Functional Applications of Text Analytics Systems
Text analytics consist of the statistics about a text element which includes the word count the word histogram and the word frequency histogram. Most text documents of value are related to other—sometimes many other—documents and so analytics describing the relative frequency of terms in a document compared to its peers are important for defining key words (tagging labeling indexing) search-responsive terms (query terms) and compressed versions of the documents (key words summary etc. ). This clearly written text explains the functional applications of search translation optimization and learning with regard to text analytics. Generation of analytics is aided by a hybrid ensemble or other combinatorial approach in which two or more effective analytic processes are used simultaneously and their outputs combined to form a better “consensus”. Additional value to the preservation of the information is provided through these methods. Also since they encompass capabilities of two or more knowledge-generating systems they can create a “superset” of access points to the data generated. The book also describes the role of functional approaches in the testing and configuration of these systems. | Functional Applications of Text Analytics Systems
