Visualization Of Similarities Research Articles

Tourism and Sustainability: A Bibliometric and Visualization Analysis

Sustainability is a growing research topic in tourism due to the importance of environmental and social issues, and the maintenance of patrimony and other facilities to conserve the potential of tourism destinations. Specifically, sustainability in tourism is crucial in order to guarantee a consistent development of destinations, measured by growth in income and employment. This relevance has been translated into an explosive growth in the sustainability literature regarding tourism, income, and employment. However, there is a lack of bibliometric and visualization research on tourism sustainability (TS), and specifically on its relationship with income and employment. This paper aims to present a bibliometric overview of TS research, and specifically TS related to income and employment. The current work analyzed 2279 references collected from the Web of Science (WoS) Core Collection database and used the visualization of similarities (VOS)viewer program to graphically map the material. The study used co-occurrence of keywords, co-citation, bibliographic coupling, and co-authorship analyses. The results identify the development status and the leading trends in terms of impact, main journals, papers, topics, authors, institutions, and countries. The analysis and graphical presentations are relevant, as they can help researchers and practitioners better understand the state of the art of TS.

Fifty years of Information Sciences: A bibliometric overview

Information Sciences is a leading international journal in computer science launched in 1968, so becoming fifty years old in 2018. In order to celebrate its anniversary, this study presents a bibliometric overview of the leading publication and citation trends occurring in the journal. The aim of the work is to identify the most relevant authors, institutions, countries, and analyze their evolution through time. The paper uses the Web of Science Core Collection in order to search for the bibliographic information. Our study also develops a graphical mapping of the bibliometric material by using the visualization of similarities (VOS) viewer. With this software, the work analyzes bibliographic coupling, citation and co-citation analysis, co-authorship, and co-occurrence of keywords. The results underline the significant growth of the journal through time and its international diversity having publications from countries all over the world.

Forty years of Computers & Industrial Engineering: A bibliometric analysis

Computers & Industrial Engineering (CIE) is a leading international journal in the field of industrial engineering, whose first issue was published in 1976. Motivated by its 40th anniversary in 2016, this study aims to develop a bibliometric analysis of the publications of the journal between 1976 and 2015. The objective is to identify the leading trends of the journal in terms of impact, topics, universities and countries. In doing so, the work uses the Web of Science Core Collection database to analyze the bibliometric data. Additionally, the work also uses the visualization of similarities (VOS) viewer software to map graphically the bibliographic material. The graphical analysis uses bibliographic coupling, co-citation, citation, co-authorship and co-occurrence of keywords. This paper also offers an editorial perspective of the journal’s policy, editorial process, and performance progress.

Statistical properties of urban mobility from location-based travel networks

Abstract This study explores urban mobility from a network-based perspective. The data samples used in study were collected from more than 1100 taxi drivers during a half year period in the city of Harbin in China. We extract trips from the original dataset and analyze operational efficiency. Then, by constructing travel networks based on occupied and vacant taxi trips, we calculate some statistical properties of the network such as degree, strength, edge weight, betweenness, clustering coefficient and network structure entropy. Analysis of such properties allows for a deep exploration of travel mobility. We also analyze the correlation between strength and betweenness to evaluate the importance of nodes in the network. Furthermore, two traditional community detection algorithms: the Louvain method and the visualization of similarities (VOS) method are applied to divide traffic zones in the mainland area of Harbin city. Two indices, the Rand index (RI) and the Fowkles–Mallows index (FMI) are adopted to evaluate recognition performance, which shows the similarity between administrative division and results from the algorithms. Finally, a dilatation index based on the weighted average distance among trips is applied to analyze the spatial structure of an urban city. Furthermore, hotspots are identified from local density of locations with different thresholds as determined by the Lorenz curve.

Identifying Similar Cases in Document Networks Using Cross-Reference Structures.

Our objective was to explore the creation of document networks based on different thresholds of shared information and different clustering algorithms on those networks to identify document clusters describing similar clinical cases. We created networks from vaccine adverse event report sets using seven approaches for linking reports. We then applied three clustering algorithms [visualization of similarities (VOS), Louvain, k-means] to these networks and evaluated their ability to identify known clusters. The report sets included one simulated set and three sets from the Vaccine Adverse Event Reporting System; each was split into training and testing subsets. Training subsets were used to estimate parameter values for the clustering algorithms and testing subsets to evaluate clusters. We created the networks by linking reports based on shared information in the form either of individual Medical Dictionary for Regulatory Activities Preferred Terms (PTs) or of dyads, triplets, quadruplets, quintuplets, and sextuplets of PTs; we created another network by weighting the single PT network connections by Lin's information theoretic approach to similarity. We then repeated this entire process using networks based on text mining output rather than structured data. We evaluated report clustering using recall, precision, and f-measure. The VOS algorithm outperformed Louvain and k-means in general. The best weighting scheme appeared to be related to the complexity of the known cluster. For example, singleton weighting performed best for an intussusception cluster driven by a single PT. We observed marginal differences between the code- and textual-based clustering. In conclusion, our approach supported identification of similar nodes in a document network.

Análisis de la interdisciplinariedad en la ingeniería química universitaria española

An analysis is made of interdisciplinarity in the chemical engineering (CE) field. It includes a detailed description of the occurrence of papers and journals in each of the Journal Citation Reports (JCR) categories in order to gain insight into the structure of knowledge in CE research, its patterns and associated trends. Bibliometric methods are used to analyse the multi-assignment of papers and/or journals to the various JCR categories. The total of journals (598) is distributed among 115 categories, with 54% of them (324) and 56% of the documents assigned to more than one category. The results of a co-occurrence analysis of the data corresponding to the different categories are mapped using the Visualization of Similarities (VOS) technique. The co-occurrences are plotted on a two-dimensional representation revealing the distinct clusters formed by their proximities. The result was 13 clusters. The categories that stand out as most central and most interconnected were “Engineering, Chemical”, “Chemistry, Physical”, and “Biotechnology & Applied Microbiology”. No relationship was found between the co-authorship index and multi-assignment into categories. The 14 categories selected as the most productive represented, in 2006, 39.7% of the journals in the JCR’s 1st quartile.