@article{Miller3,
  author = "Tristan Miller",
  title = "Essay assessment with latent semantic analysis",
  journal = "Journal of Educational Computing Research",
  volume = "29",
  title = "4",
  year = "2003",
  pages = "495--512",
  abstract = "Latent semantic analysis (LSA) is an automated, statistical
                technique for comparing the semantic similarity of words or
                documents.  In this paper, I examine the application of LSA to
                automated essay scoring.  I compare LSA methods to earlier
                statistical methods for assessing essay quality, and critically
                review contemporary essay-scoring systems built on LSA, including
                the <i>Intelligent Essay Assessor</i>, <i>Summary Street</i>,
                <i>State the Essence</i>, <i>Apex</i>, and
                <i>Select-a-Kibitzer</i>. Finally, I discuss current avenues of
                research, including LSA's application to computer-measured
                readability assessment and to automatic summarization of student
                essays. ",
  download = "http://baywood.metapress.com/(tri0lq55vfwgmoz2qbzypcax)/app/home/contribution.asp?referrer=parent&backto=issue,6,7;searcharticlesresults,3,38;"
}