In this thesis we argue that these hierarchical relationships between entities can be exploited to facilitate common data mining tasks defined upon them, like automated classification. Specifically, we show that the information encoded in these hierarchies can be reduced to constraints on class membership scores that can then be enforced as a post-processing step to enhance the accuracy of classification. We demonstrate our ideas and algorithms on three real-world tasks.The class Car might group together the instances Honda-Civic and Ford-Mustang , and also the class Sedan. ... Even today, the use of taxonomies for organization spans the gamut of knowledge from objects as ephemeral as web- pagesanbsp;...
|Title||:||Enhanced Classification Through Exploitation of Hierarchical Structures|
|Author||:||Kunal Vinod Kumar Punera|
|Publisher||:||ProQuest - 2007|