Identifying key players in bipartite networks

2020 ◽  
Vol 8 (1) ◽  
pp. 42-61
Author(s):  
Scott W. Duxbury
Keyword(s):  
Network Structure ◽  
The Other ◽  
Centrality Measures ◽  
Bipartite Network ◽  
Bipartite Networks ◽  
Key Players ◽  
Two Measures ◽  
The One

AbstractMeasures of bipartite network structure have recently gained attention from network scholars. However, there is currently no measure for identifying key players in two-mode networks. This article proposes measures for identifying key players in bipartite networks. It focuses on two measures: fragmentation and cohesion centrality. It extends the centrality measures to bipartite networks by considering (1) cohesion and fragmentation centrality within a one-mode projection, (2) cross-modal cohesion and fragmentation centrality, where a node in one mode is influential in the one-mode projection of the other mode, and (3) cohesion and fragmentation centrality across the entire bipartite structure. Empirical examples are provided for the Southern Women’s data and on the Ndrangheta mafia data.

Continual representation learning for evolving biomedical bipartite networks

2021 ◽  
Author(s):  
Kishlay Jha ◽  
Guangxu Xun ◽  
Aidong Zhang
Keyword(s):  
Network Structure ◽  
Learning Strategy ◽  
Structure Learning ◽  
Fundamental Problem ◽  
Representation Learning ◽  
Research Area ◽  
Bipartite Network ◽  
Bipartite Networks ◽  
Straightforward Application ◽  
Low Dimensional

Abstract Motivation Many real-world biomedical interactions such as ‘gene-disease’, ‘disease-symptom’ and ‘drug-target’ are modeled as a bipartite network structure. Learning meaningful representations for such networks is a fundamental problem in the research area of Network Representation Learning (NRL). NRL approaches aim to translate the network structure into low-dimensional vector representations that are useful to a variety of biomedical applications. Despite significant advances, the existing approaches still have certain limitations. First, a majority of these approaches do not model the unique topological properties of bipartite networks. Consequently, their straightforward application to the bipartite graphs yields unsatisfactory results. Second, the existing approaches typically learn representations from static networks. This is limiting for the biomedical bipartite networks that evolve at a rapid pace, and thus necessitate the development of approaches that can update the representations in an online fashion. Results In this research, we propose a novel representation learning approach that accurately preserves the intricate bipartite structure, and efficiently updates the node representations. Specifically, we design a customized autoencoder that captures the proximity relationship between nodes participating in the bipartite bicliques (2 × 2 sub-graph), while preserving both the global and local structures. Moreover, the proposed structure-preserving technique is carefully interleaved with the central tenets of continual machine learning to design an incremental learning strategy that updates the node representations in an online manner. Taken together, the proposed approach produces meaningful representations with high fidelity and computational efficiency. Extensive experiments conducted on several biomedical bipartite networks validate the effectiveness and rationality of the proposed approach.

Introduction

2020 ◽  
pp. 1-34
Author(s):  
Floris Verhaart
Keyword(s):  
Eighteenth Century ◽  
Close Contact ◽  
Culture Wars ◽  
The Other ◽  
Moral Content ◽  
Key Players ◽  
The One ◽  
United Provinces

This chapter introduces the debate on classical learning, as well as some of the key players in these debates, such as Jean Le Clerc (1657–1736), Pieter Burman (1668–1741), Richard Bentley (1662–1742), and Charles Rollin (1661–1741), against the background of the culture wars of the late seventeenth and early eighteenth centuries. The opposing approaches to Latin and Greek texts are discussed. On the one hand, we find a more text-critically oriented focus that was associated by contemporaries with scholars either operating in the United Provinces or in close contact with Dutch peers. The other approach was associated with French scholars and focused on the historical and moral content of texts. This opposition is helpful in understanding the culture wars at the turn of the eighteenth century as it guards us from simplifying the Quarrel of the Ancients and the Moderns to a straightforward clash between ‘old’ and ‘new’.

