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Article
Publication date: 11 November 2014

S. Thenmalar and T.V. Geetha

The purpose of this paper is to improve the conceptual-based search by incorporating structural ontological information such as concepts and relations. Generally, Semantic-based…

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Abstract

Purpose

The purpose of this paper is to improve the conceptual-based search by incorporating structural ontological information such as concepts and relations. Generally, Semantic-based information retrieval aims to identify relevant information based on the meanings of the query terms or on the context of the terms and the performance of semantic information retrieval is carried out through standard measures-precision and recall. Higher precision leads to the (meaningful) relevant documents obtained and lower recall leads to the less coverage of the concepts.

Design/methodology/approach

In this paper, the authors enhance the existing ontology-based indexing proposed by Kohler et al., by incorporating sibling information to the index. The index designed by Kohler et al., contains only super and sub-concepts from the ontology. In addition, in our approach, we focus on two tasks; query expansion and ranking of the expanded queries, to improve the efficiency of the ontology-based search. The aforementioned tasks make use of ontological concepts, and relations existing between those concepts so as to obtain semantically more relevant search results for a given query.

Findings

The proposed ontology-based indexing technique is investigated by analysing the coverage of concepts that are being populated in the index. Here, we introduce a new measure called index enhancement measure, to estimate the coverage of ontological concepts being indexed. We have evaluated the ontology-based search for the tourism domain with the tourism documents and tourism-specific ontology. The comparison of search results based on the use of ontology “with and without query expansion” is examined to estimate the efficiency of the proposed query expansion task. The ranking is compared with the ORank system to evaluate the performance of our ontology-based search. From these analyses, the ontology-based search results shows better recall when compared to the other concept-based search systems. The mean average precision of the ontology-based search is found to be 0.79 and the recall is found to be 0.65, the ORank system has the mean average precision of 0.62 and the recall is found to be 0.51, while the concept-based search has the mean average precision of 0.56 and the recall is found to be 0.42.

Practical implications

When the concept is not present in the domain-specific ontology, the concept cannot be indexed. When the given query term is not available in the ontology then the term-based results are retrieved.

Originality/value

In addition to super and sub-concepts, we incorporate the concepts present in same level (siblings) to the ontological index. The structural information from the ontology is determined for the query expansion. The ranking of the documents depends on the type of the query (single concept query, multiple concept queries and concept with relation queries) and the ontological relations that exists in the query and the documents. With this ontological structural information, the search results showed us better coverage of concepts with respect to the query.

Details

Aslib Journal of Information Management, vol. 66 no. 6
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 22 December 2022

Sergio Evangelista Silva and André Luís Silva

This article introduces a model of knowledge creation in consciousness, the creation of explicit knowledge in six forms and its register and organisation in documents.

Abstract

Purpose

This article introduces a model of knowledge creation in consciousness, the creation of explicit knowledge in six forms and its register and organisation in documents.

Design/methodology/approach

Assuming the premise of three realms of reference to knowledge and two forms of reference to entities, this article, through a phenomenological perspective, deduces a model of the creation of knowledge in consciousness and the creation of explicit knowledge in six forms and its register in documents.

Findings

Two basic types of knowledge are introduced: situated knowledge and theoretical/normative knowledge. Considering three realms of reference of knowledge – the space–time realm, subjectivity realm and linguistic realm – six general types of knowledge are deduced. Finally, three layers of knowledge organisation are presented: classification and mapping documents, theoretical/normative documents and documents of situations.

Practical implications

This article can contribute to the development of more efficient forms of creation of explicit knowledge, its register in documents and the development of more efficient knowledge organisation and management systems.

Originality/value

Relying on established perspectives of the realms where subjectivity is immersed, this article discusses how knowledge is created in consciousness and registered in documents. It also presents a novel perspective of types of knowledge through the combination of dimensions, realms of reference and forms of reference to entities.

Details

Journal of Documentation, vol. 79 no. 4
Type: Research Article
ISSN: 0022-0418

Keywords

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