Towards open data discovery: a comparative study
Authors: 
Maria Helena Franciscatto, Marcos Didonet Del Fabro, Celio Trois, Hegler TissotAuthors Info & Claims
Maria Helena Franciscatto, Marcos Didonet Del Fabro, Celio Trois, Hegler TissotAuthors Info & ClaimsPages 713 - 716
Abstract
Open Data discovery enables the retrieval of data sources most likely to contain the information needed, facilitating data access and transparency. This work presents a comparative study involving three different methods: a hybrid algorithm based on Linear Discriminant Analysis and Word2Vec, Cosine similarity measure, and a Semantic Test proposed for Open Data search. Each method was evaluated on its ability to discover, among eight open datasets, using only their metadata and descriptions, the most likely one to meet an input question. Three evaluation rounds were performed with different sets of questions and databases, showing a classification accuracy above 81% for all methods.
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- Towards open data discovery: a comparative study
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Published In
April 2022
2099 pages
ISBN:9781450387132
DOI:10.1145/3477314
- Conference Chairs:
- Jiman Hong,
- Miroslav Bures,
- Program Chairs:
- Juw Won Park,
- Tomas Cerny
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Published: 06 May 2022
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- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES)
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SAC '22
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