Authors:
Silvia B. González Brambila
1
;
Mihaela Juganaru-Mathieu
2
and
Claudia N. González-Brambila
3
Affiliations:
1
Universidad Autónoma Metropolitana and Unidad Azcapotzalco, Mexico
;
2
Institut Henri Fayol and Ecole Nationale Supérieure des Mines de Saint Etienne, France
;
3
Instituto Tecnológico Autónomo de Mexico, Mexico
Keyword(s):
Text Mining, Analysis, Clustering, Scientific Field.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Clustering and Classification Methods
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mining Text and Semi-Structured Data
;
Symbolic Systems
Abstract:
This paper presents an exploring analysis of the research activity of a country using ISI web of Science Collection. We decided to focus the work on Mexican research in computer science. The aim of this text mining work is to extract the main direction in this scientific field. The focal exploring axe is: clustering. We have done two folds analysis: the first one on frequency representation of the extracted terms, and the second, much larger and difficult, on mining the document representations with the aim of finding clusters of documents, using the most used terms in the title. The cluster algorithms applied were hierarchical, kmeans, DIANA, SOM, SOTA, PAM, AGNES and model. Experiments with different number of terms and with the complete dataset were realized, but results were not satisfactory. We conclude that the best model for this type of analysis is model based, because it gives a better classification, but still it needs better performance algorithms. Results show that very f
ew areas are developed by Mexicans.
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