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Author(s): Coelho, J.
Neto, A.
Tavares, M.
Coutinho, C.
Ribeiro, R.
Batista, F.
Editor: Queirós. R., Pinto, M., Simões, A., Portela, F., & Pereira, M. J.
Date: 2021
Title: Semantic search of mobile applications using word embeddings
Volume: 94
Event title: 10th Symposium on Languages, Applications and Technologies, SLATE 2021
ISSN: 2190-6807
ISBN: 978-3-95977-202-0
DOI (Digital Object Identifier): 10.4230/OASIcs.SLATE.2021.12
Keywords: Semantic search
Word embeddings
Mobile applications
Abstract: This paper proposes a set of approaches for the semantic search of mobile applications, based on their name and on the unstructured textual information contained in their description. The proposed approaches make use of word-level, character-level, and contextual word-embeddings that have been trained or fine-tuned using a dataset of about 500 thousand mobile apps, collected in the scope of this work. The proposed approaches have been evaluated using a public dataset that includes information about 43 thousand applications, and 56 manually annotated non-exact queries. Our results show that both character-level embeddings trained on our data, and fine-tuned RoBERTa models surpass the performance of the other existing retrieval strategies reported in the literature.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:ISTAR-CRI - Comunicações a conferências internacionais

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