An Ontology-Based Information Retrieval System

Varga, Péter Pál; Mészáros, Tamás; Dezsenyi, Csaba; Dobrowiecki, Tadeusz

doi:10.1007/3-540-45034-3_36

Cited by 7 publications

(2 citation statements)

References 4 publications

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“…In the simplest case, an application may require only text files, iteratively read from a local directory. A more autonomous solution would apply intelligent retrieval agents that can search the internet for relevant documents (Varga et al, 2003). The retrieval phase can also include format conversion and other required pre-processing.…”

Section: Overview Of the Document Analyser Frameworkmentioning

confidence: 99%

Adaptive information extraction from unstructured documents

Dezsenyi

Dobrowiecki

Mészáros

2007

IJIIDS

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The authors present a novel adaptive framework that enables efficient development of applications demanding complex document analysis. In processing natural language documents the task is to transform them into application specific structured form. Such transformation has to be designed taking into account various abstraction levels and granularity of the processing and the multitude of possibly related requests driving the application. The proposed solution is based on the adaptively planned and executed network of information processing modules. The paper presents an overview of the framework, with the focus on the adaptive mechanism. An illustrative pilot application is also provided.

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Section: Overview Of the Document Analyser Frameworkmentioning

confidence: 99%

Adaptive information extraction from unstructured documents

Dezsenyi

Dobrowiecki

Mészáros

2007

IJIIDS

Self Cite

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“…Both models include an ontology-based scheme for the annotation of documents, and a retrieval model based on an adaptation of the classic vector-space model [58]. Two other information retrieval systems based on ontologies are presented in [70] and [36]. The first describes a general architecture and a prototype application for the concise storage and presentation of the information retrieved from a wide spectrum of information sources, while the second proposes an information retrieval system which has landmark information database that has hierarchical structures and semantic meanings of the features and characteristics of the landmarks.…”

Section: Ontologies In Retrieval Systemsmentioning

confidence: 99%

A conceptual representation of documents and queries for information retrieval systems by using light ontologies

Dragoni

Pereira

Tettamanzi

2012

Expert Systems with Applications

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This article presents a vector space model approach to representing documents and queries, based on concepts instead of terms and using WordNet as a light ontology. Such representation reduces information overlap with respect to classic semantic expansion techniques. Experiments carried out on the MuchMore benchmark and on the TREC-7 and TREC-8 Ad-hoc collections demonstrate the effectiveness of the proposed approach.

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