Search (11 results, page 1 of 1)

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Abstract

Ontology alignment became a very important problem to ensure semantic interoperability for different sources of information heterogeneous and distributed. Instance-based ontology alignment represents a very promising technique to find semantic correspondences between entities of different ontologies when they contain a lot of instances. In this paper, we describe a new approach to manage ontologies that do not share common instances.This approach extracts the argument and event structures from a set of instances of the concept of the source ontology and compared them with other semantic features extracted from a set of instances of the concept of the target ontology using Generative Lexicon Theory. We show that it is theoretically powerful because it is based on linguistic semantics and useful in practice. We present the experimental results obtained by running our approach on Biblio test of Benchmark series of OAEI 2011. The results show the good performance of our approach.

Type

a

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Abstract

The Semantic Web consists of data structured for use by computer programs, such as data sets made available under the Linked Open Data initiative. Much of this data is structured following the entity-relationship model encoded in RDF for syntactic interoperability. For semantic interoperability, the semantics of the relationships used in any given dataset needs to be made explicit. Ultimately this requires an inventory of these relationships structured around a relation ontology. This talk will outline a blueprint for such an inventory, including a format for the description/definition of binary and n-ary relations, drawing on ideas put forth in the classification and thesaurus community over the last 60 years, upper level ontologies, systems like FrameNet, the Buffalo Relation Ontology, and an analysis of linked data sets.

Source

Classification and ontology: formal approaches and access to knowledge: proceedings of the International UDC Seminar, 19-20 September 2011, The Hague, The Netherlands. Eds.: A. Slavic u. E. Civallero

Type

a

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Abstract

This paper presents a new approach to understanding how indexing strategies, models for interoperability and retrieval paradigms interact in information systems and how this can be used to support the design and implementation of components of a semantic navigation for information retrieval systems.

Type

a

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Abstract

The article presents a method for automatic semantic indexing of archaeological grey-literature reports using empirical (rule-based) Information Extraction techniques in combination with domain-specific knowledge organization systems. The semantic annotation system (OPTIMA) performs the tasks of Named Entity Recognition, Relation Extraction, Negation Detection, and Word-Sense Disambiguation using hand-crafted rules and terminological resources for associating contextual abstractions with classes of the standard ontology CIDOC Conceptual Reference Model (CRM) for cultural heritage and its archaeological extension, CRM-EH. Relation Extraction (RE) performance benefits from a syntactic-based definition of RE patterns derived from domain oriented corpus analysis. The evaluation also shows clear benefit in the use of assistive natural language processing (NLP) modules relating to Word-Sense Disambiguation, Negation Detection, and Noun Phrase Validation, together with controlled thesaurus expansion. The semantic indexing results demonstrate the capacity of rule-based Information Extraction techniques to deliver interoperable semantic abstractions (semantic annotations) with respect to the CIDOC CRM and archaeological thesauri. Major contributions include recognition of relevant entities using shallow parsing NLP techniques driven by a complimentary use of ontological and terminological domain resources and empirical derivation of context-driven RE rules for the recognition of semantic relationships from phrases of unstructured text.

Type

a

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Abstract

iQvoc is a new open source SKOS-XL vocabulary management tool developed by the Federal Environment Agency, Germany, and innoQ Deutschland GmbH. Its immediate purpose is maintaining and publishing reference vocabularies in the upcoming Linked Data cloud of environmental information, but it may be easily adapted to host any SKOS- XL compliant vocabulary. iQvoc is implemented as a Ruby on Rails application running on top of JRuby - the Java implementation of the Ruby Programming Language. To increase the user experience when editing content, iQvoc uses heavily the JavaScript library jQuery.

