Ontology assessment based on linked data principles

2018 ◽  
Vol 14 (4) ◽  
pp. 453-479
Author(s):  
Leila Zemmouchi-Ghomari ◽  
Kaouther Mezaache ◽  
Mounia Oumessad
Keyword(s):  
Linked Data ◽  
Design Methodology ◽  
State Of The Art ◽  
Experimental Results ◽  
Data Sets ◽  
Content Type ◽  
Detailed Interpretation

Purpose The purpose of this paper is to evaluate ontologies with respect to the linked data principles. This paper presents a concrete interpretation of the four linked data principles applied to ontologies, along with an implementation that automatically detects violations of these principles and fixes them (semi-automatically). The implementation is applied to a number of state-of-the-art ontologies. Design/methodology/approach Based on a precise and detailed interpretation of the linked data principles in the context of ontologies (to become as reusable as possible), the authors propose a set of algorithms to assess ontologies according to the four linked data principles along with means to implement them using a Java/Jena framework. All ontology elements are extracted and examined taking into account particular cases, such as blank nodes and literals. The authors also provide propositions to fix some of the detected anomalies. Findings The experimental results are consistent with the proven quality of popular ontologies of the linked data cloud because these ontologies obtained good scores from the linked data validator tool. Originality/value The proposed approach and its implementation takes into account the assessment of the four linked data principles and propose means to correct the detected anomalies in the assessed data sets, whereas most LD validator tools focus on the evaluation of principle 2 (URI dereferenceability) and principle 3 (RDF validation); additionally, they do not tackle the issue of fixing detected errors.

Website traffic measurement and rankings: competitive intelligence tools examination

2018 ◽  
Vol 14 (4) ◽  
pp. 423-437 ◽  
Author(s):  
David Prantl ◽  
Martin Prantl
Keyword(s):  
Design Methodology ◽  
State Of The Art ◽  
Competitive Intelligence ◽  
Data Sets ◽  
Traffic Data ◽  
Content Type ◽  
Traffic Measurement ◽  
Data Estimation ◽  
Research Studies

PurposeThe purpose of this paper is to examine and verify the competitive intelligence tools Alexa and SimilarWeb, which are broadly used for website traffic data estimation. Tested tools belong to the state of the art in this area.Design/methodology/approachThe authors use quantitative approach. Research was conducted on a sample of Czech websites for which there are accurate traffic data values, against which the other data sets (less accurate) provided by Alexa and SimilarWeb will be compared.FindingsThe results show that neither tool can accurately determine the ranking of websites on the internet. However, it is possible to approximately determine the significance of a particular website. These results are useful for another research studies which use data from Alexa or SimilarWeb. Moreover, the results show that it is still not possible to accurately estimate website traffic of any website in the world.Research limitations/implicationsThe limitation of the research lies in the fact that it was conducted solely in the Czech market.Originality/valueSignificant amount of research studies use data sets provided by Alexa and SimilarWeb. However, none of these research studies focus on the quality of the website traffic data acquired by Alexa or SimilarWeb, nor do any of them refer to other studies that would deal with this issue. Furthermore, authors describe approaches to measuring website traffic and based on the analysis, the possible usability of these methods is discussed.

BOLD (Big and Open Linked Data): what’s next?

2017 ◽  
Vol 34 (5) ◽  
pp. 10-13 ◽  
Author(s):  
Stuti Saxena
Keyword(s):  
Open Source ◽  
Linked Data ◽  
Design Methodology ◽  
Data Sets ◽  
Content Type ◽  
Data Architecture ◽  
Different Sources ◽  
Practical Implications

