Advanced Methods for Knowledge Discovery from Complex Data

Part II: Applications

Chapter List

Chapter 8: Knowledge Discovery from Evolutionary Trees
Chapter 9: Ontology-Assisted Mining of RDF Documents
Chapter 10: Image Retrieval using Visual Features and Relevance Feedback
Chapter 11: Significant Feature Selection Using Computational Intelligent Techniques for Intrusion Detection
Chapter 12: On-board Mining of Data Streams in Sensor Networks
Chapter 13: Discovering an Evolutionary Classifier over a High-speed Nonstatic Stream

Sen Zhang and Jason T. L. Wang

Summary. In this chapter we present new techniques for discovering knowledge from evolutionary trees. An evolutionary tree is a rooted unordered labeled tree in which there is a root and the order among siblings is unimportant. The knowledge to be discovered from these trees refers to "cousin pairs" in the trees. A cousin pair is a pair of nodes sharing the same parent, the same grandparent, or the same great-grandparent, etc. Given a tree T , our algorithm finds all interesting cousin pairs of T in O( T 2) time where T is the number of nodes in T . We also extend this algorithm to find interesting cousin pairs in multiple trees. Experimental results on synthetic data and real trees demonstrate the scalability and effectiveness of the proposed algorithms. To show the usefulness of these techniques, we discuss an application of the cousin pairs to evaluate the consensus of equally parsimonious trees and compare them with the widely used clusters in the trees. We also report the implementation status of the system built based on...

UNLIMITED FREE
ACCESS
TO THE WORLD'S BEST IDEAS

SUBMIT
Already a GlobalSpec user? Log in.

This is embarrasing...

An error occurred while processing the form. Please try again in a few minutes.

Customize Your GlobalSpec Experience

Category: Lumber and Engineered Wood
Finish!
Privacy Policy

This is embarrasing...

An error occurred while processing the form. Please try again in a few minutes.