Text Mining Technology
Making sense of unstructured data
Organizations use natural language to communicate with employees, customers, partners and general public, as well as to organize information internally for future reference. Analysts estimate that over 80% of useful information is being stored in the form of text. Can you afford ignoring the dominant portion of your data?
Emails, web pages, memos, call center transcripts, survey responses, claims notes, legal cases, patent descriptions, research articles, and incident reports - all hold valuable pieces of knowledge that enable analysts to discover patterns, trends and anomalies, predict outcomes of future situations, and make better business decisions.
Yet, manual analysis is inefficient for processing large volumes of text, as it is slow, biased and prone to human errors. Statistical techniques fall short of achieving this goal because text documents contain hidden linguistic and semantic relationships that have to be taken into account. Eliciting knowledge from unstructured text represents a major technological challenge.
The solution is offered by Text Mining the technology for automated knowledge discovery in large volumes of text based on a combination of linguistic, semantic, statistical and machine learning techniques.
Many important tasks can be solved with text mining:
Megaputer provides two separate software packages for text analysis. PolyAnalyst performs linguistic and semantic text analysis and coding, clustering and categorization of documents, entity extraction, visualization of patterns, automated or manual taxonomy creation, text OLAP, and generating interactive graphical reports on results. TextAnalyst provides a list of the most important keywords in a document, a set of related keywords for each word, and the ability to automatically summarize a document or perform natural language queries.
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