Analyzing Scientific Corpora Using Word Embedding
Autor: | Audrey Romero-Pelaez, Veronica Segarra-Faggioni |
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Rok vydání: | 2019 |
Předmět: |
Information retrieval
Word embedding Relation (database) Computer science InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Section (typography) Search engine indexing 020206 networking & telecommunications 02 engineering and technology Semantics Metadata Semantic similarity 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Word2vec |
Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030118891 ICITS |
Popis: | The bibliographic databases have abstract and citations of scientific articles, the summary being the most consulted section of an article. In order to classify and address the entries in a system of indexing and retrieval of information in the databases of a manuscript, there are keywords, which in many cases this information should not achieve greater dissemination. This paper presents an evaluation of the semantic relatedness between the abstract of scientific papers and their keywords. This analysis will be using word2vec that is a predictive model, and it will find the nearest words. Thus, this study is focused on the metadata quality assessment through the similar semantics between two words that allow the accuracy in relation to metadata of scientific databases. |
Databáze: | OpenAIRE |
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