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<Paper uid="W03-0402">
  <Title>An SVM Based Voting Algorithm with Application to Parse Reranking</Title>
  <Section position="7" start_page="2" end_page="2" type="concl">
    <SectionTitle>
6 Conclusions and Future Work
</SectionTitle>
    <Paragraph position="0"> We have introduced a new approach for applying SVMs to sequential models indirectly, and described a novel SVM based voting algorithm inspired by the parse reranking problem. We have presented a risk formulation under the PAC framework for this voting algorithm, and applied this algorithm to the parse reranking problem, and achieved LR/LP of 89.4%/89.8% on WSJ section 23.</Paragraph>
    <Paragraph position="1"> Experimental results show that the SVM with a linear kernel is superior to the SVM with tree kernel in both accuracy and speed. The SVM with tree kernel only achieves a rather low f-score because it takes too many unrelated features into account. The linear kernel is defined on the features which are manually selected from a large set of possible features.</Paragraph>
    <Paragraph position="2"> As far as context-free grammars are concerned, it will be hard to include more features into the current feature set. If we simply use n-grams on context-free grammars, it is very possible that we will introduce many useless features, which may be harmful as they are in tree kernel systems. One way to include more useful features is to take advantage of the derivation tree and the elementary trees in Lexicalized Tree Adjoining Grammar (LTAG) (Joshi and Schabes, 1997). The basic idea is that each elementary tree and every segment in a derivation tree is linguistically meaningful.</Paragraph>
    <Paragraph position="3"> We also plan to apply this algorithm to other sequential models, especially to the Supertagging problem. We believe it will also be very useful to problems of POS tagging and NP chunking. Compared to parse reranking, they have a much smaller training dataset and feature size, which is more suitable for our SVM-based voting problem.</Paragraph>
  </Section>
class="xml-element"></Paper>