sparse Network of Winnows (SNoW) classifier. Then the face of an actor of interest is selected to match with different available faces, already extracted, using Eigenfaces method. A shot is taken into consideration, if the method succeeds in finding at least one matched face in the shot. The selected shots are finally combined to create summarized video.
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Pub Date : 2013-12-01DOI: 10.1109/RAICS.2013.6745442
Ansamma John, M. Wilscy
In the recent times, the requirement for generation of multi-document summary has gained a lot of attention among the researchers due to the information explosion in the web media. Mostly, the text summarization technique uses the sentence extraction technique where the salient sentences in the multiple documents are extracted and presented as a summary. In our proposed system, we have developed a random forest classifier based multi-document summarization system that differentiates the sentences in the multiple documents as one belonging to the summary or not belonging to the summary. For this each sentence in the documents is represented by a set of feature scores. Classifier is trained using feature scores and summary information of each sentence in the document set. Feature scores of sentences of multiple documents to be summarized are given as the test document for the classifier. From the output of the classifier, sentences that belonging to the summary class, a required size summary is generated using Maximal Marginal Relevance. The experiments are conducted using the DUC 2002 dataset and its corresponding summary. Experimental results show the quality of the summary generated by this method is good in terms of relevance and novelty.
{"title":"Random forest classifier based multi-document summarization system","authors":"Ansamma John, M. Wilscy","doi":"10.1109/RAICS.2013.6745442","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745442","url":null,"abstract":"In the recent times, the requirement for generation of multi-document summary has gained a lot of attention among the researchers due to the information explosion in the web media. Mostly, the text summarization technique uses the sentence extraction technique where the salient sentences in the multiple documents are extracted and presented as a summary. In our proposed system, we have developed a random forest classifier based multi-document summarization system that differentiates the sentences in the multiple documents as one belonging to the summary or not belonging to the summary. For this each sentence in the documents is represented by a set of feature scores. Classifier is trained using feature scores and summary information of each sentence in the document set. Feature scores of sentences of multiple documents to be summarized are given as the test document for the classifier. From the output of the classifier, sentences that belonging to the summary class, a required size summary is generated using Maximal Marginal Relevance. The experiments are conducted using the DUC 2002 dataset and its corresponding summary. Experimental results show the quality of the summary generated by this method is good in terms of relevance and novelty.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131868847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-12-01DOI: 10.1109/RAICS.2013.6745488
Angana Chakraborty, S. Bandyopadhyay
Clustering of the web sessions to identify the vis-itors' choices while browsing the web pages, is an important problem in web mining. The sequence of pages viewed by the user in a particular time-frame, i.e., the session, captures his/her interest in a specific topic. Clustering of these sessions is therefore needed to provide customized services to the users having similar interests. In this article, we propose a novel and accurate similarity measure, Psim, between two web pages and a method of clustering the web sessions using a recently developed Fast Optimal Global Sequence Alignment Algorithm (FOGSAA). FOGSAA is an optimal global alignment algorithm which is used to align the pairs of sessions. It computes the pair-wise distances, which is used to cluster the sessions in similar groups. FOGSAA aligns the sessions in much less time and results in an average time gain of 35.84% over the conventional dynamic programming based Needleman-Wunsch's method, where both are generating the same optimal alignment. Therefore, application of FOGSAA to align the sessions makes the procedure faster and at the same time maintains the quality.
{"title":"Clustering of web sessions by FOGSAA","authors":"Angana Chakraborty, S. Bandyopadhyay","doi":"10.1109/RAICS.2013.6745488","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745488","url":null,"abstract":"Clustering of the web sessions to identify the vis-itors' choices while browsing the web pages, is an important problem in web mining. The sequence of pages viewed by the user in a particular time-frame, i.e., the session, captures his/her interest in a specific topic. Clustering of these sessions is therefore needed to provide customized services to the users having similar interests. In this article, we propose a novel and accurate similarity measure, Psim, between two web pages and a method of clustering the web sessions using a recently developed Fast Optimal Global Sequence Alignment Algorithm (FOGSAA). FOGSAA is an optimal global alignment algorithm which is used to align the pairs of sessions. It computes the pair-wise distances, which is used to cluster the sessions in similar groups. FOGSAA aligns the sessions in much less time and results in an average time gain of 35.84% over the conventional dynamic programming based Needleman-Wunsch's method, where both are generating the same optimal alignment. Therefore, application of FOGSAA to align the sessions makes the procedure faster and at the same time maintains the quality.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115605894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-12-01DOI: 10.1109/RAICS.2013.6745456
C. M. Portela, H. Slootweg, Marko van Eekelen
Current electricity grids are developing towards so called “Smart Grids”. Within these Smart Grids information and communication technology (ICT) will play a role in new categories of communication, measurement and control equipment in the electricity grid. Furthermore, it will play a role in the communication between the main actors of a Smart Grid (Market players, Grid Operators and Consumers) and inside the home of the consumer. For ICT architects it is difficult to make the appropriate architectural design choices as different architecture variants are possible and their design space has not been structured. In order to help ICT architects we have structured the design space of the ICT architecture for the Smart Grid and we briefly show how the structured design space can be used in concrete Smart Grid projects. In this paper, first an overview will be given of current views on Smart Grids. Then, the applied research strategy will be explained and the resulting ICT architecture variants for the Smart Grid are presented. The design space is structured based on market orientedness, grid orientedness and the level of distributedness of these architecture variants. Finally, the ICT architecture variants are positioned in the 3-dimensional design space and an overview is given of how the design space could be used in concrete Smart Grid projects.
{"title":"Structuring the design space of the ICT architecture for the Smart Grid","authors":"C. M. Portela, H. Slootweg, Marko van Eekelen","doi":"10.1109/RAICS.2013.6745456","DOIUrl":"https://doi.org/10.1109/RAICS.2013.6745456","url":null,"abstract":"Current electricity grids are developing towards so called “Smart Grids”. Within these Smart Grids information and communication technology (ICT) will play a role in new categories of communication, measurement and control equipment in the electricity grid. Furthermore, it will play a role in the communication between the main actors of a Smart Grid (Market players, Grid Operators and Consumers) and inside the home of the consumer. For ICT architects it is difficult to make the appropriate architectural design choices as different architecture variants are possible and their design space has not been structured. In order to help ICT architects we have structured the design space of the ICT architecture for the Smart Grid and we briefly show how the structured design space can be used in concrete Smart Grid projects. In this paper, first an overview will be given of current views on Smart Grids. Then, the applied research strategy will be explained and the resulting ICT architecture variants for the Smart Grid are presented. The design space is structured based on market orientedness, grid orientedness and the level of distributedness of these architecture variants. Finally, the ICT architecture variants are positioned in the 3-dimensional design space and an overview is given of how the design space could be used in concrete Smart Grid projects.","PeriodicalId":184155,"journal":{"name":"2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127252366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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