Summary of the paper

Title Cross-Corpus Textual Entailment for Sublanguage Analysis in Epidemic Intelligence
Authors Avaré Stewart, Kerstin Denecke and Wolfgand Nejdl
Abstract Textual entailment has been recognized as a generic task that captures major semantic inference needs across many natural language processing applications. However, to date, textual entailment has not been considered in a cross-corpus setting, nor for user generated content. Given the emergence of Medicine 2.0, medical blogs are becoming an increasingly accepted source of information. However, given the characteristics of blogs( which tend to be noisy and informal; or contain a interspersing of subjective and factual sentences) a potentially large amount of irrelevant information may be present. Given the potential noise, the overarching problem with respect to information extraction from social media is achieving the correct level of sentence filtering - as opposed to document or blog post level. Specifically for the task of medical intelligence gathering. In this paper, we propose an approach to textual entailment with uses the text from one source of user generated content (T text) for sentence-level filtering within a new and less amenable one (H text), when the underlying domain, tasks or semantic information is the same, or overlaps.
Topics Information Extraction, Information Retrieval, Knowledge Discovery/Representation, Corpus (creation, annotation, etc.)
Full paper Cross-Corpus Textual Entailment for Sublanguage Analysis in Epidemic Intelligence
Slides -
Bibtex @InProceedings{STEWART10.881,
  author = {Avaré Stewart and Kerstin Denecke and Wolfgand Nejdl},
  title = {Cross-Corpus Textual Entailment for Sublanguage Analysis in Epidemic Intelligence},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
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