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    <identifier>10.11922/sciencedb.j00104.00029</identifier>
    <datestamp>2020-10-16T13:34:39Z</datestamp>
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  <dc:date>2020-10-16</dc:date>
  <dc:title>An Evaluation of Chinese Human-Computer Dialogue Technology</dc:title>
  <dc:identifier>doi:10.11922/sciencedb.j00104.00029</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Seven tables of this paper. Table 1 shows an example of air ticket booking. Table 2 presents some examples in training set of Task 1. Table 3 shows statistics of the intent data set in Task 1. Table 4 presents the top 8 teams of Task 1 ranked by F1 score. Table 5 shows the top 5 teams of Task 2. Note: C denotes task completion ratio, T denotes average dialogue turns, Sa denotes user satisfaction score, F denotes fluency degree of response, and G denotes uncovered data guidance capability. All these indicators are average scores of all test cases. Table A1 is the complete leaderboard of Task 1 ranking by F1 score. Table A2 shows the complete leaderboard of Task 2. Note: C denotes task completion ratio, T denotes average dialogue turns, Sa denotes user satisfaction score, F denotes fluency degree of response, and G denotes uncovered data guidance capability. All these indicators are average scores of all test cases.</dc:description>
  <dc:subject>Chinese human-computer dialogue evaluation;  Evaluation data;  User intent classification;  Taskoriented dialogue</dc:subject>
  <dc:creator>Zhengyu Zhao</dc:creator>
  <dc:creator>Weinan Zhang</dc:creator>
  <dc:creator>Wanxiang Che</dc:creator>
  <dc:creator>Zhigang Chen</dc:creator>
  <dc:creator>Yibo Zhang</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.1162/dint_a_00007</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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