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Title: Semantic search architecture for retrieving information in biodiversity repositories
Authors: Amanqui, Flor K.
Serique, Kleberson J.A.
Lamping, Franco
Albuquerque, Andréa Corrêa Flôres
dos Santos, José Laurindo Campos
Moreira, Dilvan de Abreu
Keywords: Architecture
Data Integration
Search Engines
Biological Data
Keyword-based Search Engines
Mapping Mechanism
Precision And Recall
Proposed Architectures
Semantic Search
Sparql Queries
State Of The Art
Semantic Web
Issue Date: 2013
Publisher: CEUR Workshop Proceedings
metadata.dc.relation.ispartof: Volume 1041, Pags. 83-93
Abstract: The amount of biological data available electronically is increasing at a rapid rate; for instance, over 16.500 specimens are available today in the National Institute for Amazonian Research (INPA) collections. However, this data is not semantically categorized and stored and thus is difficult to search. To tackle this problem, we present a semantic search architecture, implemented using state of the art semantic web tools, and test it on a set of representative data about biodiversity from INPA. This paper describes how the mechanism of mapping is designed so that the semantic search can find information, based on ontologies. We show a series of SPARQL queries and explain how the mapping mechanism works. Our experiments, using a prototype of the proposed architecture, showed that the prototype had better precision and recall then traditional keyword based search engines.
Appears in Collections:Trabalhos Apresentados em Evento

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