Purpose The purpose of this paper is to appreciate the futuristic trends of Big and Open Linked Data (BOLD). While designating the ongoing progress of BOLD as BOLD 0.0, the paper also identifies the trajectory of BOLD 0.0 as BOLD 1.0, BOLD 2.0 and BOLD 3.0 in terms of the complexity and management of data sets from different sources. Design/methodology/approach This is a viewpoint and the ideas presented here are personal. Findings The trajectory of BOLD shall witness ever-growing challenges as the nature and scope of data sets grow complicated. The paper posits that by the time BOLD would attain its maturity, there would be a need for newer technologies and data architecture platforms which are relatively affordable and available as “Open Source”, if possible. Research limitations/implications Being exploratory in approach, this viewpoint presents a futuristic trend, which may or may not be valid. Nevertheless, there are significant practical implications for the academicians and practitioners to appreciate the likely challenges in the coming times for ensuring the sustainability of BOLD. Originality/value While there are a number of studies on BOLD, there are no studies which seek to propose the possible trends in BOLD’s progress. This paper seeks to plug this gap.

Learning domain taxonomies: the TaxoLine approach

2017 ◽  
Vol 13 (3) ◽  
pp. 281-301 ◽  
Author(s):  
Omar El Idrissi Esserhrouchni ◽  
Bouchra Frikh ◽  
Brahim Ouhbi ◽  
Ismail Khalil Ibrahim
Keyword(s):  
Execution Time ◽  
Design Methodology ◽  
State Of The Art ◽  
Relation Extraction ◽  
Ontology Learning ◽  
Conditional Mutual Information ◽  
Web Documents ◽  
Content Type ◽  
Innovative Methodology

Purpose The aim of this paper is to present an online framework for building a domain taxonomy, called TaxoLine, from Web documents automatically. Design/methodology/approach TaxoLine proposes an innovative methodology that combines frequency and conditional mutual information to improve the quality of the domain taxonomy. The system also includes a set of mechanisms that improve the execution time needed to build the ontology. Findings The performance of the TaxoLine framework was applied to nine different financial corpora. The generated taxonomies are evaluated against a gold-standard ontology and are compared to state-of-the-art ontology learning methods. Originality/value The experimental results show that TaxoLine produces high precision and recall for both concept and relation extraction than well-known ontology learning algorithms. Furthermore, it also shows promising results in terms of execution time needed to build the domain taxonomy.

Quality measures for skos

2018 ◽  
Vol 52 (3) ◽  
pp. 405-423 ◽  
Author(s):  
Riccardo Albertoni ◽  
Monica De Martino ◽  
Paola Podestà
Keyword(s):  
Linked Data ◽  
Design Methodology ◽  
Quality Measures ◽  
Third Party ◽  
Data Set ◽  
Content Type ◽  
Knowledge Organisation ◽  
The Cross ◽  
The Web

Purpose The purpose of this paper is to focus on the quality of the connections (linkset) among thesauri published as Linked Data on the Web. It extends the cross-walking measures with two new measures able to evaluate the enrichment brought by the information reached through the linkset (lexical enrichment, browsing space enrichment). It fosters the adoption of cross-walking linkset quality measures besides the well-known and deployed cardinality-based measures (linkset cardinality and linkset coverage). Design/methodology/approach The paper applies the linkset measures to the Linked Thesaurus fRamework for Environment (LusTRE). LusTRE is selected as testbed as it is encoded using a Simple Knowledge Organisation System (SKOS) published as Linked Data, and it explicitly exploits the cross-walking measures on its validated linksets. Findings The application on LusTRE offers an insight of the complementarities among the considered linkset measures. In particular, it shows that the cross-walking measures deepen the cardinality-based measures analysing quality facets that were not previously considered. The actual value of LusTRE’s linksets regarding the improvement of multilingualism and concept spaces is assessed. Research limitations/implications The paper considers skos:exactMatch linksets, which belong to a rather specific but a quite common kind of linkset. The cross-walking measures explicitly assume correctness and completeness of linksets. Third party approaches and tools can help to meet the above assumptions. Originality/value This paper fulfils an identified need to study the quality of linksets. Several approaches formalise and evaluate Linked Data quality focusing on data set quality but disregarding the other essential component: the connection among data.

