Actively Learning Ontology Matching via User Interaction

Ontology matching plays a key role for semantic interoperability. Many methods have been proposed for automatically finding the alignment between heterogeneous ontologies. However, in many real-world applications, finding the alignment in a completely automatic way is highly infeasible. Ideally, an ontology matching system would have an interactive interface to allow users to provide feedbacks to guide the automatic algorithm. Fundamentally, we need answer the following questions: How can a system perform an efficiently interactive process with the user? How many interactions are sufficient for finding a more accurate matching? To address these questions, we propose an active learning framework for ontology matching, which tries to find the most informative candidate matches to query the user. The user’s feedbacks are used to: 1) correct the mistake matching and 2) propagate the supervise information to help the entire matching process. Three measures are proposed to estimate t...

• Type: Conference
• Year: 2009
• Where: SEMWEB
• Authors: Feng Shi, Juanzi Li, Jie Tang, Guo Tong Xie, Hanyu Li
• Keywords: Accurate Matching, Entire Matching Process, Internet Technology, Ontology Matching, SEMWEB 2009