{"product_id":"9780792375074","title":"Knowledge Discovery and Measures of Interest","description":"\u003ch1\u003eKnowledge Discovery and Measures of Interest\u003c\/h1\u003e \u003ch2\u003eHilderman, Robert J.; Hamilton, Howard J.\u003c\/h2\u003e \u003cp\u003e\u003cem\u003eKnowledge Discovery and Measures of Interest\u003c\/em\u003e is a  reference book for knowledge discovery researchers, practitioners, and  students. The knowledge discovery researcher will find that the  material provides a theoretical foundation for measures of interest in  data mining applications where diversity measures are used to rank  summaries generated from databases. The knowledge discovery  practitioner will find solid empirical evidence on which to base  decisions regarding the choice of measures in data mining  applications. The knowledge discovery student in a senior  undergraduate or graduate course in databases and data mining will  find the book is a good introduction to the concepts and techniques of  measures of interest.\u003cbr\u003e  In \u003cem\u003eKnowledge Discovery and Measures of Interest\u003c\/em\u003e, we study two  closely related steps in any knowledge discovery system: the  generation of discovered knowledge; and the interpretation and  evaluation of discovered knowledge. In the generation step, we study  data summarization, where a single dataset can be generalized in many  different ways and to many different levels of granularity according  to domain generalization graphs. In the interpretation and evaluation  step, we study diversity measures as heuristics for ranking the  interestingness of the summaries generated.\u003cbr\u003e  The objective of this work is to introduce and evaluate a technique  for ranking the interestingness of discovered patterns in data. It  consists of four primary goals:\u003c\/p\u003e\u003cul\u003e \u003cli\u003e To introduce  domain generalization graphs for describing and guiding the generation  of summaries from databases. \u003c\/li\u003e  \u003cli\u003e To introduce and evaluate serial  and parallel algorithms that traverse the domain generalization space  described by the domain generalization graphs.\u003c\/li\u003e  \u003cli\u003e To introduce and  evaluate diversity measures as heuristic measures of interestingness  for ranking summaries generated from databases.\u003c\/li\u003e  \u003cli\u003e To develop the  preliminary foundation for a theory of interestingness within the  context of ranking summaries generated from databases.\u003c\/li\u003e  \u003c\/ul\u003e  \u003cem\u003eKnowledge Discovery and Measures of Interest\u003c\/em\u003e is suitable as a  secondary text in a graduate level course and as a reference for  researchers and practitioners in industry. \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2001-09-30\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9780792375074\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-4757-3283-2\u003c\/p\u003e \u003cp\u003eDimensions: 235.0cm x156.0cm\u003c\/p\u003e \u003cp\u003ePages: 162.0\u003c\/p\u003e ","brand":"Springer US","offers":[{"title":"Default Title","offer_id":45578396303500,"sku":"9780792375074","price":49.49,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9780792375074.jpg?v=1767145754","url":"https:\/\/lateknightbooks.com\/products\/9780792375074","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}