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<Paper uid="W02-1102">
  <Title>Induction of Classification from Lexicon Expansion : Assigning Domain Tags to WordNet Entries</Title>
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Abstract
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    <Paragraph position="0"> We present in this paper a series of induced methods to assign domain tags to WordNet entries. Our prime objective is to enrich the contextual information in WordNet specific to each synset entry. By using the available lexical sources such as Far East Dictionary and the contextual information in WordNet itself, we can find a foundation upon which we can base our categorization. Next we further examine the similarity between common lexical taxonomy and the semantic hierarchy of WordNet. Based on this observation and the knowledge of other semantic relations we enlarge the coverage of our findings in a systematic way. Evaluation of the results shows that we achieved reasonable and satisfactory accuracy. We propose this as the first step of wordnet expansion into a bona fide semantic network linked to real-world knowledge.</Paragraph>
    <Paragraph position="1"> 0. Introduction1 WordNet is a lexicon comprising of nouns, verbs, adjectives and adverbs. Its basic 1 This research is partially funded by an IDLP project grant from the National Science Council of Taiwan, ROC. Work reported in this paper was carried out in summer 2001, during Chang's internship at Academia Sinica. We are indebted to two anonymous reviewers of SemaNet 2002, as well as from the First International WordNet Conference for their helpful comments. An earlier version of this paper was accepted by the first IWC but was not presented because of the authors' travelling difficulties at that time. We thank colleagues at Academia Sinica, especially Shu-Chuan Tseng, Keh-jiann Chen, and members of the WordNet group, for their input and help.</Paragraph>
    <Paragraph position="2"> organization is based on different semantic relations among the words. Entries (or lemas) sharing the same meaning is grouped into a synset and assigned with a unique sense identification number for easy retrieval and tracking purposes. This unique offset number gives the information about the parts of speech and the hierarchy position to which a specific synset belongs. For nouns and verbs the synsets are grouped into multiple lexical hierarchies; modifiers such as adjectives and adverbs are simply &amp;quot;organized into clusters on the basis of binary opposition (antinomy).&amp;quot; [1] This lexical hierarchy makes the lexical domain assigning task more straightforward because it coincides with a ontological taxonomy in many aspects. The primary objective of our project is to enrich the WordNet knowledge content due to the fact that &amp;quot;WordNet lacks relations between related concepts.&amp;quot; [2] We adopt WordNet itself, together with other lexical resources to develop an integrated domain specific lexical resource.</Paragraph>
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