Text Mining Techniques In Data Mining

Abstract Data Mining is the process to extract hidden predictive information from database and transform it into understandable structure for future use. The assorted domains in data mining are Web Mining, Text Mining, Sequence Mining, Graph Mining, Temporal Data Mining, Spatial Data Mining (SDM), Distributed Data Mining (DDM) and Multimedia Mining. Some of the applications of data mining, it is used for financial data analysis, retail and telecommunication industries, science and engineering and intrusion detection and prevention. In this paper we discussed about the text mining techniques and its applications.Text Mining is used to extract interesting information or knowledge or patternfrom the unstructured texts that are from different

All these stages of Text Mining process can be combined into a single workflow. Figure 1 shows the text mining techniques.

Figure 1: Techniques in Text Mining

Information Extraction

Information Extraction is the process of extracting information from unstructured document using the techniques. The main objective of information extraction is to find specific data or information in natural language text. This information is stored in database like patterns and it can be available for further use. It converts a quality of textual documents into more structured database. Figure 2 shows process of information extraction. The major task of information extraction,

• Term Analysis:It identifies the term; the term may contain one or more words. It can be helpful for extracting information from documents

• Named Entity Recognition:It identifies the textual information in a document relating the names of person , place , organization or product

• Fact Extraction:It identifies and extracts the complex facts from the documents

Figure 2: Information Extraction

Table 1: Comparative Analysis of Information Extraction

NLP is related to the area of human-computer interaction. NLP is the component of an Artificial Intelligence (AI). It is used to analyze the human languages so that computers can understand natural languages as humans do. The approaches to NLP is based on machine learning, a type of artificial intelligence that examines and uses the patterns in data to improve a program's own understanding. The role of NLP in Text Mining is to provide the systems in the information extraction phase with linguistic data that they need to perform their task. Figure 4 explains about the process of natural language processing. NLP includes the