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4. Pick out any text-mining tool that impressed you the most and discuss an overview of its text
mining process, sentimental & speech analytics.
Solution
LanguageWare is a natural language processing (NLP) technology developed by ibm, which
allows applications to process natural language text. It comprises a set of Java libraries which
provide a range of nlp functions: language identification, text segmentation/tokenization,
normalization, entity and relationship extraction, and semantic analysis and disambiguation. The
analysis engine uses Finite state machine approach at multiple levels, which aids its performance
characteristics, while maintaining a reasonably small footprint.
Speech analytics:
Speech analytics allows users to analyse and extract information from both live and recorded
conversations. It is being used effectively to gather intelligence for security purposes, to enhance
the presentation and utility of rich media applications, and perhaps most significantly, to deliver
quantitative business intelligence through the analysis of the millions of recorded calls .
Sentiment analysis:
Sentiment analysis is a branch of speech analytics that focuses specifically on assessing the
emotional states displayed in a conversation.
One common use of sentiment analysis within contact centres is to provide insight into a
customer’s feelings about an organisation, its products, services, customer service processes, as
well as its individual agent behaviours.

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4. Pick out any text-mining tool that impressed you the most and dis.pdf

  • 1. 4. Pick out any text-mining tool that impressed you the most and discuss an overview of its text mining process, sentimental & speech analytics. Solution LanguageWare is a natural language processing (NLP) technology developed by ibm, which allows applications to process natural language text. It comprises a set of Java libraries which provide a range of nlp functions: language identification, text segmentation/tokenization, normalization, entity and relationship extraction, and semantic analysis and disambiguation. The analysis engine uses Finite state machine approach at multiple levels, which aids its performance characteristics, while maintaining a reasonably small footprint. Speech analytics: Speech analytics allows users to analyse and extract information from both live and recorded conversations. It is being used effectively to gather intelligence for security purposes, to enhance the presentation and utility of rich media applications, and perhaps most significantly, to deliver quantitative business intelligence through the analysis of the millions of recorded calls . Sentiment analysis: Sentiment analysis is a branch of speech analytics that focuses specifically on assessing the emotional states displayed in a conversation. One common use of sentiment analysis within contact centres is to provide insight into a customer’s feelings about an organisation, its products, services, customer service processes, as well as its individual agent behaviours.