Towards Ontology Based Data Extraction for Organizational Goals Metrics Indicator
In this paper, we proposed a measurement framework to evaluate the quality of results at organizational goals level. We proposed metrics indicators to guarantee and optimize the usage of data to extract useful information in organization. The framework is flexible to change without affecting things...
| Published in: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
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Springer Science and Business Media Deutschland GmbH
2020
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092245815&doi=10.1007%2f978-3-030-58811-3_19&partnerID=40&md5=177d3723bb78d2dc2592973aad3fe2cb |
| Summary: | In this paper, we proposed a measurement framework to evaluate the quality of results at organizational goals level. We proposed metrics indicators to guarantee and optimize the usage of data to extract useful information in organization. The framework is flexible to change without affecting things around because the framework is applicable in any domains. We discuss the review of the problems, proposed solution to the problems and draw a conclusion of this paper. © 2020, Springer Nature Switzerland AG. |
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| ISSN: | 3029743 |
| DOI: | 10.1007/978-3-030-58811-3_19 |