151 research outputs found
Towards ontology interoperability through conceptual groundings
Abstract. The widespread use of ontologies raises the need to resolve heterogeneities between distinct conceptualisations in order to support interoperability. The aim of ontology mapping is, to establish formal relations between a set of knowledge entities which represent the same or a similar meaning in distinct ontologies. Whereas the symbolic approach of established SW representation standards β based on first-order logic and syllogistic reasoning β does not implicitly represent similarity relationships, the ontology mapping task strongly relies on identifying semantic similarities. However, while concept representations across distinct ontologies hardly equal another, manually or even semi-automatically identifying similarity relationships is costly. Conceptual Spaces (CS) enable the representation of concepts as vector spaces which implicitly carry similarity information. But CS provide neither an implicit representational mechanism nor a means to represent arbitrary relations between concepts or instances. In order to overcome these issues, we propose a hybrid knowledge representation approach which extends first-order logic ontologies with a conceptual grounding through a set of CS-based representations. Consequently, semantic similarity between instances β represented as members in CS β is indicated by means of distance metrics. Hence, automatic similarity-detection between instances across distinct ontologies is supported in order to facilitate ontology mapping
Exploiting conceptual spaces for ontology integration
The widespread use of ontologies raises the need to integrate distinct conceptualisations. Whereas the symbolic approach of established representation standards β based on first-order logic (FOL) and syllogistic reasoning β does not implicitly represent semantic similarities, ontology mapping addresses this problem by aiming at establishing formal relations between a set of knowledge entities which represent the same or a similar meaning in distinct ontologies. However, manually or semi-automatically identifying similarity relationships is costly. Hence, we argue, that representational facilities are required which enable to implicitly represent similarities. Whereas Conceptual Spaces (CS) address similarity computation through the representation of concepts as vector spaces, CS rovide neither an implicit representational mechanism nor a means to represent arbitrary relations between concepts or instances. In order to overcome these issues, we propose a hybrid knowledge representation approach which extends FOL-based ontologies with a conceptual grounding through a set of CS-based representations. Consequently, semantic similarity between instances β represented as members in CS β is indicated by means of distance metrics. Hence, automatic similarity detection across distinct ontologies is supported in order to facilitate ontology integration
Recommended from our members
Two-fold Semantic Web service matchmaking β applying ontology mapping for service discovery
Semantic Web Services (SWS) aim at the automated discovery and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. Since SWS annotations usually are created by distinct SWS providers, semantic-level mediation, i.e. mediation between concurrent semantic representations, is a key requirement for SWS discovery. Since semantic-level mediation aims at enabling interoperability across heterogeneous semantic representations, it can be perceived as a particular instantiation of the ontology mapping problem. While recent SWS matchmakers usually rely on manual alignments or subscription to a common ontology, we propose a two-fold SWS matchmaking approach, consisting of (a) a general-purpose semantic-level mediator and (b) comparison and matchmaking of SWS capabilities. Our semantic-level mediation approach enables the implicit representation of similarities across distinct SWS by grounding service descriptions in so-called Mediation Spaces (MS). Given a set of SWS and their respective grounding, a SWS matchmaker automatically computes instance similarities across distinct SWS ontologies and matches the request to the most suitable SWS. A prototypical application illustrates our approach
Enabling Future Smart Energy Systems
The on-going transition to more sustainable energy production methods means that we are moving away from a monolithic, centrally controlled model to one in which both production and consumption are progressively decentralised and localised. This in turn gives rise to complex interacting networks. ICT and mathematics will be instrumental in making these networks more efficient and resilient. This article highlights two research areas that we expect will play an important role in these developments
MEMPERKAYA ONTOLOGI DARI BERBAGAI ONLINE SCHEMA DATA
Database relasional dianggap salah satu solusi penyimpanan yang paling populer untuk berbagai macam data dan
telah diakui sebagai faktor kunci dalam pengelolaan data untuk berbagai aplikasi. Ontologi, di sisi lain, adalah
salah satu konsep kunci dan media utama di bidang penelitian Semantik Web. Masalah menjembatani
kesenjangan antara database relasional dan ontologi telah menarik minat masyarakat Semantik Web, bahkan dari
tahun-tahun awal keberadaannya dan umumnya disebut sebagai masalah pemetaan database-ke-ontologi. Proses
manual dalam memperkaya ontologi yang sudah ada menjadi hal yang harus dilakukan berulang kali dan
menjadi pekerjaan yang tiada akhir. Usaha membuat proses memperkaya ontologi secara semi otomatis menjadi
suatu kebutuhan. Adapun tujuan dari paper ini adalah untuk mengembangkan arsitektur pemetaan database ke
ontologi dalam rangka memperkaya ontologi yang sudah ada. Model pendekatan ini dapat memperkaya ontologi
yang ada baik dari level class, property maupun instance/individu yang bersumber dari informasi dijital dalam
bentuk database terstruktur
- β¦