عنوان
پدید آورنده
موضوع
رده
کتابخانه
محل استقرار
شابک
شابک
9781441949134
شابک
9781475732832
شماره کتابشناسی ملی
شماره
b402345
عنوان و نام پديدآور
عنوان اصلي
Knowledge Discovery and Measures of Interest
نام عام مواد
[Book]
نام نخستين پديدآور
by Robert J. Hilderman, Howard J. Hamilton.
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
Boston, MA :
نام ناشر، پخش کننده و غيره
Imprint: Springer,
تاریخ نشرو بخش و غیره
2001.
فروست
عنوان فروست
Springer International Series in Engineering and Computer Science,
مشخصه جلد
638
شاپا ي ISSN فروست
0893-3405 ;
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
Knowledge Discovery and Measures of Interest 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. In Knowledge Discovery and Measures of Interest, 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. 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: To introduce domain generalization graphs for describing and guiding the generation of summaries from databases. To introduce and evaluate serial and parallel algorithms that traverse the domain generalization space described by the domain generalization graphs. To introduce and evaluate diversity measures as heuristic measures of interestingness for ranking summaries generated from databases. To develop the preliminary foundation for a theory of interestingness within the context of ranking summaries generated from databases. Knowledge Discovery and Measures of Interest is suitable as a secondary text in a graduate level course and as a reference for researchers and practitioners in industry.
ویراست دیگر از اثر در قالب دیگر رسانه
شماره استاندارد بين المللي کتاب و موسيقي
9781441949134
قطعه
عنوان
Springer eBooks
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Artificial intelligence.
موضوع مستند نشده
Computational complexity.
موضوع مستند نشده
Computer science.
موضوع مستند نشده
Data structures (Computer science).
موضوع مستند نشده
Information theory.
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )
مستند نام اشخاص تاييد نشده
Hilderman, Robert J.
نام شخص - (مسئولیت معنوی برابر )
مستند نام اشخاص تاييد نشده
Hamilton, Howard J.
نام تنالگان _ (مسئولیت معنوی برابر)
مستند نام تنالگان تاييد نشده
SpringerLink (Online service)
مبدا اصلی
تاريخ عمليات
20190307154800.0
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب اطلاعات رکورد کتابشناسی
نوع ماده
[Book]
اطلاعات دسترسی رکورد
تكميل شده
Y
