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'''Semantic computing''' is a field of computing that combines elements of [[semantic analysis (knowledge representation)|semantic analysis]], [[natural language processing]], [[data mining]], [[knowledge graph]]s, and related fields.
'''Semantic computing''' is a field of computing that combines elements of [[semantic analysis (knowledge representation)|semantic analysis]], [[natural language processing]], [[data mining]], [[knowledge graph]]s, and related fields.



Revision as of 08:36, 10 April 2024

Semantic computing is a field of computing that combines elements of semantic analysis, natural language processing, data mining, knowledge graphs, and related fields.

Semantic computing addresses three core problems:

  1. Understanding the (possibly naturally-expressed) intentions (semantics) of users and expressing them in a machine-processable format
  2. Understanding the meanings (semantics) of computational content (of various sorts, including, but is not limited to, text, video, audio, process, network, software and hardware) and expressing them in a machine-processable format
  3. Mapping the semantics of user with that of content for the purpose of content retrieval, management, creation, etc.

The IEEE has held an International Conference on Semantic Computing since 2007. A conference on Knowledge Graphs and Semantic Computing has been held since 2015.[1]

See also

References

  1. ^ Zhao, Jun; Harmelen, Frank; Tang, Jie; Han, Xianpei; Wang, Quan; Li, Xianyong, eds. (2019). Knowledge Graph and Semantic Computing. Knowledge Computing and Language Understanding: Third China Conference, CCKS 2018, Tianjin, China, August 14–17, 2018, Revised Selected Papers. Communications in Computer and Information Science. Springer Singapore. ISBN 978-981-13-3145-9.