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Named Entities as Privileged Information for Hierarchical Text Clustering

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Author(s):
Sinoara, Roberta A. ; Sundermann, Camila V. ; Marcacini, Ricardo M. ; Domingues, Marcos A. ; Rezende, Solange O. ; Almeida, A ; Bernardino, J ; Gomes, EF
Total Authors: 8
Document type: Journal article
Source: PROCEEDINGS OF THE 18TH INTERNATIONAL DATABASE ENGINEERING AND APPLICATIONS SYMPOSIUM (IDEAS14); v. N/A, p. 10-pg., 2014-01-01.
Abstract

Text clustering is a text mining task which is often used to aid the organization, knowledge extraction, and exploratory search of text collections. Nowadays, the automatic text clustering becomes essential as the volume and variety of digital text documents increase, either in social networks and the Web or inside organizations. This paper explores the use of named entities as privileged information in a hierarchical clustering process, so as to improve clusters quality and interpretation. We carried out an experimental evaluation on three text collections (one written in Portuguese and two written in English) and the results show that named entities can be applied as privileged information to power clustering solution in dynamic text collection scenarios. (AU)

FAPESP's process: 13/16039-3 - Exploration of text mining techniques for automatic acquisition of contextual information for Context-Aware recommendation systems
Grantee:Camila Vaccari Sundermann
Support Opportunities: Scholarships in Brazil - Master
FAPESP's process: 13/14757-6 - Incorporating the semantics into the websensors construction process
Grantee:Roberta Akemi Sinoara
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 10/20564-8 - Unsupervised multi-view learning in incremental hierarchical clustering of text documents
Grantee:Ricardo Marcondes Marcacini
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 12/13830-9 - Automatic Acquisition of Contextual Information for Context-Aware Recommender Systems
Grantee:Marcos Aurelio Domingues
Support Opportunities: Scholarships in Brazil - Post-Doctoral