Computational trust models and machine learning
Liu, Xin (Mathematician)
Reading Time
at 250 WPM3h 52m
The average reader, reading at a speed of 250 WPM, would take 3h 52m to read Computational trust models and machine learning.
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232
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Computational trust models and machine learning
by Liu, Xin (Mathematician), Anwitaman Datta, Ee-Peng Lim
Published
2020
Publisher
Taylor & Francis Group
Pages
232
ISBN-13
9780367739331
Description
"This book provides an introduction to computational trust models from a machine learning perspective. After reviewing traditional computational trust models, it discusses a new trend of applying formerly unused machine learning methodologies, such as supervised learning. The application of various learning algorithms, such as linear regression, matrix decomposition, and decision trees, illustrates how to translate the trust modeling problem into a (supervised) learning problem. The book also shows how novel machine learning techniques can improve the accuracy of trust assessment compared to traditional approaches"--
Subjects
Frequently Asked Questions
How many pages are in Computational trust models and machine learning?
This edition of Computational trust models and machine learning has approximately 232 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.
How long does it take to read Computational trust models and machine learning?
For most readers, Computational trust models and machine learning typically takes between 4h 50m and 3h 13m to complete. This is based on the book's length of approximately 58,000 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 3h 52m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 8 days • Estimated word count: 58,000 words
Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.
What is the word count of Computational trust models and machine learning?
The estimated word count for Computational trust models and machine learning is approximately 58,000 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.
This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.
Who is the author of Computational trust models and machine learning?
Computational trust models and machine learning was written by Liu, Xin (Mathematician), Anwitaman Datta, Ee-Peng Lim.
When was Computational trust models and machine learning published?
The publication date for this specific edition is 2020. The original work may have been published on a different date.