Knowledge Representation Structure for Cloud Platforms: SUMMUS Semantic Encoding Forest

DOI

10.2991/aiie-15.2015.82How to use a DOI?

Keywords

knowledge representation; big data; cloud platform; semantic encoding forest

Abstract

Big data era, modern knowledge representation structures do not have appropriate structural support for parallel computing, unable to meet the time requirements of large data processing. We proposed one knowledge representation structure for cloud platform called SUMMUS Semantic Encoding Forest. Through semantic concept further fine-grained decomposition to achieve a unified representation of semantic relations and make binary semantic content-based encoding, then from structure level support parallel computing of semantic reasoning. This structure have better capabilities than the traditional knowledge represent structure at easy programming, complexity of rules and better structural etc. aspects. The time complexity of knowledge reasoning is limited to O (n). Experiments show that knowledge inference time of SUMMUS Semantic Encoding Forest do not obviously increased with the consumption of entities' or events' number of conflicts linearly increase, time performance is better than other existing knowledge representation structures.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - S.S. Xie
AU  - Y. Tang
AU  - Z.X. Miao
AU  - L. Sun
AU  - Y. He
PY  - 2015/07
DA  - 2015/07
TI  - Knowledge Representation Structure for Cloud Platforms: SUMMUS Semantic Encoding Forest
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 294
EP  - 296
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.82
DO  - 10.2991/aiie-15.2015.82
ID  - Xie2015/07
ER  -