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<Paper uid="P97-1010">
  <Title>Homonymy and Polysemy in Information Retrieval</Title>
  <Section position="3" start_page="0" end_page="0" type="metho">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> Lexical ambiguity is a fundamental problem in natural language processing, but relatively little quantitative information is available about the extent of the problem, or about the impact that it has on specific applications. We report on our experiments to resolve lexical ambiguity in the context of information retrieval (IR). Our approach to disambiguation is to treat the information associated with dictionary This paper is based on work that was done at the Center for Intelligent Information Retrieval at the University of Massachusetts. It was supported by the National Science Foundation, Library of Congress, and Department of Commerce raider cooperative agreement number EEC-9209623. I am grateful for their support.</Paragraph>
    <Paragraph position="1"> senses (morphology. part of speech, and phrases) as multiple sources of evidence. 1 Experiments were designed to test each source of evidence independently, and to identify areas of interaction. Our hypothesis is: Hypothesis 1 Resolving lexical ambiguity will lead to an improvement in retrieval performance.</Paragraph>
    <Paragraph position="2"> There are many issues involved in determining how word senses should be used in information retrieval. The most basic issue is one of identity -what is a word sense? In previous work, researchers have usually made distinctions based on their intuition. This is not satisfactory for two reasons.</Paragraph>
    <Paragraph position="3"> First, it is difficult to scale up; researchers have generally focused on only two or three words. Second, they have used very coarse grained distinctions (e.g., 'river bank' v. 'commercial bank'). In practice it is often difficult to determine how many senses a word should have, and meanings are often related (Kilgarrift 91).</Paragraph>
    <Paragraph position="4"> A related issue is sense granularity. Dictionaries often make very fine distinctions between word meanings, and it isn't clear whether these distinctions are important in the context of a particular application. For example, the sentence They danced across the lvom is ambiguous with respect to the word dance. It can be paraphrased as They were across the room and they were dancing, or as They crossed the tvom as they danced. The sentence is not. ambiguous in Romance languages, and can only have the former meaning. Machine translation syst.ems therefore need to be aware of this ambiguity and translate the sentence appropriately. This is a systematic class of ambiguity, and applies to all &amp;quot;verbs of translatory motion&amp;quot; (e.g., The bottle floated ~mder the bridge will exhibit the same distinction (Talmy 85)). Such distinctions are unlikely to have an impact on information retrieval. However, there are  also distinctions that are important in information retrieval that are unlikely to be important in machine translation. For example, the word west can be used in the context the East versus the West, or in the context West Germany. These two senses were found to provide a good separation between relevant and non-relevant documents, but the distinction is probably not important for machine translation. It is likely that different applications will require different types of distinctions, and the type of distinctions required in information retrieval is an open question.</Paragraph>
    <Paragraph position="5"> Finally, there are questions about how word senses should be used in a retrieval system. In general, word senses should be used to supplement word-based indexing rather than indexing on word senses alone. This is because of the uncertainty involved with sense representation, and the degree to which we can identify a particular sense with the use of a word in context. If we replace words with senses, we are making an assertion that we are very certain that the replacement does not lose any of the information important in making relevance judgments, and that the sense we are choosing for a word is in fact correct. Both of these are problematic. Until more is learned about sense distinctions, and until very accurate methods are developed for identifying senses, it is probably best to adopt a more conservative approach (i.e., uses senses as a supplement to word-based indexing).</Paragraph>
    <Paragraph position="6"> The following section will provide an overview of lexical ambiguity and information retrieval. This will be followed by a discussion of our experiments.</Paragraph>
    <Paragraph position="7"> The paper will conclude with a summary of what has been accomplished, and what work remains for the future.</Paragraph>
  </Section>
  <Section position="4" start_page="0" end_page="73" type="metho">
    <SectionTitle>
2 Lexical Ambiguity and
</SectionTitle>
    <Paragraph position="0"/>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
Information Retrieval
2.1 Background
</SectionTitle>
      <Paragraph position="0"> Many retrieval systems represent documents and queries by the words they contain. There are two problems with using words to represent the content of documents. The first problem is that words are ambiguous, and this ambiguity can cause documents to be retrieved that are not relevant. Consider the following description of a search that was performed using the keyword &amp;quot;AIDS': Unfortunately, not all 34 \[references\] were about AIDS, the disease. The references included &amp;quot;two helpful aids during the first three months after total hip replacemenC, and &amp;quot;aids in diagnosing abnormal voiding patterns&amp;quot;. (Helm 83) One response to this problem is to use phrases to reduce ambiguity (e.g., specifying &amp;quot;hearing aids&amp;quot; if that is the desired sense). It is not always possible, however, to provide phrases in which the word occurs only with the desired sense. In addition, the requirement for phrases imposes a significant burden on the user.</Paragraph>
      <Paragraph position="1"> The second problem is that a document can be relevant even though it does not use the same words as those that are provided in the query. The user is generally not interested in retrieving documents with exactly the same words, but with the concepts that those words represent. Retrieval systems address this problem by expanding the query words using related words from a thesaurus (Salton and Mc-Gill 83). The relationships described in a thesaurus, however, are really between word senses rather than words. For example, the word &amp;quot;term&amp;quot; could be synonymous with 'word' (as in a vocabulary term), &amp;quot;sentence' (as in a prison term), or &amp;quot;condition' (as in 'terms of agreement'). If we expand the query with words from a thesaurus, we must be careful to use the right senses of those words. We not only have to know the sense of the word in the query (in this example, the sense of the word &amp;quot;term'), but the sense of the word that is being used to augment it (e.g., the appropriate sense of the word 'sentence') (Chodorow et al 88).</Paragraph>
    </Section>
    <Section position="2" start_page="0" end_page="73" type="sub_section">
      <SectionTitle>
2.2 Types of Lexlcal Ambiguity
</SectionTitle>
      <Paragraph position="0"> Lexical ambiguity can be divided into homonymy and polysemy, depending on whether or not the meanings are related. The bark of a dog versus the bark of a tree is an example of homonymy; review as a noun and as a verb is an example of polysemy.</Paragraph>
      <Paragraph position="1"> The distinction between homonymy and polysemy is central. Homonymy is important because it separates unrelated concepts. If we have a query about &amp;quot;AIDS' (tile disease), and a document contains &amp;quot;aids&amp;quot; in the sense of a hearing aid, then the word aids should not contribute to our belief that the document is relevant to the query. Polysemy is important because the related senses constitute a partial representation of the overall concept. If we fail to group related senses, it is as if we are ignoring some of the occurrences of a query word in a document. So for example, if we are distinguishing words by part-ofspeech, and the query contains 'diabetic' as a noun, the retrieval system will exclude instances in which 'diabetic' occurs as an adjective unless we recognize that the noun and adjective senses for that word are related and group them together.</Paragraph>
      <Paragraph position="2"> Although there is a theoretical distinction between homonymy and polysemy, it is not always easy to tell  them apart in practice. What determines whether the senses are related? Dictionaries group senses based on part-of-speech and etymology, but as illustrated by the word review, senses can be related even though they differ in syntactic category. Senses may also be related etymologically, but be perceived as distinct at the present time (e.g., the &amp;quot;cardinal' of a church and &amp;quot;cardinal' numbers are etymologically related). We investigated several methods to identify related senses both across part of speech and within a single homograph, and these will be described in more detail in Section 3.2.1.</Paragraph>
    </Section>
  </Section>
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