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{ "item_title" : "N-ary Relations for Logical Analysis of Data and Knowledge", "item_author" : [" Boris Kulik", "Alexander Fridman "], "item_description" : "Mathematics has been used as a tool in logistical reasoning for centuries. Examining how specific mathematic structures can aid in data and knowledge management helps determine how to efficiently and effectively process more information in these fields. N-ary Relations for Logical Analysis of Data and Knowledge is a critical scholarly reference source that provides a detailed study of the mathematical techniques currently involved in the progression of information technology fields. Featuring relevant topics that include algebraic sets, deductive analysis, defeasible reasoning, and probabilistic modeling, this publication is ideal for academicians, students, and researchers who are interested in staying apprised of the latest research in the information technology field.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/52/252/782/1522527826_b.jpg", "price_data" : { "retail_price" : "225.00", "online_price" : "225.00", "our_price" : "225.00", "club_price" : "225.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
N-ary Relations for Logical Analysis of Data and Knowledge|Boris Kulik

N-ary Relations for Logical Analysis of Data and Knowledge

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Overview

Mathematics has been used as a tool in logistical reasoning for centuries. Examining how specific mathematic structures can aid in data and knowledge management helps determine how to efficiently and effectively process more information in these fields. N-ary Relations for Logical Analysis of Data and Knowledge is a critical scholarly reference source that provides a detailed study of the mathematical techniques currently involved in the progression of information technology fields. Featuring relevant topics that include algebraic sets, deductive analysis, defeasible reasoning, and probabilistic modeling, this publication is ideal for academicians, students, and researchers who are interested in staying apprised of the latest research in the information technology field.

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Details

  • ISBN-13: 9781522527824
  • ISBN-10: 1522527826
  • Publisher: Information Science Reference
  • Publish Date: November 2017
  • Dimensions: 10 x 7 x 0.75 inches
  • Shipping Weight: 1.71 pounds
  • Page Count: 334

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