Semantic Mining for Language Text Analysis

Abstract

Recent work into knowledge-mining algorithms has found that second order models can be used to approximate the inputs to systems by first calculating their time trajectories, and then obtaining the causal parameters of these trajectories. In this paper a new method of text analysis is proposed, and the application of knowledge-mining algorithms to text analysis is investigated. Mathcad is used to model relevant knowledge mining algorithms and test their performance with signals derived from ASCII codes of text excerpts. For the first time, time-varying signals relating to a series of input values have been analysed with knowledge mining algorithms. The Mathcad program which does this has been embedded into a user interface in MS Access to allow ease of text selection by users and automatic calculation of ASCII values for analysis.