The Brainy Read for the Business Strategist: Free Text Search

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Formalizing language
Gisting meaning in free text
Establishing English as a binary tool for computer applications
Identifying part-of-speech by word order
Establishing meaning without individual word definitions
Providing a level of meaning deeper than words
Allowing the user to reduce documents to four universal patterns
Changing the paradigm of free text beyond word search /heuristics
Addressing substance as a thinking tool
Tying algorithmic structure to context without any dictionary definitions in the source code
Creating tools for natural-language query
Exceeding power of word-tagging
Eliminating the ambiguity and assumptions tied to the meanings of words
Minimizing fraud
Serving as ThoughtPrint^Ž baseline for norm and deviation standards in environments which systematically track communication

theExactWord^Ž seeks partners in this venture. The baseline is completed; products are not.

Data-Base Search Engine Goals:

To Query for Information by Using English Meaning, rather than Key-Word Searches

Our algorithms will create a product that will query a data base by meaning rather than by key-word searches, greatly streamlining computer memory and efficiency. Also, paired with data-mining tools, theExact Word^Ž's technology can significantly filter enormous quantities of data by examining meaning rather than merely listing key words.

ThoughtPrint^Ž Psychological Profiling:

The color-coded WordPrint^Ž product has applications for psychological profiling and identification matching. For example, we analyze the UNABOMBER's "Manifesto." Also, a current capability exists for our Surveil product to gist free text to determine fraudulent or threatening behavior.

Data-base search engines are queried by using key words supplied by the user. The computer searches by matching that word to identical words in a body of information. This process not only requires multiple passes by a computer, but also causes the amount of information returned to be too large and not necessarily the information needed by the user. theExact Word^Ž's discovery about language will change the process from word-tagging to context identification without a word-definition base.

Such a query approach can reduce the overwhelming flow of data for searches and for sorting text.

Natural Language queries can logically follow from context identification because the user can formulate thought to relate to searched data. Currently the glut of information overwhelms individual users and the text search field itself. Further, the result of gathered indexed information cannot as yet identify significance to the data collected.

At once a data-mining tool and the means to identify significance, theExact Word^Ž's technology can move to a Generation 5 use of natural language.

Back to Free Text Search Intro