<?xml version="1.0" standalone="yes"?>
<Paper uid="H01-1045">
  <Title>Large scale testing of a descriptive phrase finder</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1. INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> Retrieving descriptions of the words and phrases, which are not often found in dictionaries, has potential benefits for a number of fields. The Descriptive Phrase Finder (DPF) is a system that retrieves descriptions of a query term from free text. The system only uses simple pattern matching to detect a description, and ranks the sentences that hold the descriptive phrases based on within document and cross document term occurrence information. The system does not attempt to extract descriptions from text, it simply locates sentences that are hopefully relevant to a user. It is assumed that users are able to read a sentence and locate any description within it. The advantage of using such an approach is that the DPF is much simplified and does not require parsing to find the exact location of the phrase. Due to its simplicity, it achieves a level of domain independence.</Paragraph>
    <Paragraph position="1"> The DPF was implemented and succeeded in The DPF was implemented and succeeded in retrieving sentences holding descriptive phrases (DPs) of a wide range of proper nouns. Initial testing on a collection of LA Times articles from the TREC Collection showed that 90% of the queries had at least one correct DP in the top 5 ranked sentences and 94% in the top 10 ([3]). It was shown that the effectiveness of the system was in part due to the large amount of free text being searched. What was not shown by the experiment was if performance could be further improved by searching an even larger text. Consequently, a larger scale experiment was conducted, searching for phrases from the World Wide Web (WWW) using the output of a commercial Web search engine to locate candidate documents that were then processed locally by the DPF.</Paragraph>
    <Paragraph position="2"> In addition to increasing the number of documents searched, more queries were tested and different definitions of relevance were tried. The rest of this short paper explains the system and shows the results of the expanded experiment, followed by pointers to future work.</Paragraph>
  </Section>
class="xml-element"></Paper>