Text Classification Quotes

Clustering analysis developed originally from anthropology in 1932, before it was introduced to psychology in 1938 and was later adopted by personality psychology in 1943 for trait theory classification. Today, clustering analysis is used in data mining, information retrieval, machine learning, text mining, web analysis, marketing, medical diagnosis, and numerous other fields.

Machine learning has been through several transition periods starting in the mid-90s. From 1995–2005, there was a lot of focus on natural language, search, and information retrieval. The machine learning tools were simpler than what we’re using today; they include things like logistic regression, SVMs (support vector machines), kernels with SVMs, and PageRank. Google became immensely successful using these technologies, building major success stories like Google News and the Gmail spam classifier using easy-to-distribute algorithms for ranking and text classification—using technologies that were already mature by the mid-90s. (Reza Zadeh)

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Key features Always write in small chunks (also-called blocks ). Unlike many paragraphs, only one topic per chunk. Nothing extra. Chunks can contain several sentences. Label very chunk with an informative, relevant, short, bold-face title. Standards for organizing and sequencing large documents. Diagrams and illustrations can be chunks. Use them. Possible to cluster most of the 40 sentence types into seven categories: procedure, process, structure, concept, fact, classification, principle. Another 160 chunk-types available for Report Documents and Scientific and Technical Reports. About 400,000 technical and business writers world-wide have been taught to write structured writing since 1969.