<?xml version="1.0" standalone="yes"?>
<Paper uid="C04-1108">
  <Title>Improving Chronological Sentence Ordering by Precedence Relation</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> The growth of computerized documents enables us to find relevant information easily owing to technologicaladvancesinInformationRetrieval.</Paragraph>
    <Paragraph position="1"> Although it is convenient that we can obtain a great number of documents with a search engine, this situation also presents the information pollution problem: &amp;quot;Who is willing to take the tedious burden of reading all those text documents?&amp;quot; Automatic text summarization (Mani, 2001), is one solution to the problem, providing users with a condensed version of the original text.</Paragraph>
    <Paragraph position="2"> Most existing summarization systems make use of sentence or paragraph extraction, which finds significant textual segments in source documents, and compile them in a summary. After we select significant sentences as a material for a summary, we must find a proper arrangement of the sentences and edit each sentence by deleting unnecessary parts or inserting necessary expressions. Although there has been a great deal of research on extraction since the early stage of natural language processing (Luhn, 1958), research on post-processing of automatic summarization is relatively small in number. It is essential to pay attention to sentence ordering in case of multi-document summarization. Sentence position in the original document, which yields a good clue to sentence arrangement for single-document summarization, is not enough for multi-document summarization because we must consider inter-document order at the same time.</Paragraph>
    <Paragraph position="3"> In this paper we propose an approach to coherent text structuring for summarizing newspaper articles. We improve chronological ordering, which is widely used by conventional summarization system, complementing presupposed information of each sentence. The rest of this paper is organized as follows. We first review the sentence ordering problem and present our approach to generate an acceptable ordering in the light of coherence relation. The subsequent section (Section 3) addresses evaluation metrics and experiment results. In Section 4 we discuss future work and conclude this paper.</Paragraph>
  </Section>
class="xml-element"></Paper>