title: Text similarity: an alternative way to search MEDLINE.
abstract: BACKGROUND
  The most widely used literature search techniques, such as those offered by NCBI's PubMed system, require significant effort on the part of the searcher, and inexperienced searchers do not use these systems as effectively as experienced users. Improved literature search engines can save researchers time and effort by making it easier to locate the most important and relevant literature.
  
  
  RESULTS
  We have created and optimized a new, hybrid search system for Medline that takes natural text as input and then delivers results with high precision and recall. The combination of a fast, low-sensitivity weighted keyword-based first pass algorithm to cast a wide net to gather an initial set of literature, followed by a unique sentence-alignment based similarity algorithm to rank order those results was developed that is sensitive, fast and easy to use. Several text similarity search algorithms, both standard and novel, were implemented and tested in order to determine which obtained the best results in information retrieval exercises.
  
  
  BACKGROUND
  Literature searching algorithms are implemented in a system called eTBLAST, freely accessible over the web at http://invention.swmed.edu. A variety of other derivative systems and visualization tools provides the user with an enhanced experience and additional capabilities.
  
  
  BACKGROUND
  Harold.Garner@UTSouthwestern.edu.
authors.affiliation: University of Texas Southwestern Medical Center, Eugene McDermott Center for Human Growth and Development, Division for Translational Research 5323 Harry Hines Boulevard, Dallas, TX 75390, USA.
authors.forename: James
authors.initials: J
authors.lastname: Lewis
authors.forename: Stephan
authors.initials: S
authors.lastname: Ossowski
authors.forename: Justin
authors.initials: J
authors.lastname: Hicks
authors.forename: Mounir
authors.initials: M
authors.lastname: Errami
authors.forename: Harold R
authors.initials: HR
authors.lastname: Garner
mesh_terms: D000043:Abstracting and Indexing / Q000379:methods*; D000465:Algorithms; D001185:Artificial Intelligence; D003628:Database Management Systems; D016247:Information Storage and Retrieval / Q000379:methods*; D016239:MEDLINE; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods; D010506:Periodicals as Topic; D014584:User-Computer Interface; D018875:Vocabulary, Controlled