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Download or read book Preface to Plato written by Eric A. HAVELOCK and published by Harvard University Press. This book was released on 2009-06-30 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: Plato's frontal attack on poetry has always been a problem for sympathetic students, who have often minimized or avoided it. Beginning with the premise that the attack must be taken seriously, Eric Havelock shows that Plato's hostility is explained by the continued domination of the poetic tradition in contemporary Greek thought. The reason for the dominance of this tradition was technological. In a nonliterate culture, stored experience necessary to cultural stability had to be preserved as poetry in order to be memorized. Plato attacks poets, particularly Homer, as the sole source of Greek moral and technical instruction-Mr. Havelock shows how the Iliad acted as an oral encyclopedia. Under the label of mimesis, Plato condemns the poetic process of emotional identification and the necessity of presenting content as a series of specific images in a continued narrative. The second part of the book discusses the Platonic Forms as an aspect of an increasingly rational culture. Literate Greece demanded, instead of poetic discourse, a vocabulary and a sentence structure both abstract and explicit in which experience could be described normatively and analytically: in short a language of ethics and science.

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Download or read book Unsupervised Learning Algorithms written by M. Emre Celebi and published by Springer. This book was released on 2016-04-29 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners. The authors outline how these algorithms have found numerous applications including pattern recognition, market basket analysis, web mining, social network analysis, information retrieval, recommender systems, market research, intrusion detection, and fraud detection. They present how the difficulty of developing theoretically sound approaches that are amenable to objective evaluation have resulted in the proposal of numerous unsupervised learning algorithms over the past half-century. The intended audience includes researchers and practitioners who are increasingly using unsupervised learning algorithms to analyze their data. Topics of interest include anomaly detection, clustering, feature extraction, and applications of unsupervised learning. Each chapter is contributed by a leading expert in the field.

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