Samuel W. K. Chan

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Discourse markers foreshadow the message thrust of texts and saliently guide their rhetorical structure which are important for content filtering and text abstraction. This paper reports on efforts to automatically identify and classify discourse markers in Chinese texts using heuristic-based and corpus-based data-mining methods, as an integral part of(More)
Recent trials of drug therapy targeting the erbB receptor HER2 have met with success in breast cancer. The epidermal growth factor receptor or EGFR is a closely related receptor from this same family that is involved in cellular signal transduction and tumor cell growth and survival. Emerging evidence indicates that EGFR is implicated in the development of(More)
The HER3 protein contributes to malignant transformation in breast and other cancer types as a consequence of elevated levels of expression, particularly in the presence of the HER2 protein. We show here that an antibody, called SGP1, to the extracellular domain of the HER3 receptor can inhibit completely Neuregulin stimulated growth of cultured breast(More)
BACKGROUND Chronic rhinosinusitis (CRS) with or without polyps is a common chronic upper airway condition of multifactorial origin. Fundamental to effective treatment of any infection is the ability to accurately characterize the underlying cause. Many studies have shown that only a small fraction of the total range of bacterial species present in CRS is(More)
Natural language understanding involves the simultaneous consideration of a large number of different sources of information. Traditional methods employed in language analysis have focused on developing powerful formalisms to represent syntactic or semantic structures along with rules for transforming language into these formalisms. However, they make use(More)
We describe a comprehensive framework for text understanding, based on the representation of context. It is designed to serve as a representation of semantics for the full range of interpretive and inferential needs of general natural language processing. Its most distinctive feature is its uniform representation of the various simple and independent(More)
With the explosion in the quantity of on-line text and multimedia information in recent years, there has been a renewed interest in the automated extraction of knowledge and information in various disciplines. In this paper, we provide a novel quantitative model for the creation of a summary by extracting a set of sentences that represent the most salient(More)