The Classified Ad

Abstracts: Problems Classified from the User Perspective Abstracts: Problems Classified from the User Perspective

s: problems classified from the user perspective 515 Journal of Information Science, 31 (6) 2005, pp. 515–526 © CILIP, DOI: 10.1177/0165551505057014 Michela Montesi University of Amsterdam, Amsterdam, The Netherlands Blanca Gil Urdiciain Universidad Complutense de Madrid, Spain Received 3 March 2005 Revised 20 April 2005

Classified Cancer Answers

Classified information: the data clustering problem

a combination of efficiency, emissions, noise levels, and other criteria. Researchers routinely classify documents as “relevant to the current project” or “irrelevant.” Genome decoding divides chromosomes into genes, regulatory regions, signals, and so on. Pathologists identify cells as cancerous or benign. We can classify data into different groups by clustering data that are close with respec...

Information extraction for classified advertisements

1. Abstract This report describes our work on the project part of the course Language Processing and Computational Linguistics. It presents a java written program that extracts six important pieces of information from French job advertisements. The inputs of the system are advertisements taken from the internet and converted as text files. The results presented in this paper show that the extra...

Holoprosencephaly classified by computed tomography.

Five cases are presented to demonstrate the computed tomographic (CT) spectrum of holoprosencephaly. The classifications of alobar, semilobar, and lobar types A and B holoprosencephaly are each represented, with an additional case of semilobar holoprosencephaly complicated by a subdural effusion.