A failure before analysis: the soup to nuts of preparing for multicountry analyses

2016 ◽  
Vol 23 (4) ◽  
pp. 590-612 ◽  
Author(s):  
Charlotte M. Karam ◽  
David A. Ralston
Keyword(s):  
Design Methodology ◽  
Cross Cultural ◽  
Data Sets ◽  
Review Of The Literature ◽  
Empirical Relationships ◽  
Content Type ◽  
Team Members ◽  
Building Trust ◽  
Key Issues

Purpose A large and growing number of researchers set out to cross-culturally examine empirical relationships. The purpose of this paper is to provide researchers, who are new to multicountry investigations, a discussion of the issues that one needs to address in order to be properly prepared to begin the cross-cultural analyses of relationships. Design/methodology/approach Thus, the authors consider two uniquely different but integrally connected challenges to getting ready to conduct the relevant analyses for just such multicountry studies. The first challenge is to collect the data. The second challenge is to prepare (clean) the collected data for analysis. Accordingly, the authors divide this paper into two parts to discuss the steps involved in both for multicountry studies. Findings The authors highlight the fact that in the process of collecting, there are a number of key issues that should be kept in mind including building trust with new team members, leading the team, and determining sufficient contribution of team members for authorship. Subsequently, the authors draw the reader’s attention to the equally important, but often-overlooked, data cleaning process and the steps that constitute it. This is important because failing to take serious the quality of the data can lead to violations of assumptions and mis-estimations of parameters and effects. Originality/value This paper provides a useful guide to assist researchers who are engaged in data collection and cleaning efforts with multiple country data sets. The review of the literature indicated how truly important a guideline of this nature is, given the expanding nature of cross-cultural investigations.

Clustering helps to improve price prediction in online booking systems

2021 ◽  
Vol 17 (1) ◽  
pp. 45-53
Author(s):  
Le Hong Trang ◽  
Tran Duong Huy ◽  
Anh Ngoc Le
Keyword(s):  
Machine Learning ◽  
Empirical Study ◽  
Sentiment Analysis ◽  
Design Methodology ◽  
Prediction Performance ◽  
Experimental Results ◽  
Data Sets ◽  
Classification Models ◽  
Content Type ◽  
Price Prediction

Purpose Pricing on the online booking systems is a difficult task for the host, the systems usually set the prices that are lower than the general premises and quality, and that only gives benefits to the system by easily attracting the customer to use the service. The setting price of the new accommodation is often based on location, the number of beds, type of house and so on. The main problem is to predict the most reasonable price for the host. This paper aims to study the use of machine learning and sentiment analysis for predicting the price of online booking systems. Design/methodology/approach In particular, an empirical study is performed first for some well-known classification models for the problems. The authors then propose to apply k-means, a clustering technique, together with Gradient Boost and XGBoost models to improve the prediction performance. Experiments are conducted and tested for real Airbnb data sets collected in London City. Findings Experimental results are given and compared to show that the authors’ method outperforms to an updated method. Originality/value The authors use k-means and sampling together with Gradient Boost and XGBoost models to improve the prediction performance.

Challenges to Portuguese tourism – Restelo old man or Cristiano Ronaldo?

2018 ◽  
Vol 10 (6) ◽  
pp. 698-704
Author(s):  
Pedro Machado
Keyword(s):  
Design Methodology ◽  
State Of The Art ◽  
Tourist Destination ◽  
Content Type ◽  
The North ◽  
Future Performance ◽  
Tourism Sector ◽  
Entire Country ◽  
Political Decisions

Purpose This paper aims to consider the state of the art of the tourism sector in Portugal, identifying the main problems and some challenges and solutions for the future. Design/methodology/approach The main political decisions related to tourism were analyzed and related to the sector´s future performance. Findings Portugal has been elected the best leading destination of the world, but it is important to outline the strategies needed to retain the quality of life of Portuguese residents and to keep and improve the experience of the tourist. This could be achieved by promoting “Portugal as a whole” (“Portugal por Inteiro”), applying policies of cohesion – policies that promote the development of the entire country, from the interior to the coastline, from the north to the south and the islands. Originality/value This paper presents the perspective of the Center of Portugal Tourism Entity (Turismo Centro de Portugal) and how this tourist destination contributes to the national strategies outlined for the coming years.

