Sinopsis
Several applications involve a transient stream of data which has to be modeled and analyzed continuously. Their continuous arrival in multiple, rapid, time-varying and possibly unpredictable and unbounded way make the analysis difficult and opens fundamentally new research problems. Examples of such data intensive applications include stock market, road traffic analysis, whether forecasting systems etc. Data Stream Management Systems are specifically designed for handling continuous data streams. They can handle multiple, time-varying, unpredictable and unbounded streams which cannot be handled using traditional tools. In this work, we have used a Data Stream Management System- Stanford STREAM in three different application domain namely Road Traffic analysis, Habitat Monitoring analysis and Network Packet analysis. We have also used another DSMS, telegraphCQ, coupled with jamdroid, an open source road traffic analysis system, for mining road traffic data.
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Reseña del editor
Several applications involve a transient stream of data which has to be modeled and analyzed continuously. Their continuous arrival in multiple, rapid, time-varying and possibly unpredictable and unbounded way make the analysis difficult and opens fundamentally new research problems. Examples of such data intensive applications include stock market, road traffic analysis, whether forecasting systems etc. Data Stream Management Systems are specifically designed for handling continuous data streams. They can handle multiple, time-varying, unpredictable and unbounded streams which cannot be handled using traditional tools. In this work, we have used a Data Stream Management System- Stanford STREAM in three different application domain namely Road Traffic analysis, Habitat Monitoring analysis and Network Packet analysis. We have also used another DSMS, telegraphCQ, coupled with jamdroid, an open source road traffic analysis system, for mining road traffic data.
Biografía del autor
Nadeem Akhtar received his B. Tech and M.Tech degree in Computer Science from Aligarh Muslim University, Aligarh, India. He is currently working as Assistant Professor in the department of Computer Engineering, Aligarh Muslim University. His research interests include Data Mining, Database Management System and Operating Systems.
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Statistical Analysis of Continuous Data Streams Using DSMS
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LAP LAMBERT Academic Publishing Apr 2012, 2012
ISBN 10: 3846545201
ISBN 13: 9783846545201
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Several applications involve a transient stream of data which has to be modeled and analyzed continuously. Their continuous arrival in multiple, rapid, time-varying and possibly unpredictable and unbounded way make the analysis difficult and opens fundamentally new research problems. Examples of such data intensive applications include stock market, road traffic analysis, whether forecasting systems etc. Data Stream Management Systems are specifically designed for handling continuous data streams. They can handle multiple, time-varying, unpredictable and unbounded streams which cannot be handled using traditional tools. In this work, we have used a Data Stream Management System- Stanford STREAM in three different application domain namely Road Traffic analysis, Habitat Monitoring analysis and Network Packet analysis. We have also used another DSMS, telegraphCQ, coupled with jamdroid, an open source road traffic analysis system, for mining road traffic data. 88 pp. Englisch. Nº de ref. del artículo: 9783846545201
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Statistical Analysis of Continuous Data Streams Using DSMS
Publicado por
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846545201
ISBN 13: 9783846545201
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Librería: moluna, Greven, Alemania
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Akhtar NadeemNadeem Akhtar received his B. Tech and M.Tech degree in Computer Science from Aligarh Muslim University, Aligarh, India. He is currently working as Assistant Professor in the department of Computer Engineering, Aligarh M. Nº de ref. del artículo: 5498072
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Statistical Analysis of Continuous Data Streams Using DSMS
Publicado por
LAP LAMBERT Academic Publishing Apr 2012, 2012
ISBN 10: 3846545201
ISBN 13: 9783846545201
Nuevo
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Several applications involve a transient stream of data which has to be modeled and analyzed continuously. Their continuous arrival in multiple, rapid, time-varying and possibly unpredictable and unbounded way make the analysis difficult and opens fundamentally new research problems. Examples of such data intensive applications include stock market, road traffic analysis, whether forecasting systems etc. Data Stream Management Systems are specifically designed for handling continuous data streams. They can handle multiple, time-varying, unpredictable and unbounded streams which cannot be handled using traditional tools. In this work, we have used a Data Stream Management System- Stanford STREAM in three different application domain namely Road Traffic analysis, Habitat Monitoring analysis and Network Packet analysis. We have also used another DSMS, telegraphCQ, coupled with jamdroid, an open source road traffic analysis system, for mining road traffic data.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch. Nº de ref. del artículo: 9783846545201
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Statistical Analysis of Continuous Data Streams Using DSMS : Mining of Data Streams
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LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846545201
ISBN 13: 9783846545201
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Several applications involve a transient stream of data which has to be modeled and analyzed continuously. Their continuous arrival in multiple, rapid, time-varying and possibly unpredictable and unbounded way make the analysis difficult and opens fundamentally new research problems. Examples of such data intensive applications include stock market, road traffic analysis, whether forecasting systems etc. Data Stream Management Systems are specifically designed for handling continuous data streams. They can handle multiple, time-varying, unpredictable and unbounded streams which cannot be handled using traditional tools. In this work, we have used a Data Stream Management System- Stanford STREAM in three different application domain namely Road Traffic analysis, Habitat Monitoring analysis and Network Packet analysis. We have also used another DSMS, telegraphCQ, coupled with jamdroid, an open source road traffic analysis system, for mining road traffic data. Nº de ref. del artículo: 9783846545201
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Statistical Analysis of Continuous Data Streams Using DSMS | Mining of Data Streams
Publicado por
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846545201
ISBN 13: 9783846545201
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Librería: preigu, Osnabrück, Alemania
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Taschenbuch. Condición: Neu. Statistical Analysis of Continuous Data Streams Using DSMS | Mining of Data Streams | Nadeem Akhtar (u. a.) | Taschenbuch | 88 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783846545201 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 106502759
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