Type

a

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Abstract

Purpose - This paper seeks to develop a specified typology of various levels of semantic interoperability, designed to provide semantically expressive and functional means to interconnect typologically different sub-systems in an international comprehensive knowledge organization system, supporting advanced information retrieval and exploration strategies. Design/methodology/approach - Taking the analysis of rudimentary forms of a functional interoperability based on simple pattern matching as a starting-point, more refined strategies to provide semantic interoperability, which is actually reaching the conceptual and even thematic level, are being developed. The paper also examines the potential benefits and perspectives of the selective transfer of modelling strategies from the field of semantic technologies for the refinement of relational structures of inter-system and inter-concept relations as a requirement for expressive and functional indexing languages supporting advanced types of semantic interoperability. Findings - As the principles and strategies of advanced information retrieval systems largely depend on semantic information, new concepts and strategies to achieve semantic interoperability have to be developed. Research limitations/implications - The approach has been developed in the functional and structural context of an international comprehensive system integrating several heterogeneous knowledge organization systems and indexing languages by interconnecting them to a central conceptual structure operating as a spine in an overall system designed to support retrieval and exploration of bibliographic records representing complex conceptual entities. Originality/value - Research and development aimed at providing technical and structural interoperability has to be complemented by a thorough and precise reflection and definition of various degrees and types of interoperability on the semantic level as well. The approach specifies these levels and reflects the implications and their potential for advanced strategies of retrieval and exploration.

Type

a

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Abstract

Sources like thesauri or taxonomies are already used as input in ontology development process. Some of them are also published on the LOD using the SKOS format. Reusing this type of sources to build an ontology is not an easy task. The ontology developer has to face different syntax and different modelling goals. We propose in this paper a new methodology to transform several non-ontological sources into a single ontology. We take into account: the redundancy of the knowledge extracted from sources in order to discover the consensual knowledge and Ontology Design Patterns (ODPs) to guide the transformation process. We have evaluated our methodology by creating an ontology on wheat taxonomy from three sources: Agrovoc thesaurus, TaxRef taxonomy, NCBI taxonomy.

Type

a

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Abstract

Current retrieval and recommendation approaches rely on hard-wired data models. This hinders personalized cus-tomizations to meet information needs of users in a more flexible manner. Therefore, the paper investigates how similarity-basedretrieval strategies can be combined with graph queries to enable users or system providers to explore repositories in the LinkedOpen Data (LOD) cloud more thoroughly. For this purpose, we developed novel content-based recommendation approaches.They rely on concept annotations of Simple Knowledge Organization System (SKOS) vocabularies and a SPARQL-based querylanguage that facilitates advanced and personalized requests for openly available knowledge graphs. We have comprehensivelyevaluated the novel search strategies in several test cases and example application domains (i.e., travel search and multimediaretrieval). The results of the web-based online experiments showed that our approaches increase the recall and diversity of rec-ommendations or at least provide a competitive alternative strategy of resource access when conventional methods do not providehelpful suggestions. The findings may be of use for Linked Data-enabled recommender systems (LDRS) as well as for semanticsearch engines that can consume LOD resources. (PDF) Similarity-based knowledge graph queries for recommendation retrieval. Available from: https://www.researchgate.net/publication/333358714_Similarity-based_knowledge_graph_queries_for_recommendation_retrieval [accessed May 21 2020].

Type

a

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Type

a

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Content

Neumaier, Sebastian (et al.): Data Integration for Open Data on the Web - Stamou, Giorgos (et al.): Ontological Query Answering over Semantic Data - Calì, Andrea: Ontology Querying: Datalog Strikes Back - Sequeda, Juan F.: Integrating Relational Databases with the Semantic Web: A Reflection - Rousset, Marie-Christine (et al.): Datalog Revisited for Reasoning in Linked Data - Kaminski, Roland (et al.): A Tutorial on Hybrid Answer Set Solving with clingo - Eiter, Thomas (et al.): Answer Set Programming with External Source Access - Lukasiewicz, Thomas: Uncertainty Reasoning for the Semantic Web - Calvanese, Diego (et al.): OBDA for Log Extraction in Process Mining

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Type

a