We investigate the use of background knowledge ontology in ontology matching. We conducted experiments on matching two medical ontologies using third extensive one as background knowledge, and compare it to the direct match. Our results indicate that using background knowledge, in particular exploitation of its structure, has enormous benefit in the matching. The semantics of knowledge within t...

Increasingly, there is a recognized need for secure information sharing. In order to implement information sharing between diverse organizations, we need privacypreserving interoperation systems. In this work, we describe two frameworks for privacy-preserving interoperation systems. Ontology matching is an indispensable component of interoperation systems. To implement privacy-preserving intero...

Current algorithms cannot be used optimally in (semi)automatic ontology matching tasks as envisioned by the Semantic Web community, mainly because of the inherent dependency between algorithms and ontology properties. As one possible solution we suggest a metadata-based ontology matching framework that takes into account the difficulties of current matching algorithms. It uses additional data c...

This paper presents the results of Lily in the ontology alignment contest OAEI 2016. As a comprehensive ontology matching system, this year Lily is intended to participate in three tracks of the contest: benchmark, conference, and anatomy. The specific techniques used by Lily will be introduced briefly. The strengths and weaknesses of Lily will also be discussed. 1 Presentation of the system Wi...

This paper presents the alignment results of Lily for the ontology alignment contest OAEI 2008. Lily is an ontology mapping system, and it has four main features: generic ontology matching, large scale ontology matching, semantic ontology matching and mapping debugging. In the past year, Lily has been improved greatly for both function and performance. In OAEI 2008, Lily submited the results fo...

This paper presents the alignment results of Lily for the ontology alignment contest OAEI 2009. Lily is an ontology mapping system, and it has four functions: generic ontology matching, large scale ontology matching, semantic ontology matching and mapping debugging. In OAEI 2009, Lily submited the results for four alignment tasks: benchmark, anatomy, directory and conference. 1 Presentation of ...

Semantic similarity measures play an important role in information retrieval and information integration. Traditional approaches to modeling semantic similarity compute the semantic distance between definitions within a single ontology. This single ontology is either a domain-independent ontology or the result of the integration of existing ontologies. We present an approach to computing semant...

Since the high time and space complexity, most existing ontology matching systems are not well scalable to solve the large ontology matching problem. Moreover, the popular divide-and-conquer matching solution faces two disadvantages: First, partitioning ontology is a complicate process; Second, it will lead to loss of semantic information during matching. To avoid these drawbacks, this paper pr...

This paper presents the results obtained by NBJLM (Nankai Baidu Joint Lab Matcher) for its first participation to OAEI 2010. The research of ontology-based similarity calculation among concepts has already been a hot issue. NBJLM is an hybrid ontology alignment method that considers both similarity of literal concept and semantic structure. Simultaneously, how to accelerate matching has been me...

schema matching is a critical step in many applications, such as data warehouse loading, online analytical process (olap), data mining, semantic web [2] and schema integration. this task is defined for finding the semantic correspondences between elements of two schemas. recently, schema matching has found considerable interest in both research and practice. in this paper, we present a new impr...