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Text Analysis: The Next Step in Search
In general, text analysis refers to the process of extracting interesting and non-trivial information and knowledge from unstructured text.
Furthermore, according to Moore's Law, computer processor and storage capacities double every 18 months, which, in the modern context, also means that the amount of information stored will double during this timeframe as well. The continual, exponential growth of information means most people and organizations are always battling with the specter of information overload.

Although effective and thorough information retrieval is a real challenge, the development of new computing techniques to help control this mountain of information is advancing quickly as well. Text analysis is at the forefront of these new techniques, but it needs to be used correctly and understood according to the particular context in which it's applied. For example, in an international environment, a suitable text analysis solution may consist of a combination of standard relevance-ranking with adaptive filtering and interactive visualization, which is based on utilizing features (i.e. metadata elements) that have been extracted earlier.

Control of Unstructured Information
More than 90% of all information is unstructured, and the absolute amount of stored unstructured information increases daily. Searching within this information, or performing analysis using database or data mining techniques, is not possible, as these techniques work only on structured information. The situation is further complicated by the diversity of stored information: scanned documents, email and multimedia files (speech, video and photos).

Text analysis neutralizes these concerns through the use of various mathematical, statistical, linguistic and pattern-recognition techniques that allow automatic analysis of unstructured information as well as the extraction of high quality and relevant data. ("High quality" here refers to the combination of relevance [i.e. finding a needle in a haystack] and the acquiring of new and interesting insights.) With text analysis, instead of searching for words, we can search for linguistic word patterns, which enables a much higher level of search.

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