Learning to combine multiple string similarity metrics for effective toponym matching

String Similarity Metrics for Ontology Alignment

Ontology alignment is an important part of enabling the semantic web to reach its full potential. The vast majority of ontology alignment systems use one or more string similarity metrics, but often the choice of which metrics to use is not given much attention. In this work we evaluate a wide range of such metrics, along with string preprocessing strategies such as removing stop words and cons...

Using Similarity Metrics for Matching Lifelong Learners

The L4All system provides an environment for the lifelong learner to access information about courses, personal development plans, recommendation of learning pathways, personalised support for planning of learning, and reflecting on learning. Designed as a web-based application, it offers lifelong learners the possibility to define and share their own timeline (a chronological record of their r...

Evaluation of Similarity Measures for Template Matching

Image matching is a critical process in various photogrammetry, computer vision and remote sensing applications such as image registration, 3D model reconstruction, change detection, image fusion, pattern recognition, autonomous navigation, and digital elevation model (DEM) generation and orientation. The primary goal of the image matching process is to establish the correspondence between two ...

Multiple Approximate String Matching

We present a very simple and eecient algorithm for on-line multiple approximate string matching. It uses a previously known counting-based lter 9] that searches for a single pattern by quickly discarding uninteresting parts of the text. Our multi-pattern algorithm is based on the simulation of many parallel lters using bits of the computer word. Our average complexity to search r patterns of le...

Sequential Multiple String Matching