60,844 research outputs found
Identifying Overlapping and Hierarchical Thematic Structures in Networks of Scholarly Papers: A Comparison of Three Approaches
We implemented three recently proposed approaches to the identification of
overlapping and hierarchical substructures in graphs and applied the
corresponding algorithms to a network of 492 information-science papers coupled
via their cited sources. The thematic substructures obtained and overlaps
produced by the three hierarchical cluster algorithms were compared to a
content-based categorisation, which we based on the interpretation of titles
and keywords. We defined sets of papers dealing with three topics located on
different levels of aggregation: h-index, webometrics, and bibliometrics. We
identified these topics with branches in the dendrograms produced by the three
cluster algorithms and compared the overlapping topics they detected with one
another and with the three pre-defined paper sets. We discuss the advantages
and drawbacks of applying the three approaches to paper networks in research
fields.Comment: 18 pages, 9 figure
CitNetExplorer: A new software tool for analyzing and visualizing citation networks
We present CitNetExplorer, a new software tool for analyzing and visualizing
citation networks of scientific publications. CitNetExplorer can for instance
be used to study the development of a research field, to delineate the
literature on a research topic, and to support literature reviewing. We first
introduce the main concepts that need to be understood when working with
CitNetExplorer. We then demonstrate CitNetExplorer by using the tool to analyze
the scientometric literature and the literature on community detection in
networks. Finally, we discuss some technical details on the construction,
visualization, and analysis of citation networks in CitNetExplorer
Bibliometric Maps of BIM and BIM in Universities: A Comparative Analysis
Building Information Modeling (BIM) is increasingly important in the architecture and engineering fields, and especially in the field of sustainability through the study of energy. This study performs a bibliometric study analysis of BIM publications based on the Scopus database during the whole period from 2003 to 2018. The aim was to establish a comparison of bibliometric maps of the building information model and BIM in universities. The analyzed data included 4307 records produced by a total of 10,636 distinct authors from 314 institutions. Engineering and computer science were found to be the main scientific fields involved in BIM research. Architectural design are the central theme keywords, followed by information theory and construction industry. The final stage of the study focuses on the detection of clusters in which global research in this field is grouped. The main clusters found were those related to the BIM cycle, including construction management, documentation and analysis, architecture and design, construction/fabrication, and operation and maintenance (related to energy or sustainability). However, the clusters of the last phases such as demolition and renovation are not present, which indicates that this field suntil needs to be further developed and researched. With regard to the evolution of research, it has been observed how information technologies have been integrated over the entire spectrum of internet of things (IoT). A final key factor in the implementation of the BIM is its inclusion in the curriculum of technical careers related to areas of construction such as civil engineering or architecture
Exploring Communities in Large Profiled Graphs
Given a graph and a vertex , the community search (CS) problem
aims to efficiently find a subgraph of whose vertices are closely related
to . Communities are prevalent in social and biological networks, and can be
used in product advertisement and social event recommendation. In this paper,
we study profiled community search (PCS), where CS is performed on a profiled
graph. This is a graph in which each vertex has labels arranged in a
hierarchical manner. Extensive experiments show that PCS can identify
communities with themes that are common to their vertices, and is more
effective than existing CS approaches. As a naive solution for PCS is highly
expensive, we have also developed a tree index, which facilitate efficient and
online solutions for PCS
Collaborative tagging as a tripartite network
We describe online collaborative communities by tripartite networks, the
nodes being persons, items and tags. We introduce projection methods in order
to uncover the structures of the networks, i.e. communities of users, genre
families...
To do so, we focus on the correlations between the nodes, depending on their
profiles, and use percolation techniques that consist in removing less
correlated links and observing the shaping of disconnected islands. The
structuring of the network is visualised by using a tree representation. The
notion of diversity in the system is also discussed
Comparison and validation of community structures in complex networks
The issue of partitioning a network into communities has attracted a great
deal of attention recently. Most authors seem to equate this issue with the one
of finding the maximum value of the modularity, as defined by Newman. Since the
problem formulated this way is NP-hard, most effort has gone into the
construction of search algorithms, and less to the question of other measures
of community structures, similarities between various partitionings and the
validation with respect to external information. Here we concentrate on a class
of computer generated networks and on three well-studied real networks which
constitute a bench-mark for network studies; the karate club, the US college
football teams and a gene network of yeast. We utilize some standard ways of
clustering data (originally not designed for finding community structures in
networks) and show that these classical methods sometimes outperform the newer
ones. We discuss various measures of the strength of the modular structure, and
show by examples features and drawbacks. Further, we compare different
partitions by applying some graph-theoretic concepts of distance, which
indicate that one of the quality measures of the degree of modularity
corresponds quite well with the distance from the true partition. Finally, we
introduce a way to validate the partitionings with respect to external data
when the nodes are classified but the network structure is unknown. This is
here possible since we know everything of the computer generated networks, as
well as the historical answer to how the karate club and the football teams are
partitioned in reality. The partitioning of the gene network is validated by
use of the Gene Ontology database, where we show that a community in general
corresponds to a biological process.Comment: To appear in Physica A; 25 page
Thesaurus-assisted search term selection and query expansion: a review of user-centred studies
This paper provides a review of the literature related to the application of domain-specific thesauri in the search and retrieval process. Focusing on studies which adopt a user-centred approach, the review presents a survey of the methodologies and results from empirical studies undertaken on the use of thesauri as sources of term selection for query formulation and expansion during the search process. It summaries the ways in which domain-specific thesauri from different disciplines have been used by various types of users and how these tools aid users in the selection of search terms. The review consists of two main sections covering, firstly studies on thesaurus-aided search term selection and secondly those dealing with query expansion using thesauri. Both sections are illustrated with case studies that have adopted a user-centred approach
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