Daya C. Wimalasuriya

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Information Extraction aims to retrieve certain types of information from natural language text by processing them automatically. For example, an information extraction system might retrieve information about geopolitical indicators of countries from a set of web pages while ignoring other types of information. Ontology-based information extraction has(More)
Information Extraction (IE) has existed as a field for several decades and has produced some impressive systems in the recent past. Despite its success, widespread usage and commercialization remain elusive goals for this field. We identify the lack of effective mechanisms for reuse as one major reason behind this situation. Here, we mean not only the reuse(More)
Our childhood eating patterns strongly affect our lifelong health. Recently, type II diabetes emerged as a national health crisis in America that can be prevented almost entirely by improving the quality of child nutrition. In this paper, we describe the scenario-based design process used to build NutriStat, a system for tracking young child nutrition for(More)
Information Extraction is the process of automatically obtaining knowledge from plain text. Because of the ambiguity of written natural language, Information Extraction is a difficult task. Ontology-based Information Extraction (OBIE) reduces this complexity by including contextual information in the form of a domain ontology. The ontology provides guidance(More)
Sinhala is one of the official languages of Sri Lanka and is used by over 19 million people. It belongs to the Indo-Aryan branch of the In-do-European languages and its origins date back to at least 2000 years. It has developed into its current form over a long period of time with influences from a wide variety of languages including Tamil, Portuguese and(More)
This paper presents a new clustering technique which is extended from the technique of clustering based on frequent-itemsets. Clustering based on frequent-itemsets has been used only in the domain of text documents and it does not consider frequency levels, which are the different levels of frequency of items in a data set. Our approach considers frequency(More)
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