Design of a Decision Making Model for Integrating Dark Data from Hybrid Sectors
- Title
- Design of a Decision Making Model for Integrating Dark Data from Hybrid Sectors
- Creator
- Maju S.V.; Prakasi O.S.G.
- Description
- The research on Dark data, from its definition to identification and utilization is a widely identified and encountered research problem since 2012 when Gartner defined Dark data as every possible information that an organization collects, process, analyze and store throughout regular business activities, but usually fails to make use of the stored information for other suitable purposes. The presence of dark data and its impact has been experienced by every sector, these data occupy large storage and remain unused. In this paper, we analyze Dark Data and proposed a design model to utilize dark data from multiple sectors and providing a solution to any critical situation a person might be in. For eg: Multiple cash transactions from an organizational bank account in a hospital successively over a period of 2-3 days may indicate a health emergency of any particular employee from that organization. Thus we are considering institutional data, medical data, and banking data in which machine learning algorithms can contribute huge changes in the current system and can help the decision-makers to make better decisions. The paper also proposes a few techniques and methods for the conversion of unstructured dark data to structured one and some extraction techniques for data using NLP and Machine Learning. Grenze Scientific Society, 2022.
- Source
- 13th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2022, Vol-8, pp. 705-712.
- Date
- 2022-01-01
- Publisher
- Grenze Scientific Society
- Subject
- Dark data; Electronic Health Record; Entity based Recognition; Natural Language Processing
- Coverage
- Maju S.V., Computer Science and Engineering Department, Christ (Deemed to be University), Bangalore, India; Prakasi O.S.G., Computer Science and Engineering Department, Christ (Deemed to be University), Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-171385793-8
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Maju S.V.; Prakasi O.S.G., “Design of a Decision Making Model for Integrating Dark Data from Hybrid Sectors,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/20213.