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Text mining is the process of extracting data from unstructured text and finding patterns or relations. Below is a list of text mining methodologies. Centroid-based Clustering: Unsupervised learning method. Clusters are determined based on data points. [1]
A template processor (also known as a template engine or template parser) is software designed to combine templates with data (defined by a data model) to produce resulting documents or programs. [ 1 ] [ 2 ] [ 3 ] The language that the templates are written in is known as a template language or templating language .
Text mining methods and software is also being researched and developed by major firms, including IBM and Microsoft, to further automate the mining and analysis processes, and by different firms working in the area of search and indexing in general as a way to improve their results.
Template filling: Extracting a fixed set of fields from a document, e.g. extract perpetrators, victims, time, etc. from a newspaper article about a terrorist attack. Event extraction: Given an input document, output zero or more event templates. For instance, a newspaper article might describe multiple terrorist attacks.
Flex (fast lexical analyzer generator) is a free and open-source software alternative to lex. [2] It is a computer program that generates lexical analyzers (also known as "scanners" or "lexers").
Named-entity recognition (NER) (also known as (named) entity identification, entity chunking, and entity extraction) is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.
Unstructured information can then be enriched and tagged to address ambiguities and relevancy-based techniques then used to facilitate search and discovery. Examples of "unstructured data" may include books, journals, documents, metadata , health records , audio , video , analog data , images, files, and unstructured text such as the body of an ...
Pdf-parser is a command-line program that parses and analyses PDF documents. It provides features to extract raw data from PDF documents, like compressed images. pdf-parser can deal with malicious PDF documents that use obfuscation features of the PDF language. [1] The tool can also be used to extract data from damaged or corrupt PDF documents.