Clustering and diversification of multi-dimensional ...

Clustering and diversification of multi-dimensional mixed structured data

Massimiliano Zanoni
DEI PhD Student

DEI - 2A Room
November 17th, 2011
5.00 pm

Abstract

Cluster Analysis is the assignment of a set of data into subsets based on some given similarity properties. The Clustering techniques have been applied in many disciplines which typically involve a large amount of complex data. My Minor research activity focus on techniques for multi-dimensional structured mixed data clustering. Considered data types are both numerical, categorical and textual. Advantages of clustering will be explored in the fields of content recommendations and of multidomain search engine results categorization and diversification. In this context, techniques for automatic semantic labeling of data clusters will be also explored.

Research area:
Signals