- (Aswani et al., 2006) ⇒ Niraj Aswani, Kalina Bontcheva, Hamish Cunningham. (2006). “Mining Information for Instance Unification.” In: Proceedings of the 5th International Semantic Web Conference (ISWC 2006). doi:10.1007/11926078_24
- It uses a Similarity Metric to compare Author Records
- The metric is based on a experimentally tuned weights.
- It uses the BT Digital Library Corpus from SEKT Project.
- It extracts (background) information from the Web about authors for additional evidence:
- This includes: author full name, author home page, paper titles and abstracts, and co-citation information
- It uses features: Author Names, Paper Title, Publication Venue, Publication Date, Paper Abstract.
- An example application is disambiguating Author Publication in Bibliographic Databases based on Citation Information.
Instance unification determines whether two instances in an ontology refer to the same object in the real world. More specifically, this paper addresses the instance unification problem for person names. The approach combines the use of citation information (i.e., abstract, initials, titles and co-authorship information) with web mining, in order to gather additional evidence for the instance unification algorithm. The method is evaluated on two datasets – one from the BT digital library and one used in previous work on name disambiguation. The results show that the information mined from the web contributes substantially towards the successful handling of highly ambiguous cases which lowered the performance of previous methods.,
|2006 MiningInformationForInstanceUnification||Niraj Aswani|
|Mining Information for Instance Unification||Proceedings of the 5th International Semantic Web Conference||http://gate.ac.uk/sale/iswc06/iswc06.pdf||10.1007/11926078_24||2006|
|Author||Niraj Aswani +, Kalina Bontcheva + and Hamish Cunningham +|
|journal||Proceedings of the 5th International Semantic Web Conference +|
|title||Mining Information for Instance Unification +|