Text Mining Knowledge Discovery Knowledge Management

Text Mining Knowledge Discovery Knowledge Management

Text Mining

Just as data mining techniques provide researchers with an automated method of gleaning unsuspected knowledge from structured electronic data (databases), parallel techniques are being developed to detect patterns and connections in unstructured electronic data (email, documents, websites). Text mining is in its infancy, but it offers hope for conquering the growing knowledge glut.

Top: Reference: Knowledge Management: Knowledge Discovery: Text Mining

See Also:

- Using text clustering as a way to group document according to the overall similarities in their content. Features background information, examples and technical papers.
- A Semio Corporation white paper.
- A comprehensive and annotated survey of knowledge extraction from text, in the form of Powerpoint PDF slides.
- Features of the tools named Extractor, Summarizer, TextMiner and InstaLink.
- Bayesian based technology for mapping and mining concepts in large text collections. Features overview, services, technique, gallery and contact information.
- Module specifically designed to study textual information. Features screen shots and purchasing information.
- Automated system of retrieving and structuring information from open Internet sources and corporate warehouses. Features demo, news, FAQs and contact information.
- Information, links, download and faq on text mining and natural language processing.
- Automatic text summarization tools. Includes contact information.
- Describes the design, prototyping and evaluation of ARC, a system for automatically compiling a list of authoritative Web resources on any sufficiently broad topic. Features resources and references.
- An interface which attempts to show the user, graphically, the relationship between the words in the query and the documents retrieved. Features technical papers and commercial and other uses.
- Automatic extraction of entities and cross references from texts.
- A list of resources including links to working groups, products, conferences and workshops.
- Offers solutions for understanding textual content and the automatic comprehension of text meaning by a computer. Features products, news and contact information.
- TextAnalyst is a unique text mining tool, using a semantic network for retrieval, clustering, classification, summarization, and natural language querying.
- Defines data mining, information access, and corpus-based computational linguistics, and then discusses the relationship of these to text data mining. The intent behind these contrasts is to draw attention to exciting new kinds of problems for computation
- Features, demo and case studies of Twid Expert and Temis Online Miner/Categorizer.
- Links to reviews and analyses of text mining research. Features online presentations, white papers and other projects, papers, people and products.
- Provide a web home for people interested in text mining related technologies, with a mailing list and a resources section.
- Offers training, integration, and custom development for applications of text mining, search, and categorization. Features white papers, testimonials, and contact information.
- A novel user interface that integrates search and browsing of very large category hierarchies with their associated text collections. Features technical papers.
- Turns unstructured information into business knowledge; includes components for building advanced text mining and text search applications. Features library, news, how to buy, events, training and certification, support and services.
- Included in the famous SAS set of tools for quantitative data analysis, the module for text analysis includes clustering algorithms, document categorisation and data extraction. Overview and screenshots.
- Develops applications to search out and retrieve data from web pages and e-mail archives and provides turnkey services to find and retrieve information from the web, XML databases or stores of incoming e-mail. Features contact information.
- Survey discussing the main approaches to text categorization that fall within the machine learning paradigm. By Fabrizio Sebastiani, in ACM Computing Surveys. [PDF Format]
- Netherlands firm offers search and text mining solutions on a hosting basis. Features services, support, portfolio and contact information.
- Profiles the content of a web page, or from a content database, and uses data mining techniques to associate profiled content dynamically during a browsing session.
- Provides NLP applications based on its proprietary VisualText technology. Product and service information, online software tour and documentation.
- The Text Mining group at the University of Waikato in New Zealand. With a focus on Viterbi search and entropy-based methods the group has a compression feel to it.
- Internet-based set of tools for text analysis including categorisation and summarization of documents. Online demo.
- Products and services offering automated collection of data from public web sites. Features overviews and contact information.

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