{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,9,9]],"date-time":"2022-09-09T23:06:19Z","timestamp":1662764779619},"reference-count":0,"publisher":"Ediciones Universidad de Salamanca","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ADCAIJ"],"abstract":"<jats:p>Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.<\/jats:p>","DOI":"10.14201\/adcaij20121118","type":"journal-article","created":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T10:59:59Z","timestamp":1614596399000},"page":"1-8","source":"Crossref","is-referenced-by-count":3,"title":["Applying a text mining framework to the extraction of numerical parameters from scientific literature in the biotechnology domain"],"prefix":"10.14201","volume":"1","author":[{"given":"Andr\u00e9","family":"Santos","sequence":"first","affiliation":[]},{"given":"Regina","family":"Nogueira","sequence":"additional","affiliation":[]},{"given":"An\u00e1lia","family":"Louren\u00e7o","sequence":"additional","affiliation":[]}],"member":"5351","published-online":{"date-parts":[[2013,7,1]]},"container-title":["ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal"],"original-title":[],"link":[{"URL":"https:\/\/revistas.usal.es\/index.php\/2255-2863\/article\/download\/ADCAIJ20121118\/10494","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/revistas.usal.es\/index.php\/2255-2863\/article\/download\/ADCAIJ20121118\/10494","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T11:00:00Z","timestamp":1614596400000},"score":1,"resource":{"primary":{"URL":"https:\/\/revistas.usal.es\/index.php\/2255-2863\/article\/view\/ADCAIJ20121118"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,7,1]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2012,7,1]]}},"URL":"https:\/\/doi.org\/10.14201\/adcaij20121118","relation":{},"ISSN":["2255-2863"],"issn-type":[{"value":"2255-2863","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,7,1]]}}}