H-SPOOL

2016 ◽  
Vol 12 (3) ◽  
pp. 359-378 ◽  
Author(s):  
Takahiro Komamizu ◽  
Toshiyuki Amagasa ◽  
Hiroyuki Kitagawa
Keyword(s):  
Linked Data ◽  
Design Methodology ◽  
Query Language ◽  
Numerical Data ◽  
Online Analytical Processing ◽  
Data Sets ◽  
Content Type ◽  
Related Information ◽  
Analytical Processing ◽  
The Web

Purpose Linked data (LD) has promoted publishing information, and links published information. There are increasing number of LD datasets containing numerical data such as statistics. For this reason, analyzing numerical facts on LD has attracted attentions from diverse domains. This paper aims to support analytical processing for LD data. Design/methodology/approach This paper proposes a framework called H-SPOOL which provides series of SPARQL (SPARQL Protocol and RDF Query Language) queries extracting objects and attributes from LD data sets, converts them into star/snowflake schemas and materializes relevant triples as fact and dimension tables for online analytical processing (OLAP). Findings The applicability of H-SPOOL is evaluated using exiting LD data sets on the Web, and H-SPOOL successfully processes the LD data sets to ETL (Extract, Transform, and Load) for OLAP. Besides, experiments show that H-SPOOL reduces the number of downloaded triples comparing with existing approach. Originality/value H-SPOOL is the first work for extracting OLAP-related information from SPARQL endpoints, and H-SPOOL drastically reduces the amount of downloaded triples.

“Please tidy up before leaving”: nudging Airbnb guests toward altruistic behavior

2019 ◽  
Vol 13 (4) ◽  
pp. 524-530 ◽  
Author(s):  
Paul Ranson ◽  
Daniel Guttentag
Keyword(s):  
Social Presence ◽  
Design Methodology ◽  
Field Experiments ◽  
Experimental Results ◽  
Altruistic Behavior ◽  
Content Type ◽  
The Social ◽  
Relationship Model ◽  
Social Market ◽  
Practical Implications

Purpose This study aimed to investigate whether increasing the social presence within an Airbnb lodging environment could nudge guests toward altruistic cleaning behaviors. Design/methodology/approach The study was based around a theoretical framework combining the social-market versus money-market relationship model, nudge theory and social presence theory. A series of three field experiments were conducted, in which social presence was manipulated to test its impact on guest cleaning behaviors prior to departure. Findings The experimental results confirmed the underlying hypothesis that an Airbnb listing’s enhanced social presence can subtly induce guests to help clean their rental units prior to departure. Originality/value This study is the first to examine behavioral nudging in an Airbnb context. It is also one of the first field experiments involving Airbnb. The study findings offer clear theoretical and practical implications.

Information processing by elderly consumers: a five-decade review

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gianluigi Guido ◽  
Marco Pichierri ◽  
Cristian Rizzo ◽  
Verdiana Chieffi ◽  
George Moschis
Keyword(s):  
Information Processing ◽  
Design Methodology ◽  
State Of The Art ◽  
Relevant Literature ◽  
Academic Research ◽  
The Elderly ◽  
Marketing Strategies ◽  
Content Type ◽  
Processing Activity ◽  
Elderly Consumers

Purpose The purpose of this study is to review scholarly research on elderly consumers’ information processing and suggest implications for services marketing. Design/methodology/approach The review encompasses a five-decade period (1970–2018) of academic research and presents relevant literature in four main areas related to information processing: sensation, attention, interpretation and memory. Findings The study illustrates how each of the aforementioned phases of the information processing activity may affect how elderly individuals buy and consume products and services, emphasizing the need for a better comprehension of the elderly to develop effectual marketing strategies. Originality/value The study provides readers with detailed state-of-the-art knowledge about older consumers’ information processing, offering a comprehensive review of academic research that companies can use to improve the effectiveness of their marketing efforts that target the elderly market.

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