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<Paper uid="P98-1038">
  <Title>PAT-Trees with the Deletion Function as the Learning Device for Linguistic Patterns</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> In this study, a learning device based on the PAT-tree data structures was developed. The original PAT-trees were enhanced with the deletion function to emulate human learning competence.</Paragraph>
    <Paragraph position="1"> The learning process worked as follows. The linguistic patterns from the text corpus are inserted into the PAT-tree one by one. Since the memory was limited, hopefully, the important and new patterns would be retained in the PAT-tree and the old and unimportant patterns would be released from the tree automatically. The proposed PAT-trees with the deletion function have the following advantages. 1) They are easy to construct and maintain. 2) Any prefix sub-string and its frequency count through PAT-tree can be searched very quickly. 3) The space requirement for a PAT-tree is linear with respect to the size of the input text. 4) The insertion of a new element can be carried out at any time without being blocked by the memory constraints because the free space is released through the deletion of unimportant elements.</Paragraph>
    <Paragraph position="2"> Experiments on learning high frequency bi-grams were carried out under different memory size constraints. High recall rates were achieved. The results show that the proposed PAT-trees can be used as on-line learning devices.</Paragraph>
  </Section>
class="xml-element"></Paper>