Toward a Model to Evaluate Machine-Processing Quality in Scientific Documentation and Its Impact on Information Retrieval

Autor: Diana Suárez López, José María Álvarez-Rodríguez, Marvin Molina-Cardenas

Publikováno v: Applied Sciences, Vol 13, Iss 24, p 13075 (2023)

The lack of quality in scientific documents affects how documents can be retrieved depending on a user query. Existing search tools for scientific documentation usually retrieve a vast number of documents, of which only a small fraction proves releva

Externí odkaz: https://doaj.org/article/36fc402872f94a93b2ffa414ff05685a

Integrity and Quality in Universities: Accountability, Excellence and Success

Autor: Onora O'Neill

Publikováno v: Humanities, Vol 4, Iss 1, Pp 109-117 (2015)

The essay focuses on the tension between the integrity of a university’s ideal or mission (academic freedom, innovation, excellence in research and teaching) and approaches to accountability that are used to monitor performance and to establish cri

Externí odkaz: https://doaj.org/article/cd079628595940ae952f506de2625bae

Statistical Machine Translation Customization between Turkish and 11 Languages

Autor: Gökhan Doğru

Publikováno v: transLogos: Translation Studies Journal, Vol 3, Iss 1, Pp 98-121 (2020)
Volume: 3, Issue: 1 98-121
transLogos Translation Studies Journal

Statistical Machine Translation (SMT) has been the dominant corpus-based machine translation (MT) approach in the last twenty years. While SMT has been studied in detail among European languages, it has not been studied sufficiently in language pairs

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d84e7549738a4ab082aacdcc51ae7f2
https://dergipark.org.tr/en/download/article-file/1180416

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Monitoring Technical Debt in an Industrial Setting

Autor: Ioannis Stamelos, Stamatia Bibi, Apostolos Ampatzoglou, Alexander Chatzigeorgiou, Elvira-Maria Arvanitou

Publikováno v: Proceedings of the Evaluation and Assessment on Software Engineering-EASE 19
Proceedings of the Evaluation and Assessment on Software Engineering -EASE '19
Proceedings of the Evaluation and Assessment on Software Engineering
EASE

Context: Technical Debt (TD) quantification has been studied in the literature and is supported by various tools; however, there is no common ground on what information shall be presented to stakeholders. Similarly to other quality monitoring process

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9293d54a2f85d62fc093c28ed238e759