| 书目名称 | MDATA: A New Knowledge Representation Model | | 副标题 | Theory, Methods and | | 编辑 | Yan Jia,Zhaoquan Gu,Aiping Li | | 视频video | | | 概述 | Introduces a new knowledge representation model called MDATA.Explores some key technologies of the MDATA model.Written by experts in the field | | 丛书名称 | Lecture Notes in Computer Science | | 图书封面 |  | | 描述 | Knowledge representation is an important task in understanding how humans think and learn. Although many representation models or cognitive models have been proposed, such as expert systems or knowledge graphs, they cannot represent procedural knowledge, i.e., dynamic knowledge, in an efficient way..This book introduces a new knowledge representation model called MDATA (Multi-dimensional Data Association and inTelligent Analysis). By modifying the representation of entities and relations in knowledge graphs, dynamic knowledge can be efficiently described with temporal and spatial characteristics. The MDATA model can be regarded as a high-level temporal and spatial knowledge graph model, which has strong capabilities for knowledge representation. This book introduces some key technologies in the MDATA model, such as entity recognition, relation extraction, entity alignment, and knowledge reasoning with spatiotemporal factors. The MDATA model can be applied in many critical applications and this book introduces some typical examples, such as network attack detection, social network analysis, and epidemic assessment...The MDATA model should be of interest to readers from many research | | 出版日期 | Book 2021 | | 关键词 | artificial intelligence; cognitive model; data mining; databases; entity alignment; entity recognition; in | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-71590-8 | | isbn_softcover | 978-3-030-71589-2 | | isbn_ebook | 978-3-030-71590-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 | | issn_series | 0302-9743 | | copyright | Springer Nature Switzerland AG 2021 |
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发表于 2025-3-21 19:07:36
