---
res:
  bibo_abstract:
  - Physician Review Websites allow users to evaluate their experiences with health
    services. As these evaluations are regularly contextualized with facts from users’
    private lives, they often accidentally disclose personal information on the Web.
    This poses a serious threat to users’ privacy. In this paper, we report on early
    work in progress on “Text Broom”, a tool to detect privacy breaches in user-generated
    texts. For this purpose, we conceptualize a pipeline which combines methods of
    Natural Language Processing such as Named Entity Recognition, linguistic patterns
    and domain-specific Machine Learning approaches which have the potential to recognize
    privacy violations with wide coverage. A prototypical web application is openly
    accesible.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Frederik Simon
      foaf_name: Bäumer, Frederik Simon
      foaf_surname: Bäumer
      foaf_workInfoHomepage: http://www.librecat.org/personId=38837
  - foaf_Person:
      foaf_givenName: Joschka
      foaf_name: Kersting, Joschka
      foaf_surname: Kersting
      foaf_workInfoHomepage: http://www.librecat.org/personId=58701
  - foaf_Person:
      foaf_givenName: Matthias
      foaf_name: Orlikowski, Matthias
      foaf_surname: Orlikowski
      foaf_workInfoHomepage: http://www.librecat.org/personId=72334
  - foaf_Person:
      foaf_givenName: Michaela
      foaf_name: Geierhos, Michaela
      foaf_surname: Geierhos
      foaf_workInfoHomepage: http://www.librecat.org/personId=42496
    orcid: 0000-0002-8180-5606
  bibo_volume: 2198
  dct_date: 2018^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/1613-0073
  dct_language: eng
  dct_publisher: CEUR-WS.org@
  dct_subject:
  - Detection of Privacy Violations
  - Physician Reviews
  dct_title: Towards a Multi-Stage Approach to Detect Privacy Breaches in Physician
    Reviews@
...