ISBN: 9786202433761 - sentiment analysis of data: sentiment analysis of twitter data using n-gram and knn (11 resultados)

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Taschenbuch. Condición: Neu. SENTIMENT ANALYSIS OF DATA | Sentiment Analysis of Twitter Data using N-Gram and KNN | Meetali Chauhan | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786202433761 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

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PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 64 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A sentiment is known as an attitude or judgment towards any particular event or person. Opinion mining is known as the extraction of these sentiments or opinions from given data. This technique also helps in analysing the kinds of sentiments that people have towards specific objects or services. The best source available to collect the sentiments is the internet. Twitter is known as a social networking platform that users access for posting their views online. Due to the unique properties of Tweets, there is an increase in new challenges. Higher analysis studies are needed in case of sentiments as compared to other domain applications due to their complexities. This research focuses on analysing the sentiments of product reviews for Amazon. Classification as well as feature extraction is applied such that sentiment analysis can be performed. The WDE-LSTM mechanism has been applied for performing sentiment analysis. In addition to this, in this research, the KNN-LSTM mechanism is applied to make certain improvements in the outcomes. Python simulator is used to implement the existing and proposed techniques. Around 94.5% of accuracy is achieved by implementing this improved method.…

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Paperback. Condición: new. Paperback. A sentiment is known as an attitude or judgment towards any particular event or person. Opinion mining is known as the extraction of these sentiments or opinions from given data. This technique also helps in analysing the kinds of sentiments that people have towards specific objects or services. The best source available to collect the sentiments is the internet. Twitter is known as a social networking platform that users access for posting their views online. Due to the unique properties of Tweets, there is an increase in new challenges. Higher analysis studies are needed in case of sentiments as compared to other domain applications due to their complexities. This research focuses on analysing the sentiments of product reviews for Amazon. Classification as well as feature extraction is applied such that sentiment analysis can be performed. The WDE-LSTM mechanism has been applied for performing sentiment analysis. In addition to this, in this research, the KNN-LSTM mechanism is applied to make certain improvements in the outcomes. Python simulator is used to implement the existing and proposed techniques. Around 94.5% of accuracy is achieved by implementing this improved method. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condición: New. PRINT ON DEMAND.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A sentiment is known as an attitude or judgment towards any particular event or person. Opinion mining is known as the extraction of these sentiments or opinions from given data. This technique also helps in analysing the kinds of sentiments that people have towards specific objects or services. The best source available to collect the sentiments is the internet. Twitter is known as a social networking platform that users access for posting their views online. Due to the unique properties of Tweets, there is an increase in new challenges. Higher analysis studies are needed in case of sentiments as compared to other domain applications due to their complexities. This research focuses on analysing the sentiments of product reviews for Amazon. Classification as well as feature extraction is applied such that sentiment analysis can be performed. The WDE-LSTM mechanism has been applied for performing sentiment analysis. In addition to this, in this research, the KNN-LSTM mechanism is applied to make certain improvements in the outcomes. Python simulator is used to implement the existing and proposed techniques. Around 94.5% of accuracy is achieved by implementing this improved method.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.…