L
Laurence A. F. Park
Researcher at University of Sydney
Publications - 85
Citations - 1405
Laurence A. F. Park is an academic researcher from University of Sydney. The author has contributed to research in topics: Probabilistic latent semantic analysis & Ranking (information retrieval). The author has an hindex of 17, co-authored 80 publications receiving 1193 citations. Previous affiliations of Laurence A. F. Park include University of Wollongong & University of Western Sydney.
Papers
More filters
Journal ArticleDOI
An effective retinal blood vessel segmentation method using multi-scale line detection
TL;DR: The proposed method for automatically extracting blood vessels from colour retinal images is based on the fact that by changing the length of a basic line detector, line detectors at varying scales are achieved and it produces accurate segmentation on central reflex vessels while keeping close vessels well separated.
Journal ArticleDOI
Clustering ellipses for anomaly detection
Masud Moshtaghi,Timothy C. Havens,James C. Bezdek,Laurence A. F. Park,Christopher Leckie,Sutharshan Rajasegarar,James M. Keller,Marimuthu Palaniswami +7 more
TL;DR: It is concluded that focal distance is the best measure of elliptical similarity, iVAT images are a reliable basis for estimating cluster structures in sets of ellipsoids, and single linkage can successfully extract the indicated clusters.
Journal ArticleDOI
Click-based evidence for decaying weight distributions in search effectiveness metrics
TL;DR: A process for extrapolating user observations from query log clickthroughs is described, and this user model is employed to measure the quality of effectiveness weighting distributions, showing that for measures with static distributions, the geometric weighting model employed in the rank-biased precision effectiveness metric offers the closest fit to the user observation model.
Proceedings ArticleDOI
Score adjustment for correction of pooling bias
TL;DR: This paper proposes to estimate the degree of bias against an unpooled system, and to adjust the system's score accordingly, and demonstrates using resampling experiments on TREC test sets that this method leads to a marked reduction in error.
Journal ArticleDOI
A novel document retrieval method using the discrete wavelet transform
TL;DR: This work proposes a new spectral-based information retrieval method that is able to utilize many different levels of document resolution by examining the term patterns that occur in the documents, and takes advantage of the multiresolution analysis properties of the wavelet transform.