Data Mining: Text Mining

Text Mining

• Deals specifically with unstructured text data
• Involves the use of natural language processing (NLP) techniques to extract useful information and insights from large amounts of unstructured text data

Text Mining Process

• Gathering unstructured information from various sources (e.g. plain text, web pages, PDF records)
• Pre-processing and data cleansing tasks to eliminate inconsistency in the data
• Processing and controlling tasks to review and further clean the data set
• Pattern analysis to extract important and applicable data for decision-making and trend analysis

Common Methods for Analyzing Text Mining

• Text Summarization: extracting partial content to reflect the whole content automatically
• Text Categorization: assigning a category to the text among predefined categories
• Text Clustering: segmenting texts into several clusters based on substantial relevance

Importance of Language and Text Analysis

• Language plays a crucial role in communication and sharing information
• Each language has its own rules and grammar for developing sentences
• Combination of words arranged meaningfully results in the formation of a sentence

Unstructured Text Data

• Only 20% of data is generated in structured format, while the majority exists in textual form, which is highly unstructured
• Examples of unstructured text data include social media posts, emails, and text messages

Text Analysis Method

• Text Analysis is a method used to produce meaningful insights from text data

Text Mining in Data Mining

• Text Mining is a component of data mining that deals with unstructured text data

Text Mining Techniques

• Information Retrieval: processing available documents and text data into a structured form for pattern recognition and analytical processes
• Information Extraction: extracting meaningful words from documents
• Natural Language Processing (NLP): automatic processing and analysis of unstructured text information using Machine Learning and Deep Learning methodologies

Text Mining and Natural Language Processing (NLP)

• Text Mining is the process of deriving meaningful information from natural language text
• NLP is a part of computer science and artificial intelligence that deals with human languages and performs linguistic analysis to help machines understand and process text

NLP Processes

• NLP involves various processes, including automatic summarization, part-of-speech tagging, disambiguation, chunking, natural language understanding, and recognition
• These processes can be performed using Python