Skip to Main Content
Building an Intelligent Web: Theory and Practice
book

Building an Intelligent Web: Theory and Practice

by Pawan Lingras, Rajendra Akerkar
March 2010
Intermediate to advanced content levelIntermediate to advanced
326 pages
12h 25m
English
Jones & Bartlett Learning
Content preview from Building an Intelligent Web: Theory and Practice
“4137X˙CH02˙Akerkar” 2007/9/20 10:12 page 63 #45
2.4 Evaluation of Retrieval Performance 63
R = Relevant documents A = Retrieved documents
Figure 2.42 Illustration of precision and recall measures
Here, |R|, |A|, and|R A| are the cardinalities (or size) of the sets R, A, and R A. Precision
is a measure of the accuracy of our retrieval. Higher precision implies that the probability
of a retrieved document being relevant is high. The recall, on the other hand, tells us what
percentage of documents was actually retrieved. If the recall value is closer to 1.0, we have
most of the relevant documents from the collection. Usually precision ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Reinventing the Organization for GenAI and LLMs

Reinventing the Organization for GenAI and LLMs

Ethan Mollick

Publisher Resources

ISBN: 9780763741372