01362nas a2200181   4500008004100000245008600041210006900127260000900196300001400205490000700219520077400226653001501000653000801015100002001023700001901043700002401062856009401086       2006                        eng d00aMatching Knowledge Elements in Concept Maps Using a Similarity Flooding Algorithm0 aMatching Knowledge Elements in Concept Maps Using a Similarity F  c2006  a1290-13060 v423 aConcept mapping systems used in education and knowledge management emphasize flexibility of representation to enhance learning and facilitate knowledge capture. Collections of concept maps exhibit terminology variance, informality, and organizational variation. These factors make it difficult to match elements between maps in comparison, retrieval, and merging processes. In this work, we add an element anchoring mechanism to a similarity flooding (SF) algorithm to match nodes and substructures between pairs of simulated maps and student-drawn concept maps. Experimental results show significant improvement over simple string matching with combined recall accuracy of 91% for conceptual nodes and concept ¨ link ¨ concept propositions in student-drawn maps.10aAccounting10aBIS1 aMarshall, Byron1 aChen, Hsinchun1 aMadhusudan, Therani  uhttp://people.oregonstate.edu/~marshaby/Papers/MatchKnowledgeElements_PrePrintVersion.pdf