Big Data Knowledge Service Framework based on Knowledge Fusion

Fei Wang, Hao Fan, Gang Liu

2016

Abstract

In big data environments, knowledge fusion is the necessary prerequisite and effective approach to implement knowledge service. This paper firstly analyses the requirements of big data knowledge service and the contents of knowledge fusion, constructs a multi-level architecture of knowledge service based on knowledge fusion. Then, this paper presents a design of a knowledge fusion process model and analyses its implementation patterns. Finally, a system framework of big data knowledge service is proposed based on knowledge fusion processes, in which processes of both knowledge fusion and knowledge service are organically combined together to provide an effective solution to achieve personalized, multi-level and innovative knowledge service.

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Paper Citation


in Harvard Style

Wang F., Fan H. and Liu G. (2016). Big Data Knowledge Service Framework based on Knowledge Fusion . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS, (IC3K 2016) ISBN 978-989-758-203-5, pages 116-123. DOI: 10.5220/0006036301160123


in Bibtex Style

@conference{kmis16,
author={Fei Wang and Hao Fan and Gang Liu},
title={Big Data Knowledge Service Framework based on Knowledge Fusion},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS, (IC3K 2016)},
year={2016},
pages={116-123},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006036301160123},
isbn={978-989-758-203-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS, (IC3K 2016)
TI - Big Data Knowledge Service Framework based on Knowledge Fusion
SN - 978-989-758-203-5
AU - Wang F.
AU - Fan H.
AU - Liu G.
PY - 2016
SP - 116
EP - 123
DO - 10.5220/0006036301160123