TY  - GEN
UR  - http://gisruk.org/proceedings.html
TI  - Trip purpose identification using pairwise constraints based semi-supervised clustering
KW  - Trip purposes
KW  -  smart card data
KW  -  COP-KMEANS
KW  -  semi-supervised clustering
ID  - discovery10127905
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
AV  - public
N2  - Clustering of smart card data captured by automated fare collection (AFC) systems has traditionally
been viewed as an unsupervised method. However,some additional information about human behaviour
is available in addition to the smart card data points that can facilitate better partitioning of the data. In
this paper, such prior knowledge is translated into pairwise constraints and used with the COPKMEANS clustering algorithm to identify user activities. The effectiveness of the method was
evaluated using performance evaluation measures by comparison of the results with the ground truth.
The results demonstrate that pairwise constraints significantly enhance the accuracy of the clusters.
PB  - GISRUK
A1  - Sari Aslam, N
A1  - Cheng, T
A1  - Cheshire, J
A1  - Zhang, Y
Y1  - 2019///
ER  -