Mong Li Lee
Email Address
dcsleeml@nus.edu.sg
Organizational Units
SPECIALTY RESEARCH INST/CTRS
faculty
COMPUTING
faculty
151 results
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Publication A framework for mining topological patterns in spatio-temporal databases(2005) Wang, J.; Hsu, W.; Lee, M.L.; COMPUTER SCIENCEMining topological patterns in spatial databases has received a lot of attention. However, existing work typically ignores the temporal aspect and suffers from certain efficiency problems. They are not scalable for mining topological patterns in spatio-temporal databases. In this paper, we study the problem for mining topological patterns by incorporating the temporal aspect in the mining process. We introduce a summary-structure that records the instances' count information of a feature in a region within a time window. Using this structure, we design an algorithm, TopologyMiner, to find interesting topological patterns without the need to generate candidates. Experimental results show that TopologyMiner is effective and scalable in finding topological patterns and outperforms Apriori-like algorithm by a few orders of magnitudes. Copyright 2005 ACM.Publication ERkNN: Efficient Reverse k-Nearest Neighbors retrieval with local kNN-distance estimation(2005) Xia, C.; Hsu, W.; Lee, M.L.; COMPUTER SCIENCEThe Reverse k-Nearest Neighbors (RkNN) queries are important in profile-based marketing, information retrieval, decision support and data mining systems. However, they are very expensive and existing algorithms are not scalable to queries in high dimensional spaces or of large values of k. This paper describes an efficient estimation-based RkNN search algorithm (ERkNN) which answers RkNN queries based on local kNN-distance estimation methods. The proposed approach utilizes estimation-based filtering strategy to lower the computation cost of RkNN queries. The results of extensive experiments on both synthetic and real life datasets demonstrate that ERkNN algorithm retrieves RkNN efficiently and is scalable with respect to data dimensionality, k, and data size. Copyright 2005 ACM.Publication A novel PIM system and its effective storage compression scheme(2012) Yang, L.H.; Zhou, J.; Wang, J.; Lee, M.L.; COMPUTER SCIENCEThe increasingly large amount of personal information poses a critical problem to users. Traditional file organization in hierarchical directories is not suited to the effective management of personal information. In order to overcome the shortcomings of the current hierarchical file system and efficiently organize and maintain personal information, some new tools are expected to be invented. In this paper, we propose a novel scheme called concept space - a network of concepts and their associations - and use topic map as the underlying data model. We present a materialized view scheme to provide users with a flexible view of the file system according to their own cognition. We also reduce the storage requirement to save space usage of this system by borrowing some ideas from XML data management and contriving a novel and efficient data compression scheme. To demonstrate the effectiveness of the above idea, we have implemented a prototype personal information management system called NovaPIM and presented its system architecture. Extensive experiments show that our proposed scheme is both efficient and effective. © 2012 ACADEMY PUBLISHER.Publication Mining dense periodic patterns in time series data(2006) Sheng, C.; Mong, W.H.; Lee, L.; COMPUTER SCIENCEExisting techniques to mine periodic patterns in time series data are focused on discovering full-cycle periodic patterns from an entire time series. However, many useful partial periodic patterns are hidden in long and complex time series data. In this paper, we aim to discover the partial periodicity in local segments of the time series data. We introduce the notion of character density to partition the time series into variable-length fragments and to determine the lower bound of each character's period. We propose a novel algorithm, called DPMiner, to find the dense periodic patterns in time series data. Experimental results on both synthetic and real-life datasets demonstrate that the proposed algorithm is effective and efficient to reveal interesting dense periodic patterns. © 2006 IEEE.Publication Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study(Elsevier Ltd, 2020) Xie, Y.; Nguyen, Q.D.; Hamzah, H.; Lim, G.; Bellemo, V.; Gunasekeran, D.V.; Yip, M.Y.T.; Qi Lee, X.; Hsu, W.; Li Lee, M.; Tan, C.S.; Tym Wong, H.; Lamoureux, E.L.; Tan, G.S.W.; Wong, T.Y.; Finkelstein, E.A.; Ting, D.S.W.; DEPARTMENT OF COMPUTER SCIENCEBackground: Deep learning is a novel machine learning technique that has been shown to be as effective as human graders in detecting diabetic retinopathy from fundus photographs. We used a cost-minimisation analysis to evaluate the potential savings of two deep learning approaches as compared with the current human assessment: a semi-automated deep learning model as a triage filter before secondary human assessment; and a fully automated deep learning model without human assessment. Methods: In this economic analysis modelling study, using 39 006 consecutive patients with diabetes in a national diabetic retinopathy screening programme in Singapore in 2015, we used a decision tree model and TreeAge Pro to compare the actual cost of screening this cohort with human graders against the simulated cost for semi-automated and fully automated screening models. Model parameters included diabetic retinopathy prevalence rates, diabetic retinopathy screening costs under each screening model, cost of medical consultation, and diagnostic performance (ie, sensitivity and specificity). The primary outcome was total cost for each screening model. Deterministic sensitivity analyses were done to gauge the sensitivity of the results to key model assumptions. Findings: From the health system perspective, the semi-automated screening model was the least expensive of the three models, at US$62 per patient per year. The fully automated model was $66 per patient per year, and the human assessment model was $77 per patient per year. The savings to the Singapore health system associated with switching to the semi-automated model are estimated to be $489 000, which is roughly 20% of the current annual screening cost. By 2050, Singapore is projected to have 1 million people with diabetes; at this time, the estimated annual savings would be $15 million. Interpretation: This study provides a strong economic rationale for using deep learning systems as an assistive tool to screen for diabetic retinopathy. Funding: Ministry of Health, Singapore. