A Knowledge-Based Approach to Ontologies Data Integration (original) (raw)

AQUA–ontology-based question answering system

2004

This paper describes AQUA, an experimental question answering system. AQUA combines Natural Language Processing (NLP), Ontologies, Logic, and Information Retrieval technologies in a uniform framework. AQUA makes intensive use of an ontology in several parts of the question answering system. The ontology is used in the refinement of the initial query, the reasoning process, and in the novel similarity algorithm. The similarity algorithm, is a key feature of AQUA.

A tool for knowledge base integration and querying

AAAI Spring Symposium

Introduction In recent years, we have witnessed the development of sev-eral efforts to incorporate semantics and knowledge-based reasoning in question and answering (QA) systems (eg, (Harabagiu 2001; Vicedo 2000; Pasca 2000)). This is nec-essary as queries, eg, concerning actions, ...

AquaLog: An ontology-driven question answering system to interface the semantic web

2006

Abstract The semantic web (SW) vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language (NL) and an ontology as input, and returns answers drawn from one or more knowledge bases (KB).

A Generic Platform for Ontological Query Answering

2012

Abstract The paper presents ALASKA, a multi-layered platform enabling to perform ontological conjunctive query answering (OCQA) over heterogeneously-stored knowledge bases in a generic, logic-based manner. While this problem knows today a renewed interest in knowledge-based systems with the semantic equivalence of different languages widely studied, from a practical view point this equivalence has been not made explicit.

A Framework for Ontology Integration

The Emerging Semantic …, 2002

One of the basic problems in the development of techniques for the semantic web is the integration of ontologies. Indeed, the web is constituted by a variety of information sources, each expressed over a certain ontology, and in order to extract information from such sources, their semantic integration and reconciliation in terms of a global ontology is required. In this paper, we address the fundamental problem of how to specify the mapping between the global ontology and the local ontologies. We argue that for capturing such mapping in an appropriate way, the notion of query is a crucial one, since it is very likely that a concept in one ontology corresponds to a view (i.e., a query) over the other ontologies. As a result query processing in ontology integration systems is strongly related to view-based query answering in data integration.

Ontology-Driven Question Answering in AquaLog

2004

The semantic web vision is one in which rich, ontology-based semantic markup is widely available, both to enable sophisticated interoperability among agents and to support human web users in locating and making sense of information. The availability of semantic markup on the web also opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input and returns answers drawn from one or more knowledge bases (KBs), which instantiate the input ontology with domain-specific information. AquaLog makes use of the GATE NLP platform, string metrics algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target knowledge base. Finally, although AquaLog has primarily been designed for use with semantic web languages, it makes use of a generic plug-in mechanism, which means it can be easily interfaced to different ontology servers and knowledge representation platforms.

Ontology Based Information Integration : A Survey 1

2019

An ontology makes a special vocabulary which describes the domain of interest and the meaning of the term on that vocabulary. Based on the precision of the specification, the concept of the ontology contains several data and conceptual models. The notion of ontology has emerged into wide ranges of applications including database integration, peer-to-peer systems, e-commerce, semantic web, etc. It can be considered as a practical tool for conceptualizing things which are expressed in computer format. This paper is devoted to ontology matching as a mean for information integration. Several matching solutions have been presented from various areas such as databases, information systems and artificial intelligence. All of them take advantages of different attributes of ontology like, structures, data instances, semantics and labels and its other valuable properties. The solutions have some common techniques and cope with similar problems, but use different methods for combining and expl...

Ontology Mapping with domain specific agents in the AQUA Question Answering system

2005

This paper describes a domain specific multi-agent ontology-mapping solution in the AQUA query answering system. In order to incorporate uncertainty inherent to the mapping process, the system uses the Dempster-Shafer model for dealing with incomplete and uncertain information produced during the mapping. A novel approach is presented how specialized agents with partial local knowledge of the particular domain achieve ontology mapping without creating global or reference ontology.

A Novel Approach for Semantic Integration of Data using Ontology

Indian Journal of Science and Technology, 2016

Integration process of data is recently recognized like a significant visualization of the Semantic Web explore for which researchers focus on numerous areas, such as integration of information, ontologies and databases. Objectives: Users generally requires an incorporated analysis of information accessible from various data and it was proposed to grant users with this view of data. Methods: The Meta data is created from different data sets like excel data set, RDF data set and XML data set. Findings: In this work a survey was made for integrating databases using ontology and a new approach for integration of databases is devised for finding correspondence between ontologies. Applications: View and Search functionality was provided by filtering data from Meta data. This provides easy access to the integrated data.