A novel method on information recommendation via hybrid similarity
Document Type
Article
Publication Date
3-1-2018
Abstract
Link similarity is widely applied in measuring the similarity between such objects as Web pages, scientific papers, and social networks. However, there are some deficiencies in the existing methods to measure it. For example, they cannot handle some semantic-similar contents. Their computation may not lead to accurate results in some cases. This paper presents a novel method to do so. It introduces the semantic similarity to calculate the similarity between two given objects, and overcomes the drawback caused by the fact that the existing methods ignore the semantic information of objects. It also gives a novel computation function to make the computing result of similarity more accurate.
Identifier
85044577256 (Scopus)
Publication Title
IEEE Transactions on Systems Man and Cybernetics Systems
External Full Text Location
https://doi.org/10.1109/TSMC.2016.2633573
e-ISSN
21682232
ISSN
21682216
First Page
448
Last Page
459
Issue
3
Volume
48
Grant
16YF1400300
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Zhao, Qin; Wang, Cheng; Wang, Pengwei; Zhou, Mengchu; and Jiang, Changjun, "A novel method on information recommendation via hybrid similarity" (2018). Faculty Publications. 8832.
https://digitalcommons.njit.edu/fac_pubs/8832
