Keyword-based search (e.g., Google) is the most popular tool for web searching and information retrieval; however, keyword-based searching also produces many irrelevant results because keywords can have multiple meanings or they often inadequately express users' intent (Michael & Rajesh, 2011). In order to find accurate information, users waste time browsing long lists of often-irrelevant results. In addition, keyword-based search does not provide adequate support to users but strictly returns the documents whose vocabulary matches the keyword terms (Wilson et al., 2009); therefore, it fails to recognize relevant documents that do not match the query (Mann, 2008).
Ontology and Topic MapsSome previous research tries to improve information searching by optimizing information organization. Ontology-based indexing technologies area promising approach (Patkar, 2011). By establishing an ontology on the basis of semantic relationships between concepts, the improved information organization may improve users' searching performance (Jimeno-Yepes et al., 2010;Yi, 2008).Building ontologies can be done using Topic Maps, which is an international standard (ISO13250) for knowledge representation and exchange. According to Pepper (2000), Topic Maps represent information concepts and their relationships using the following elements:• Topics: represent any concept, from people, countries, and organizations to software modules, individual files, and events; •Associations: representing relationships between topics; •Occurrences: representing information resources relevant to a particular topic.This paper describes a project that has created a Topic Map search tool for a mathematics educational database containing articles from the journal For the Learning of Mathematics. The resulting website enables users to retrieve research articles based on a variety of topics such as mathematics classification, research methods, educational objectives, in addition to traditional bibliographic information.