An Empirical Study on Property Clustering in Linked Data

2016 ◽  
pp. 67-82 ◽  
Author(s):  
Saisai Gong ◽  
Haoxuan Li ◽  
Wei Hu ◽  
Yuzhong Qu
Keyword(s):  
Empirical Study ◽  
Linked Data ◽  
Property Clustering

Property Clustering in Linked Data

2018 ◽  
Vol 14 (1) ◽  
pp. 31-70 ◽  
Author(s):  
Saisai Gong ◽  
Wei Hu ◽  
Haoxuan Li ◽  
Yuzhong Qu
Keyword(s):  
User Experience ◽  
Linked Data ◽  
Clustering Algorithms ◽  
Open Domain ◽  
Combination Methods ◽  
Property Clustering ◽  
Sample Set

Properties are used to describe entities, and a part of them are likely to be clustered together to constitute an aspect. For example, first name, middle name and last name are usually gathered to describe a person's name. However, existing automated approaches to property clustering remain far from satisfactory for an open domain like Linked Data. In this paper, the authors firstly investigated the relatedness between properties using 13 different measures. Then, they employed seven clustering algorithms and two combination methods for property clustering. Based on a sample set of Linked Data, the authors empirically studied property clustering in Linked Data and found that a proper combination of different measures and clustering algorithms gave rise to the best result. Additionally, they reported how property clustering can improve user experience in an entity browsing system.

Individuals without jobs: An empirical study of job-seeking behavior and reemployment.

1996 ◽  
Vol 81 (1) ◽  
pp. 76-87 ◽  
Author(s):  
Connie R. Wanberg ◽  
John D. Watt ◽  
Deborah J. Rumsey
Keyword(s):  
Empirical Study ◽  
Job Seeking ◽  
Seeking Behavior

Psychology: An empirical study of behavior.

1933 ◽  
Author(s):  
Frederick H. Lund
Keyword(s):  
Empirical Study
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