| 書目名稱 | On Knowledge Base Management Systems |
| 副標題 | Integrating Artifici |
| 編輯 | Micheal L. Brodie,John Mylopoulos |
| 視頻video | http://file.papertrans.cn/702/701014/701014.mp4 |
| 叢書名稱 | Topics in Information Systems |
| 圖書封面 |  |
| 描述 | Current experimental systems in industry, government, and the military take advantage of knowledge-based processing. For example, the Defense Advanced Research Projects Agency (DARPA), and the United States Geological Survey (USGS) are supporting the develop- ment of information systems that contain diverse, vast, and growing repositories of data (e.g., vast databases storing geographic informa- tion). These systems require powerful reasoning capabilities and pro- cessing such as data processing, communications, and multidisciplinary of such systems will scientific analysis. The number and importance grow significantly in the near future. Many of these systems are severely limited by current knowledge base and database systems technology. Currently, knowledge-based system technology lacks the means to provide efficient and robust knowledge bases, while database system technology lacks knowledge representation and reasoning capabilities. The time has come to face the complex research problems that must be solved before we can design and implement real, large scale software systems that depend on knowledge-based processing. To date there has been little research directed at integrati |
| 出版日期 | Book 1986 |
| 關(guān)鍵詞 | artificial intelligence; conceptual model; control; database; database management; information system; int |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4612-4980-1 |
| isbn_softcover | 978-1-4612-9383-5 |
| isbn_ebook | 978-1-4612-4980-1Series ISSN 1431-9365 |
| issn_series | 1431-9365 |
| copyright | Springer-Verlag New York Inc. 1986 |
|Archiver|手機版|小黑屋|
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