Automatic Text Standardisation by Synonym Mapping

Automatic Text Standardisation by Synonym Mapping

9 Pages · 2011 · 293 KB · English

Automatic Text Standardisation by Synonym Mapping Stella Asiimwe1, Susan Craw1, Nirmalie Wiratunga1, and Bruce Taylor2 1 School of Computing 2 The Scott Sutherland School

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Automatic Text Standardisation by Synonym MappingStella Asiimwe 1 , Susan Craw 1 , Nirmalie Wiratunga 1 , and Bruce Taylor 2 1 School of Computing 2 The Scott Sutherland School The Robert Gordon University, Aberdeen, Scotland, UK { sa, smc, nw }@comp.rgu.ac.uk ,[email protected] Abstract. Creating a case-based reasoning system from textual sources is chal- lenging because it requires that the text be interpreted in a meaningful wa y in order to create cases and interprete queries during problem-solving. H owever, this is only possible if a domain-specic conceptual model is available and if the different meanings that words can take, can be recognised in the text. T his paper presents an unsupervised methodology for text harmonisation in order to create a standard conceptual model of the domain, and for query interpretation . The main core of this technique is the disambiguation of each polysemous word in ord er to represent all synonyms of a particular word, with one common word. The al- gorithm for Word Sense Disambiguation relies on the syntactic structure of th e sentence in which the target word resides to obtain the context. It does not rely on large amounts of hand-crafted knowledge or statistical data from the c orpus, but makes use of two other knowledge sources, namely WordNet and G oogle. Preliminary results are promising when the algorithm is tested on documents in the SmartHouse domain. Keywords: Word Sense Disambiguation, text harmonisation 1 Introduction Designing a case-based reasoning system can be challenging when the problem-solving experiences are captured as text. This is because the text ha s to be interpreted in a meaningful way in order to create cases that are useful for pr oblem-solving. However, correct interpretation of text is only possible if the domai n is familiar to the reader, otherwise, they will either misinterpret or, not understan d, what they read. Consider a construction worker who encounters the word mortarwhilst reading a cookery book. Unless they have knowledge of the domain, they will take

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