Entry Wu:2006:ERT from talip.bib

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BibTeX entry

@Article{Wu:2006:ERT,
  author =       "Chung-Hsien Wu and Ze-Jing Chuang and Yu-Chung Lin",
  title =        "Emotion recognition from text using semantic labels
                 and separable mixture models",
  journal =      j-TALIP,
  volume =       "5",
  number =       "2",
  pages =        "165--183",
  month =        jun,
  year =         "2006",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1165255.1165259",
  ISSN =         "1530-0226 (print), 1558-3430 (electronic)",
  ISSN-L =       "1530-0226",
  bibdate =      "Thu Oct 5 07:00:29 MDT 2006",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/talip.bib",
  abstract =     "This study presents a novel approach to automatic
                 emotion recognition from text. First, emotion
                 generation rules (EGRs) are manually deduced from
                 psychology to represent the conditions for generating
                 emotion. Based on the EGRs, the emotional state of each
                 sentence can be represented as a sequence of semantic
                 labels (SLs) and attributes (ATTs); SLs are defined as
                 the domain-independent features, while ATTs are
                 domain-dependent. The emotion association rules (EARs)
                 represented by SLs and ATTs for each emotion are
                 automatically derived from the sentences in an
                 emotional text corpus using the a priori algorithm.
                 Finally, a separable mixture model (SMM) is adopted to
                 estimate the similarity between an input sentence and
                 the EARs of each emotional state. Since some features
                 defined in this approach are domain-dependent, a dialog
                 system focusing on the students' daily expressions is
                 constructed, and only three emotional states, happy,
                 unhappy, and neutral, are considered for performance
                 evaluation. According to the results of the
                 experiments, given the domain corpus, the proposed
                 approach is promising, and easily ported into other
                 domains.",
  acknowledgement = ack-nhfb,
  fjournal =     "ACM Transactions on Asian Language Information
                 Processing",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?&idx=J820",
}

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