INVESTIGADORES
MATEOS DIAZ Cristian Maximiliano
artículos
Título:
Exploiting Named Entity Recognition for Improving Syntactic-based Web Service Discovery [JCR]
Autor/es:
IGNACIO LIZARRALDE; CRISTIAN MATEOS; JUAN MANUEL RODRIGUEZ; ALEJANDRO ZUNINO
Revista:
JOURNAL OF INFORMATION SCIENCE
Editorial:
SAGE PUBLICATIONS LTD
Referencias:
Lugar: London; Año: 2018
ISSN:
0165-5515
Resumen:
Web Services have become essential to the software industry as they represent reusable, remotely-accessible functionality and data. Since Web Services must be discovered before being consumed, many discovery approaches applying classic Information Retrieval techniques, which store and process textual service descriptions, have arisen. These efforts are affected by term mismatch: a description relevant to a query can be retrieved only if they share many words. We present an approach to improve Web Service discoverability that automatically augments Web Service descriptions and can be used on top of such existing syntactic-based approaches. We exploit Named Entity Recognition to identify entities in descriptions and expand them with information from public text corpuses, e.g. Wikidata, mitigating term mismatch since it exploits both synonyms and hypernyms. We evaluated our approach together with classical syntactic-based service discovery approaches using a real 1,274-service dataset, achieving up to 15.06% better Recall scores, and up to 17% Precision-at-1, 8% Precision-at-2, and 4% Precision-at-3.