New Opportunities for Sentiment Analysis and Information Processing (Advances in Data Mining and Database Management)

Price: $270.00
(as of Dec 27,2024 14:11:16 UTC – Details)

Publisher ‏ : ‎ Engineering Science Reference (June 25, 2021)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 315 pages
ISBN-10 ‏ : ‎ 1799880613
ISBN-13 ‏ : ‎ 978-1799880615
Item Weight ‏ : ‎ 2.34 pounds
Dimensions ‏ : ‎ 8.5 x 0.75 x 11 inches

New Opportunities for Sentiment Analysis and Information Processing (Advances in Data Mining and Database Management)

Sentiment analysis, the process of identifying and extracting opinions, emotions, and attitudes from text data, has become an essential tool for businesses to understand customer feedback, market trends, and brand reputation. With the rapid growth of social media platforms and online review sites, there is an increasing need for more advanced techniques and tools to efficiently analyze and process large volumes of unstructured text data.

Recent advances in data mining and database management have opened up new opportunities for sentiment analysis and information processing. Machine learning algorithms, natural language processing techniques, and big data technologies are being used to develop more accurate and efficient sentiment analysis models. These models can not only classify text data into positive, negative, or neutral sentiments but also identify specific emotions, topics, and entities within the text.

Furthermore, advancements in database management systems have enabled organizations to store, retrieve, and analyze massive amounts of text data in real-time. NoSQL databases, in-memory databases, and distributed computing frameworks are being leveraged to handle the complexities of unstructured text data and support the scalability and performance requirements of sentiment analysis applications.

Overall, the combination of advanced data mining and database management technologies is revolutionizing the way organizations extract insights from text data. By leveraging these tools and techniques, businesses can gain a deeper understanding of customer preferences, market trends, and brand sentiment, ultimately driving better decision-making and improving overall business performance.
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