Clustering of Spatial Data for Knowledge Extraction

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Martins, ES (Author) Other; Ribeiro, M (Author) Other; Lisboa Filho, J (Author) Other; Reinaldo, F (Author) Other; Freddo, A (Author) Other; reis, lp (Author) REIT

Conference proceedings International

Title: 11a Conferencia Ibérica de Sistemas y Tecnologías de Información

Indexing

ISI Web of Knowledge - 0 Citations

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Other information

Authenticus ID: P-00K-S8Q

DOI: 10.1109/cisti.2016.7521626

Abstract (EN): Spatial Data Infrastructures (SDI) are repositories of large volumes of data, documented through standardized metadata. Data mining is one of the main techniques used to extract knowledge from large amounts of data, because of its versatility. The purpose of this article is to use clustering techniques and data mining to extract relationships and knowledge from metadata in SDI. For this reason, knowledge discovery techniques, clustering, text mining and data mining algorithms were used. In order to demonstrate the effectiveness of the proposed method, a case study was implemented to evaluate the performance of data mining techniques in this type of database. The results showed that the data mining process and clustering techniques guided to the classification proposed method for extracting relations and knowledge from a group of metadata extracted from within the database.

Language: Portuguese

Type (Professor's evaluation): Scientific

No. of pages: 6