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Robert W. P. Luk
Researcher at Hong Kong Polytechnic University
Publications - 116
Citations - 2080
Robert W. P. Luk is an academic researcher from Hong Kong Polytechnic University. The author has contributed to research in topics: Vector space model & Relevance (information retrieval). The author has an hindex of 18, co-authored 114 publications receiving 1901 citations. Previous affiliations of Robert W. P. Luk include Applied Science Private University & University of Southampton.
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Interpreting TF-IDF term weights as making relevance decisions
TL;DR: A novel probabilistic retrieval model forms a basis to interpret the TF-IDF term weights as making relevance decisions, and it is shown that the term-frequency factor of the ranking formula can be rendered into different term- frequency factors of existing retrieval systems.
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An evolutionary approach to pattern-based time series segmentation
TL;DR: An evolutionary time series segmentation algorithm that allows a sizeable set of pattern templates to be generated for mining or query by identifying the perceptually important points directly from the time domain and which can be compared and intuitive pattern matching can be carried out in an effective and efficient manner.
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Stock time series pattern matching: Template-based vs. rule-based approaches
TL;DR: Three ways of distance measure, including Euclidean distance, perpendicular distance and vertical distance, for PIP identification are compared and both template- and rule-based pattern-matching approaches are introduced, making them particularly user friendly to ordinary data analysts like stock market investors.
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A survey in indexing and searching XML documents
TL;DR: This article surveys several indexing techniques for XML documents, grouping them into flat-file, semistructured, and structured indexing paradigms, and discusses various open issues that XML poses with respect to information retrieval and database research.
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Representing financial time series based on data point importance
TL;DR: Different data point importance evaluation methods, a new updating method and two dimensionality reduction approaches are proposed and evaluated by a series of experiments and the application of the proposed representation on mobile environment is demonstrated.