Stefan Pantazi | Search PubMed

PubMed2002

A new method for matching a document to potential users' information needs.

This paper explores approach to finding out how the information needs that a document can address can be captured. This is important in order to improve indexing strategies applied to document collections. We propose and implemented a cognitive science approach, the "jeopardy game" method of evaluation combined with "think aloud" analysis. The results of the demonstration study are presented and discussed. Some possible improvements to the method for matching a document to potential users' information needs are identified.

Information Storage and Retrieval↗

PubMed2002

Cluster analysis of Wisconsin Breast Cancer dataset using self-organizing maps.

This work deals with multidimensional data analysis, precisely cluster analysis applied to a very well known dataset, the Wisconsin Breast Cancer dataset. After the introduction of the topics of the paper the cluster analysis concept is shortly explained and different methods of cluster analysis are compared. Further, the Kohonen model of self-organizing maps is briefly described together with an example and with explanations of how the cluster analysis can be performed using the maps. After describing the data set and the methodology used for the analysis we present the findings using textual as well as visual descriptions and conclude that the approach is a useful complement for assessing multidimensional data and that this dataset has been overused for automated decision benchmarking purposes, without a thorough analysis of the data it contains.

Breast Neoplasms↗