9786202564236 - map-reduce technique for sentiment analysis of twitter data di majgave, amol; desai, pallavi (12 risultati)
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Da: California Books, Miami, FL, U.S.A.California Books
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Map-Reduce Technique for sentiment analysis of twitter data | Amol Majgave (u. a.) | Taschenbuch | 64 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202564236 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de…| Anbieter: preigu.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As per some current studies, public opinions expressed in social media may be connected with various social issues. To find out what actually can be discovered in social media data, we need data mining. But traditional data mining…has many limitations as size of datasets. So, new data mining approaches that can handle massive amount of data have recently been referred to as big data algorithms. In this paper a new system is proposed that delivers large database of Social Networking Site (SNS) called 'Twitter'. Processing the tweet involves extraction of metadata of tweet, geocoding the physical address in a tweet, analysing the sentiment of content in the tweet text and extracting the considerable and key phrases from a text. After all the Information Extracted and NER (Named Entity Recognition) text analysis from tweet, are stored into a MongoDB database, as it is more scalable and more flexible among others of NoSQL databases 64 pp. Englisch.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Majgave AmolMr.Amol B.Majgave working in CSE Department of DKTE S Textile and Engineering Instutute IchlkaranjiMs.Pallavi R.Desai working in CSE Department of Dr.J.J.Magdum college of Engineering Jaysi…ngpurAs per some current stu.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -As per some current studies, public opinions expressed in social media may be connected with various social issues. To find out what actually can be discovered in social media data, we need data mining. But traditional data mining has…many limitations as size of datasets. So, new data mining approaches that can handle massive amount of data have recently been referred to as big data algorithms. In this paper a new system is proposed that delivers large database of Social Networking Site (SNS) called 'Twitter'. Processing the tweet involves extraction of metadata of tweet, geocoding the physical address in a tweet, analysing the sentiment of content in the tweet text and extracting the considerable and key phrases from a text. After all the Information Extracted and NER (Named Entity Recognition) text analysis from tweet, are stored into a MongoDB database, as it is more scalable and more flexible among others of NoSQL databasesVDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As per some current studies, public opinions expressed in social media may be connected with various social issues. To find out what actually can be discovered in social media data, we need data mining. But traditional data mining has m…any limitations as size of datasets. So, new data mining approaches that can handle massive amount of data have recently been referred to as big data algorithms. In this paper a new system is proposed that delivers large database of Social Networking Site (SNS) called 'Twitter'. Processing the tweet involves extraction of metadata of tweet, geocoding the physical address in a tweet, analysing the sentiment of content in the tweet text and extracting the considerable and key phrases from a text. After all the Information Extracted and NER (Named Entity Recognition) text analysis from tweet, are stored into a MongoDB database, as it is more scalable and more flexible among others of NoSQL databases.
