@article{Sheng2010,
abstract = {As a part of the Semantic Web, Linked data is used to connect and share related data on the Web. Compared with traditional Web documents, it has following advantages: more structural; easily understood by humans; describing the things rather than documents or pages; stronger associations. For these reasons, it is more suitable for information search and data mining. In this paper, we proposed a novel approach for semantic similarity between linked data based on lexical taxonomy and corpus statistics. Our approach has been empirically tested by the linked data of Traditional Chinese Medicine (TCM). The experimental results show a good performance in finding and recommending similar herbs in TCM.},
author = {Sheng, Hao and Chen, Huajun and Yu, Tong and Feng, Yelei},
doi = {10.1109/IRI.2010.5558957},
isbn = {9781424480999},
journal = {Main},
keywords = {SML-LIB-BIBLIO,data mining,lang:ENG,linked data,semantic,semantic web,similarity},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
pages = {104--108},
publisher = {IEEE},
title = {{Linked Data based Semantic Similarity and Data Mining}},
url = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=5558957},
year = {2010}
}