@MASTERSTHESIS{Ott-09,
  author = {Niels Ott},
  title = {Information Retrieval for Language Learning: An Exploration of Text
	Difficulty Measures},
  school = {University of T\"{u}bingen, Seminar f\"{u}r Sprachwissenschaft},
  year = {2009},
  address = {T\"{u}bingen, Germany},
  abstract = {This thesis explores a variety of text difficulty measures in the context
	of language learning and Information Retrieval. The possibilities
	of fast and straightforward retrieval of general information as well
	as of reading material at the language proficiency level of a learner
	are examined on the basis of a prototypical search engine implementation.
	In a preliminary evaluation experiment we found two of nine traditional
	readability formulas to be promising candidates for classifying texts
	gained from the Web into levels of text difficulty. In addition, the
	use of Lexical Frequency Profiles as indicators for vocabulary load
	appears to be promising as well. Having shown the general track to
	follow in order to retrieve information and reading at the learner’s
	level, we suggest future work to investigate the mapping of the discussed
	difficulty measures to a well-established system of representing language
	proficiency, such as the system of Common European Framework.},
  keywords = {readabability, measures, search engine, text model, query model, information retrieval, computer-assisted language learning},
  url = {http://drni.de/zap/ma-thesis}
}