Paper: Using Semantic Distance to Automatically Suggest Transfer Course Equivalencies

ACL ID W11-1418
Title Using Semantic Distance to Automatically Suggest Transfer Course Equivalencies
Venue Innovative Use of NLP for Building Educational Applications
Session
Year 2011
Authors

Semantic distance is the degree of closeness betweentwopiecesoftextdeterminedbytheir meaning. Semantic distance is typically mea- sured by analyzing a set of documents or a list of terms and assigning a metric based on the likeness of their meaning or the concept they represent. Although related research provides some semantic-based algorithms, few applica- tions exist. This work proposes a semantic- based approach for automatically identifying potential course equivalencies given their cat- alog descriptions. The method developed by Lietal.(2006)isextendedinthispapertotake a course description from one university as the inputandsuggestequivalentcoursesofferedat another university. Results are evaluated and future work is discussed.