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licensePublication Mining progressive confident rules(2006) Zhang, M.; Hsu, W.; Lee, M.L.; COMPUTER SCIENCEMany real world objects have states that change over time. By tracking the state sequences of these objects, we can study their behavior and take preventive measures before they reach some undesirable states. In this paper, we propose a new kind of pattern called progressive confident rules to describe sequences of states with an increasing confidence that lead to a particular end state. We give a formal definition of progressive confident rules and their concise set. We devise pruning strategies to reduce the enormous search space. Experiment result shows that the proposed algorithm is efficient and scalable. We also demonstrate the application of progressive confident rules in classification. Copyright 2006 ACM.Publication Constrained-MSER detection of retinal pathology(2012) San, G.L.Y.; Lee, M.L.; Hsu, W.; COMPUTER SCIENCEWith the increase in age and diabetes-related eye diseases, there is a rising demand for systems which can efficiently screen and locate abnormalities in retinal images. In this paper, we propose a framework that utilizes a variant of the Maximally Stable Extremal Region method, termed C-MSER, to systematically detect various retinopathy pathologies such as microaneurysms, haemorrhages, hard exudates and soft exudates. Experiments on three real-world datasets show that C-MSER is effective for online screening of diabetic retinopathy. © 2012 ICPR Org Committee.Publication A path-based labeling scheme for efficient structural join(2005) Li, H.; Lee, M.L.; Hsu, W.; COMPUTER SCIENCEThe structural join has become a core operation in XML query processing. This work examines how path information in XML can be utilized to speed up the structural join operation. We introduce a novel approach to pre-filter path expressions and identify a minimal set of candidate elements for the structural join. The proposed solution comprises of a path-based node labeling scheme and a path join algorithm. The former associates every node in an XML document with its path type, while the latter greatly reduces the cost of subsequent element node join by filtering out elements with irrelevant path types. Comparative experiments with the state-of-the-art holistic join algorithm clearly demonstrate that the proposed approach is efficient and scalable for queries ranging from simple paths to complex branch queries. © Springer-Verlag Berlin Heidelberg 2005.Publication Retinal vascular fractal dimension and its relationship with cardiovascular and ocular risk factors(2012) Cheung, C.Y.; Thomas, G.N.; Tay, W.; Ikram, M.K.; Hsu, W.; Lee, M.L.; Lau, Q.P.; Wong, T.Y.; DUKE-NUS GRADUATE MEDICAL SCHOOL S'PORE; OPHTHALMOLOGY; COMPUTER SCIENCEPurpose: To examine the influence of a range of cardiovascular risk factors and ocular conditions on retinal vascular fractal dimension in the Singapore Malay Eye Study. Design: Population-based cross-sectional study. Methods: Fractal analysis of the retinal vessels is a method to quantify the global geometric complexity of the retinal vasculature. Retinal vascular fractal dimension (Df) and caliber were measured from retinal photographs using a computer-assisted program. Df and arteriolar caliber were combined to form a retinal vascular optimality score (ranging from 0 to 3). Data on cardiovascular and ocular factors were collected from all participants based on a standardized protocol. Results: Two thousand nine hundred thirteen (88.8% of 3280 participants) persons had retinal photographs of sufficient quality for the measurement. The mean Df was 1.405 (standard deviation, 0.046; interquartile range, 1.243 to 1.542). In the multiple linear regression analysis, after controlling for gender, serum glucose, intraocular pressure, anterior chamber depth, and retinal vascular caliber, smaller Df was associated independently with older age (standardized regression coefficient [sβ] = -0.311; P <.001), higher mean arterial blood pressure (sβ = -0.085; P <.001), a more myopic spherical equivalent (sβ = 0.152; P <.001), and presence of cataract (sβ = -0.107; P <.001). Retinal vascular optimality score was associated significantly with higher mean arterial blood pressure (P >.001 for trend). Conclusions: Age, blood pressure, refractive error, and lens opacity had significant influence on retinal vascular fractal measurements. A new score of retinal vascular optimality combining fractals and caliber showed strong association with blood pressure. Quantitative analysis of retinal vasculature therefore may provide additional information on microvascular architecture and optimality. © 2012 Elsevier Inc.Publication A path-based approach for efficient structural join with not-predicates(2007) Li, H.; Lee, M.L.; Hsu, W.; Li, L.; COMPUTER SCIENCEThere has been much research on XML query processing. However, there has been little work on the evaluation of XML queries involving not-predicates. Such queries are useful and common in many real-life applications. In this paper, we present a model called XQuery tree to model queries involving not-predicates and describe a path-based method to evaluate such queries efficiently. A comprehensive set of experiments is carried out to demonstrate the effectiveness and efficiency of the proposed solution. © Springer-Verlag Berlin Heidelberg 2007.