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DAI for Document Retrieval
| Content Provider | Scilit |
|---|---|
| Author | Kumar, Anuj Yadav, Satya Prakash Mittal, Sugandha |
| Copyright Year | 2020 |
| Description | The issue of storing and retrieving information has attracted growing attention since the 1940s. One consequence of this is that sensitive knowledge is overlooked because it is never revealed, which in turn results in a lot of research and effort duplication. Computers have effectively taken over a few of the more ordinary assignments, such as cataloging and common organization in libraries, and many of these computers have data capacity and recovery issues. The point of a computerized retrieval procedure is to recover exceptionally significant archives while recovering as not many as conceivable this thought is at the center of data retrieval. We need to build a model in which to quantify appropriate decisions for a computer to do this. Most information retrieval research has been concerned with different aspects of such a model. Book Name: Distributed Artificial Intelligence |
| Related Links | https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781003038467-15&type=chapterpdf |
| Ending Page | 262 |
| Page Count | 12 |
| Starting Page | 251 |
| DOI | 10.1201/9781003038467-15 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2020-12-17 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Distributed Artificial Intelligence Build Information Retrieval Exceptionally Cataloging Ordinary Conceivable Libraries Lot Computerized Taken |
| Content Type | Text |
| Resource Type | Chapter |