scholarly journals Structure-sensitive testimonial norms

2021 ◽  
Vol 11 (3) ◽  
Author(s):  
Benedikt T. A. Höltgen
Keyword(s):  
Network Structure ◽  
The Other ◽  
Local Network ◽  
The Novel ◽  
Scientific Communities ◽  
Agent Based ◽  
Structure Sensitive ◽  
Conventional Structure ◽  
The One ◽  
Size And Structure

AbstractAlthough there has been a lot of investigation into the influence of the network structure of scientific communities on the one hand and into testimonial norms (TNs) on the other, a discussion of TNs that take the network structure into account has been lacking. In this paper, I introduce two TNs which are sensitive to the local network structure. According to these norms, scientists should give less weight to the results of well-connected colleagues, as compared to less connected ones. I employ an Agent Based Model to test the reliability of the two novel TNs against different versions of conventional, structure-insensitive TNs in networks of varying size and structure. The results of the simulations show that the novel TNs are more reliable. This suggests that it would be beneficial for scientific communities if their members followed such norms. For individual scientists, I show that there are both reasons for and reasons against adopting them.

Are You Sure That This Happened? Assessing the Factuality Degree of Events in Text

2012 ◽  
Vol 38 (2) ◽  
pp. 261-299 ◽  
Author(s):  
Roser Saurí ◽  
James Pustejovsky
Keyword(s):  
Computational Model ◽  
Upper Bounds ◽  
Epistemic Modality ◽  
The Other ◽  
Proof Of Concept ◽  
Lower And Upper Bounds ◽  
Information Level ◽  
Two Measures ◽  
The One ◽  
Event Factuality

Identifying the veracity, or factuality, of event mentions in text is fundamental for reasoning about eventualities in discourse. Inferences derived from events judged as not having happened, or as being only possible, are different from those derived from events evaluated as factual. Event factuality involves two separate levels of information. On the one hand, it deals with polarity, which distinguishes between positive and negative instantiations of events. On the other, it has to do with degrees of certainty (e.g., possible, probable), an information level generally subsumed under the category of epistemic modality. This article aims at contributing to a better understanding of how event factuality is articulated in natural language. For that purpose, we put forward a linguistic-oriented computational model which has at its core an algorithm articulating the effect of factuality relations across levels of syntactic embedding. As a proof of concept, this model has been implemented in De Facto, a factuality profiler for eventualities mentioned in text, and tested against a corpus built specifically for the task, yielding an F1 of 0.70 (macro-averaging) and 0.80 (micro-averaging). These two measures mutually compensate for an over-emphasis present in the other (either on the lesser or greater populated categories), and can therefore be interpreted as the lower and upper bounds of the De Facto's performance.

scholarly journals CINNA: An R/CRAN package to decipher Central Informative Nodes in Network Analysis

2017 ◽  
Author(s):  
Minoo Ashtiani ◽  
Mehdi Mirzaie ◽  
Mohieddin Jafari
Keyword(s):  
Network Analysis ◽  
Network Structure ◽  
Dimensional Reduction ◽  
Network Science ◽  
The Other ◽  
Centrality Measures ◽  
Large Network ◽  
Topological Features ◽  
Reduction Methods ◽  
Centrality Analysis

AbstractIn network science, usually there is a critical step known as centrality analysis. This is an important step, since by using centrality measures, a large number of vertices with low priority are set aside and only a few ones remain to be used for further inferential outcomes. In the other words, these measures help us to sieve our large network and distinguish coarse vertices. By that, important decisions could be made based on the circumstances of these vertices on the overall behavior of networks. These vertices are potentially assumed as central or essential nodes. However, the centrality analysis has always been accompanied by a series of ambiguities, since there are a large number of well-known centrality measures, with different algorithms pointing to these essential nodes and there is no well-defined preference. Which measure explore more information in a given network about node essentiality according to the topological features? While here, we tried to provide a pipeline to have a comparison among all proper centrality measures regarding the network structure and choose the most informative one according to dimensional reduction methods. Central Informative Nodes in Network Analysis (CINNA) package is prepared to gather all required function for centrality analysis in the weighted/unweighted and directed/undirected networks.Availability and implementationCINNA is available in CRAN, including a tutorial. URL: https://cran.r-proiect.org/web/packages/CINNA/index.htmlContact:[email protected]

scholarly journals FALCON: a software package for analysis of nestedness in bipartite networks

