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Keyword-based faceted search interface for knowledge graph construction and exploration

Samir Sellami (LIRE Laboratory, Department of Software Technologies and Information Systems, Abdelhamid Mehri Constantine 2 University Faculty of New Technologies of Information and Communication, Constantine, Algeria and Department of Mathematics and Computer Science, Higher Normal School of Technological Education Skikda, Azzaba, Algeria)
Nacer Eddine Zarour (LIRE Laboratory, Department of Software Technologies and Information Systems, Abdelhamid Mehri Constantine 2 University Faculty of New Technologies of Information and Communication, Constantine, Algeria)

International Journal of Web Information Systems

ISSN: 1744-0084

Article publication date: 25 October 2022

Issue publication date: 12 December 2022

241

Abstract

Purpose

Massive amounts of data, manifesting in various forms, are being produced on the Web every minute and becoming the new standard. Exploring these information sources distributed in different Web segments in a unified way is becoming a core task for a variety of users’ and companies’ scenarios. However, knowledge creation and exploration from distributed Web data sources is a challenging task. Several data integration conflicts need to be resolved and the knowledge needs to be visualized in an intuitive manner. The purpose of this paper is to extend the authors’ previous integration works to address semantic knowledge exploration of enterprise data combined with heterogeneous social and linked Web data sources.

Design/methodology/approach

The authors synthesize information in the form of a knowledge graph to resolve interoperability conflicts at integration time. They begin by describing KGMap, a mapping model for leveraging knowledge graphs to bridge heterogeneous relational, social and linked web data sources. The mapping model relies on semantic similarity measures to connect the knowledge graph schema with the sources' metadata elements. Then, based on KGMap, this paper proposes KeyFSI, a keyword-based semantic search engine. KeyFSI provides a responsive faceted navigating Web user interface designed to facilitate the exploration and visualization of embedded data behind the knowledge graph. The authors implemented their approach for a business enterprise data exploration scenario where inputs are retrieved on the fly from a local customer relationship management database combined with the DBpedia endpoint and the Facebook Web application programming interface (API).

Findings

The authors conducted an empirical study to test the effectiveness of their approach using different similarity measures. The observed results showed better efficiency when using a semantic similarity measure. In addition, a usability evaluation was conducted to compare KeyFSI features with recent knowledge exploration systems. The obtained results demonstrate the added value and usability of the contributed approach.

Originality/value

Most state-of-the-art interfaces allow users to browse one Web segment at a time. The originality of this paper lies in proposing a cost-effective virtual on-demand knowledge creation approach, a method that enables organizations to explore valuable knowledge across multiple Web segments simultaneously. In addition, the responsive components implemented in KeyFSI allow the interface to adequately handle the uncertainty imposed by the nature of Web information, thereby providing a better user experience.

Keywords

Citation

Sellami, S. and Zarour, N.E. (2022), "Keyword-based faceted search interface for knowledge graph construction and exploration", International Journal of Web Information Systems, Vol. 18 No. 5/6, pp. 453-486. https://doi.org/10.1108/IJWIS-02-2022-0037

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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