Falcon-AO is an automatic tool for aligning ontologies. There are two matchers integrated in Falcon-AO: one is a matcher based on linguistic matching for ontologies, called LMO; the other is a matcher based on graph matching for ontologies, called GMO. In Falcon-AO, GMO takes the alignments generated by LMO as external input and outputs additional alignments. Reliable alignments are gained thro...

A perennial problem in recovering 3-D models from images is repeated structures common in modern cities. The problem can be traced to the feature matcher which needs to match less distinctive features (permitting wide-baselines and avoiding broken sequences), while simultaneously avoiding incorrect matching of ambiguous repeated features. To meet this need, we develop RepMatch, an epipolar guid...

Schema matching is the task of matching between concepts describing the meaning of data in various heterogeneous, distributed data sources. With many heuristics to choose from, several tools have enabled the use of schema matcher ensembles, combining principles by which different schema matchers judge the similarity between concepts. In this work, we investigate means of estimating the uncertai...

Presumably, with sufficient training data, it would be possible to build a classifier for each of the twenty predetermined complication labels. However since our training set consists of only a hundred and forty patients in total, and 14 of the 20 labels were associated with 10 or fewer patients, this approach was clearly infeasible. Similarly for the second task, there were only twenty patient...

This paper describes our participation in the Ontology Alignment Evaluation Initiative (OAEI) 2009 with the AgreementMaker system for ontology matching, in which we obtained excellent results. In particular, we participated in the benchmarks, anatomy, and conference tracks. In the anatomy track, we competed against nine other systems in all four subtracks obtaining the best result in subtrack 3...

Evan's 1968 ANALOGY system was the first computer model of analogy. This paper demonstrates that structure-mapping, when combined with high-level visual processing and qualitative representations, can do the same kinds of problems with hand-drawn sketched inputs. Importantly, the bulk of the computations are not particular to the model of this task but are general purpose: we sketch the problem...

Given the recent explosion of interest in human authentication, verification based on tokenised pseudo-random numbers and userspecific biometric feature (BioHashing) has received much attention. The purpose of our paper is to investigate the pros and the cons of BioHashing. In particular we study: how to combine BioHashing in a multi-modal fusion approach based on the integration of face and fi...

With a growing number of ontologies used in the semantic web, agents can fully make sense of different datasets only if correspondences between those ontologies are known. Ontology matching tools have been proposed to find such correspondences. While the current research focus is mainly on fully automatic matching tools, some approaches have been proposed that involve the user in the matching p...

PPMuSA is a pattern matching program for PROSITE [2] signature patterns against amino acid sequence database. To characterize a group of protein among others, it is important work to find occurrences of a signature in an amino acid sequence of the protein. Such signatures are compiled in databases. The PROSITE is one of the databases of signatures that distinguish members of a protein families ...

The central problems w.r.t. interoperability and data integration issues in the Semantic Web are schema and ontology matching approaches. Today it takes an expert to determine the best algorithm and a decision can usually be made only after experimentation, so as both the necessary scaling and off-the-shelf use of matching algorithms are not possible. To tackle these issues, we present a rule-b...