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 185 ◽  
Author(s):  
Stephen J. Beckett ◽  
Chris A. Boulton ◽  
Hywel T. P. Williams
Keyword(s):  
Species Interactions ◽  
Software Package ◽  
Statistical Significance ◽  
Null Distribution ◽  
Null Models ◽  
Bipartite Network ◽  
Bipartite Networks ◽  
Efficient Calculation ◽  
Two Measures ◽  
Host Parasite

Nestedness is a statistical measure used to interpret bipartite interaction data in several ecological and evolutionary contexts, e.g. biogeography (species-site relationships) and species interactions (plant-pollinator and host-parasite networks). Multiple methods have been used to evaluate nestedness, which differ in how the metrics for nestedness are determined. Furthermore, several different null models have been used to calculate statistical significance of nestedness scores. The profusion of measures and null models, many of which give conflicting results, is problematic for comparison of nestedness across different studies. We developed the FALCON software package to allow easy and efficient comparison of nestedness scores and statistical significances for a given input network, using a selection of the more popular measures and null models from the current literature. FALCON currently includes six measures and five null models for nestedness in binary networks, and two measures and four null models for nestedness in weighted networks. The FALCON software is designed to be efficient and easy to use. FALCON code is offered in three languages (R, MATLAB, Octave) and is designed to be modular and extensible, enabling users to easily expand its functionality by adding further measures and null models. FALCON provides a robust methodology for comparing the strength and significance of nestedness in a given bipartite network using multiple measures and null models. It includes an “adaptive ensemble” method to reduce undersampling of the null distribution when calculating statistical significance. It can work with binary or weighted input networks. FALCON is a response to the proliferation of different nestedness measures and associated null models in the literature. It allows easy and efficient calculation of nestedness scores and statistical significances using different methods, enabling comparison of results from different studies and thereby supporting theoretical study of the causes and implications of nestedness in different biological contexts.

ANCHOR WINDLASSES: A DESIGN PROPOSAL TO STANDARDISE REGULATIONS

2021 ◽  
Vol 157 (A2) ◽  
Author(s):  
J C Carral Couce ◽  
L Carral Couce ◽  
R Villa Caro ◽  
J Á Fraguela Formoso
Keyword(s):  
Economies Of Scale ◽  
Equipment Design ◽  
The Other ◽  
Manufacturing Processes ◽  
Specific Design ◽  
High Quality ◽  
Key Players ◽  
Design And Manufacturing ◽  
The One ◽  
Design Proposal

Shipbuilding is an increasingly competitive field. As the key players in this activity, shipyard managers have to make their counterparts in related industries aware of two conflicting needs. On the one hand, they must produce high quality components that are technologically advanced. On the other, they need equipment that lets them build vessels at a reasonable price. With this second aim in mind, it would be useful to standardise both design and manufacturing processes. At the same time, ship owners always impose regulations. The manufacturers of deck equipment must therefore adapt their product designs to comply with these regulations, some of which have aspects in common. However, guidelines also differ on many points. This makes it difficult to reach desirable levels of standardisation in equipment design. The situation can be summed up in a phrase: for each vessel, a specific design. This article will first provide a comparative overview of current legislation. A proposal for anchor windlass design is then presented in an attempt to make the various regulations more cohesive. The objective here is to reach an acceptable degree of standardisation and, consequently, lower costs by applying economies of scale.

scholarly journals The role of bipartite structure in R&D collaboration networks

2020 ◽  
Vol 8 (4) ◽  
Author(s):  
D Vasques Filho ◽  
Dion R J O’Neale
Keyword(s):  
Collaboration Network ◽  
European Patent ◽  
Bipartite Network ◽  
Bipartite Networks ◽  
Different Types ◽  
Underlying Network ◽  
Network Properties ◽  
Using Data ◽  
The One

