Marc Ehrig

QOM: quick ontology mapping

(Semi-)automatic mapping - also called (semi-) automatic alignment - of ontologies is a core task to achieve interoperability when two agents or services use different ontologies. In the existing literature, the focus has so far been on improving the quality of mapping results. We here consider QOM, Quick Ontology Mapping, as a way to trade off between effectiveness (i.e. quality) and efficiency of the mapping generation algorithms. We show that QOM has lower run-time complexity than existing prominent approaches. Then, we show in experiments that this theoretical investigation translates into practical benefits. While QOM gives up some of the possibilities for producing high-quality results in favor of efficiency, our experiments show that this loss of quality is marginal.

Ontology Mapping – An Integrated Approach

Ontology mapping is important when working with more than one ontology. Typically similarity considerations are the basis for this. In this paper an approach to integrate various similarity methods is presented. In brief, we determine similarity through rules which have been encoded by ontology experts. These rules are then combined for one overall result. Several boosting small actions are added. All this is thoroughly evaluated with very promising results.

KAON - Towards a Large Scale Semantic Web

The Semantic Web will bring structure to the content of Web pages, being an extension of the current Web, in which information is given a well-defined meaning. Especially within e-commerce applications, Semantic Web technologies in the form of ontologies and metadata are becoming increasingly prevalent and important. This paper introduce KAON - the Karlsruhe Ontology and Semantic WebTool Suite. KAON is developed jointly within several EU-funded projects and specifically designed to provide the ontology and metadata infrastructure needed for building, using and accessing semantics-driven applications on the Web and on your desktop.

Bibster-a semantics-based bibliographic Peer-to-Peer system

This paper describes Bibster, a Peer-to-Peer system for exchanging bibliographic metadata among researchers. We show how Bibster exploits ontologies in data-representation, query formulation, query routing, and query result presentation. The Bibster system is freely available and is used by researchers across multiple organizations.

Bootstrapping ontology alignment methods with APFEL

Ontology alignment is a prerequisite in order to allow for interoperation between different ontologies and many alignment strategies have been proposed to facilitate the alignment task by (semi-)automatic means. Due to the complexity of the alignment task, manually defined methods for (semi-)automatic alignment rarely constitute an optimal configuration of substrategies from which they have been built. In fact, scrutinizing current ontology alignment methods, one may recognize that most are not optimized for given ontologies. Some few include machine learning for automating the task, but their optimization by machine learning means is mostly restricted to the extensional definition of ontology concepts. With APFEL (Alignment Process Feature Estimation and Learning) we present a machine learning approach that explores the user validation of initial alignments for optimizing alignment methods. The methods are based on extensional and intensional ontology definitions. Core to APFEL is the idea of a generic alignment process, the steps of which may be represented explicitly. APFEL then generates new hypotheses for what might be useful features and similarity assessments and weights them by machine learning approaches. APFEL compares favorably in our experiments to competing approaches.

Ontology-focused crawling of Web documents

The Web, the largest unstructured database of the world, has greatly improved access to documents. However, documents on the Web are largely disorganized. Due to the distributed nature of the World Wide Web it is difficult to use it as a tool for information and knowledge management. Therefore, users doing the difficult task of exploring the Web have to be supported by intelligent means.This paper proposes an approach for document discovery building on a comprehensive framework for ontology-focused crawling of Web documents. Our framework includes means for using a complex ontology and associated instance elements. It defines several relevance computation strategies and provides an empirical evaluation which has shown promising results.

The SWAP Data and Metadata Model for Semantics-Based Peer-to-Peer Systems

Peer-to-Peer systems are a new paradigm for information sharing and some systems have successfully been deployed. It has been argued that current Peer-to-Peer systems suffer from the lack of semantics. The SWAP project (Semantic Web and Peer-to-Peer) aims at overcoming this problem by combining the Peer-to-Peer paradigm with Semantic Web technologies. In this paper, we propose a data model for encoding semantic information that combines features of ontologies (concept hierarchies, relational structures) with a flexible description and rating model that allows us to handle heterogeneous and even contradictory views on the domain of interest. We discuss the role of this model in the SWAP environment and describe the model as well as its application.

Bibster: a semantics-based bibliographic peer-to-peer system

This paper describes the design and implementation of Bibster, a Peer-to-Peer system for exchanging bibliographic data among researchers. Bibster exploits ontologies in data storage, query formulation, query routing and answer presentation: When bibliographic entries are made available for use in Bibster, they are structured and classified according to two different ontologies. This ontological structure is then exploited to help users formulate their queries. Subsequently, the ontologies are used to improve query routing across the Peer-to-Peer network. Finally, the ontologies are used to postprocess the returned answers in order to do duplicate detection. The paper describes each of these ontology-based aspects of Bibster. Bibster is a fully implemented open source solution built on top of the JXTA platform.

Personalized Information Access in a Bibliographic Peer-to-Peer System

The Bibster system is an application of the use of semantics in Peer-to-Peer systems, which is aimed at researchers that share bibliographic metadata. In this paper we describe the design and implementation of recommender functionality in the Bibster system which allows personalized access to the bibliographic metadata available in the Peer-to-Peer network. These functions are based on a semantic user profile which is created from content and usage information as well as a similarity function. Furthermore, these functions make use of the semantic topology of the Peer-to-Peer system.

Towards Evaluation of Peer-to-Peer-Based Distributed Knowledge Management Systems

Distributed knowledge management systems (DKMS) have been suggested to meet the requirements of today’s knowledge management. Peer-to-peer systems offer technical foundations for such distributed systems. To estimate the value of P2P-based knowledge management evaluation criteria that measure the performance of such DKMS are required. We suggest a concise framework for evaluation of such systems within different usage scenarios. Our approach is based on standard measures from the information retrieval and the databases community. These measures serve as input to a general evaluation function which is used to measure the efficiency of P2P-based KM systems. We describe test scenarios as well as the simulation software and data sets that can be used for that purpose.