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Title: | Why We Need an Interdisciplinary View in Information Retrieval |
Authors: | Volovici, Daniel |
Keywords: | Information Retrieval, Machine Learning, Artificial Intelligence, Statistics, Contingency Tables Research Subject Categories::INTERDISCIPLINARY RESEARCH AREAS |
Issue Date: | 11-Mar-2021 |
Publisher: | Sciendo |
Abstract: | Information Retrieval (IR) may be considered the scientific foundation of the librarians’ activity. Information retrieval(Van Rijsbergen, 1979) is the science of searching for information relevant for a need specified by a user(Volovici&Volovici, 2013). The search could be inside a document, or for finding documents. It is possible to have searching using metadata that describes data and using databases of texts. In the recent years other fields of study develop methods to find relevant information in large collection of data, especially Data Mining (DM)(Witten et al., 2011). Some such methods are inspired from IR. But the process, relevant for both domains, of finding patterns in data(Crețulescu&Morariu, 2012) (not only in texts) is covered by the academic discipline present in all curricula of Computer Science, Machine Learning (ML)(Japkowicz& Shah, 2011). |
URI: | http://hdl.handle.net/123456789/2589 |
ISBN: | 978-83-958150-6-5 |
Appears in Collections: | Proceeding ICISIL
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