Independent knowledge extraction in nature of humorous text analysis review using online text analysis tool

Abstract

The purpose of Text Mining is to process unstructured (textual) information, extracting meaningful numeric indices from the text, and, thus, make the information contained in the text accessible to the various data mining (statistical and machine learning) algorithms. Information can be extracted to derive summaries for the words contained in the documents or to compute summaries for the documents based on the words contained in them. Hence, we can analyze words, clusters of words used in documents, etc., or we can analyze documents and determine similarities between them or how they are related to other variables of interest in the data mining project. This topic that might be integrated with massive files of very disparate joke clusters, bound only because someone thought that they were funny or someone had an interesting thing for light-bulb jokes. Therefore, there are probably tons of doubles and triples and what you have in this collection, and there's just not enough time in the day to sort them, manually. This paper is going to analyze the different variation and analysis of funny or humorous words using data mining techniques.