Matching of concepts describing the meaning of data in heterogeneous distributed information sources, such as database schemas and other metadata models, grouped here under the heading of an ontology, is one of the basic operations of semantic heterogeneity reconciliation. The aim of this chapter is to motivate the need for ontology matching, introduce the basics of ontology matching, and then ...

Extending complex information structures by means of ontology matching is of high interest for a number of tasks solved in the semantic web. The main motivation behind this work is that the procedure of ontology matching requires a robust and scalable solution that ensures the maximal efficiency of matching operations. That is especially important when thinking of matching large scale data amon...

We investigate the use of a background knowledge ontology in ontology matching. We conducted experiments on matching two medical ontologies using a third extensive one as background knowledge, and compare the results with directly matching the two ontologies. Our results indicate that using background knowledge, in particular the exploitation of its structure, has enormous benefits on the match...

This paper describes ONTMAT an ontology matching system, and presents the results obtained for the Ontology Alignment Evaluation Initiative (OAEI) 2017. ONTMAT is an ontology matching process, which compares the instances of ontologies to align in order to deduce the relations between their concepts. Then, based on hierarchical and binary relations between the concepts inside the ontologies it ...

As a key representation model of knowledge, ontology has been widely used in a lot of NLP related tasks, such as semantic parsing, information extraction and text mining etc. In this paper, we study the task of ontology matching, which concentrates on finding semantically related entities between different ontologies that describe the same domain, to solve the semantic heterogeneity problem. Pr...

Ontology matching is the process of generating correspondences between terms of different ontologies. Today, several methods for ontology matching have been proposed, which makes difficult the choice of the most suitable to use in a particular setting. In this paper, we propose a novel ontology matching framework that uses automatic matchers recommendation to generate alignments. The differenti...

This paper presents the results of Lily in the ontology alignment contest OAEI 2015. As a comprehensive ontology matching system, Lily is intended to participate in four tracks of the contest: benchmark, conference, anatomy, and instance matching. The specific techniques used by Lily will be introduced briefly. The strengths and weaknesses of Lily will also be discussed. 1 Presentation of the s...

Ontology matching has emerged as a crucial step when information sources are being integrated. Hence, ontology matching has attracted considerable attention in both academia and industry. Clearly, as information sources grow rapidly, manual ontology matching becomes tedious, time-consuming and leads to errors and frustration. Thus the need for automated and semi-automated approaches becomes inc...

The abundance of ontology data is very crucial to the emerging semantic web. This paper proposes a framework that supports the generation of ontology data in a peer-to-peer environment. It not only enables users to convert existing structured data to ontology data aligned with given ontology schemas, but also allows them to publish new ontology data with ease. Besides ontology data generation, ...

The FAST gadget development environment allows users to graphically compose intelligent, i.e., semantically annotated gadgets from predefined building blocks and deploy them on various mashup platforms, thus enabling the interconnection of different systems and services. In an environment where different parties use different ontologies to describe such building blocks, ontology matching is cru...