Named Entity Recognition
Studies
Practices
Textual Feedback Analysis
Leveraging Text Data
Effective Textual Analysis
The Significance of Text Analysis in Innovation
Analyzing Customer Feedback
Mining Unstructured Data with Text Analytics 
Named Entity Recognition (NER) Identifying and classifying key entities in text into predefined categories such as names, organizations, and locations
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Studies following are key areas where text analytics is applied: Sentiment analysis Topic modeling Text classification
Named entity recognition Keyword extraction 2
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Practices Named Entity Recognition: Identifying and classifying key entities within the text
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Textual Feedback Analysis Spam detection, issue categorization
Named Entity Recognition (NER) Identifies and classifies key entities in text (e
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Leveraging Text Data Named Entity Recognition Identifies and classifies key entities in text, such as names, organizations, and locations
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Effective Textual Analysis Named Entity Recognition (NER): This involves identifying and classifying key entities in text, such as names of people, organizations, locations, and dates
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The Significance of Text Analysis in Innovation Named Entity Recognition (NER): Identifies and classifies key entities within the text, such as names, organizations, and locations
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Analyzing Customer Feedback Named Entity Recognition: Identifies and categorizes key entities mentioned in the feedback, such as products, services, or locations
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Text Mining for Business Intelligence Named Entity Recognition (NER) A technique that identifies and classifies key entities in text, such as names, organizations, and locations, enhancing data relevance
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User Feedback Named Entity Recognition (NER): Identifying and classifying key entities (e
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