Abstract A great number of real-world networks are, in fact, one-mode projections of bipartite networks comprised of two different types of nodes. In the case of interactions between institutions engaging in collaboration for technological innovation, the underlying network is bipartite with institutions (agents) linked to the patents they have filed (artefacts), while the projection is the co-patenting network. Since projected network properties are highly affected by the underlying bipartite structure a lack of understanding of the bipartite network has consequences for the information that might be drawn from the one-mode co-patenting network. Here, we create an empirical bipartite network using data from 2.7 million patents recorded by the European Patent Office. We project this network onto the agents (institutions) and look at properties of both the bipartite and projected networks that may play a role in knowledge sharing and collaboration. We compare these empirical properties to those of synthetic bipartite networks and their projections. We show that understanding the bipartite network topology is critical for understanding the potential flow of technological knowledge. Properties of the bipartite structure, such as degree distributions and small cycles, affect the topology of the one-mode projected network—specifically degree and clustering distributions, and degree assortativity. We propose new network-based metrics as a way to quantify how collaborative agents are in the collaboration network. We find that several large corporations are the most collaborative agents in the network; however, such organizations tend to have a low diversity of collaborators. In contrast, the most prolific institutions tend to collaborate relatively little but with a diverse set of collaborators. This indicates that they concentrate the knowledge of their core technical research while seeking specific complementary knowledge via collaboration with smaller institutions.

Anchor Windlasses: A Design Proposal to Standardise Regulations

2015 ◽  
Vol 157 (A2) ◽  
pp. 95-104 ◽  
Keyword(s):  
Economies Of Scale ◽  
Equipment Design ◽  
The Other ◽  
Manufacturing Processes ◽  
Specific Design ◽  
High Quality ◽  
Key Players ◽  
Design And Manufacturing ◽  
The One ◽  
Design Proposal

"Shipbuilding is an increasingly competitive field. As the key players in this activity, shipyard managers have to make their counterparts in related industries aware of two conflicting needs. On the one hand, they must produce high quality components that are technologically advanced. On the other, they need equipment that lets them build vessels at a reasonable price. With this second aim in mind, it would be useful to standardise both design and manufacturing processes. At the same time, ship owners always impose regulations. The manufacturers of deck equipment must therefore adapt their product designs to comply with these regulations, some of which have aspects in common. However, guidelines also differ on many points. This makes it difficult to reach desirable levels of standardisation in equipment design. The situation can be summed up in a phrase: for each vessel, a specific design. This article will first provide a comparative overview of current legislation. A proposal for anchor windlass design is then presented in an attempt to make the various regulations more cohesive. The objective here is to reach an acceptable degree of standardisation and, consequently, lower costs by applying economies of scale."

Note on Selection of Coordinate Systems for Geodynamics

1975 ◽  
Vol 26 ◽  
pp. 395-407
Author(s):  
S. Henriksen
Keyword(s):  
Sea Level ◽  
The Other ◽  
Coordinate Systems ◽  
Mean Sea Level ◽  
The Earth ◽  
The One ◽  
Static Systems ◽  
Selection Of

The first question to be answered, in seeking coordinate systems for geodynamics, is: what is geodynamics? The answer is, of course, that geodynamics is that part of geophysics which is concerned with movements of the Earth, as opposed to geostatics which is the physics of the stationary Earth. But as far as we know, there is no stationary Earth – epur sic monere. So geodynamics is actually coextensive with geophysics, and coordinate systems suitable for the one should be suitable for the other. At the present time, there are not many coordinate systems, if any, that can be identified with a static Earth. Certainly the only coordinate of aeronomic (atmospheric) interest is the height, and this is usually either as geodynamic height or as pressure. In oceanology, the most important coordinate is depth, and this, like heights in the atmosphere, is expressed as metric depth from mean sea level, as geodynamic depth, or as pressure. Only for the earth do we find “static” systems in use, ana even here there is real question as to whether the systems are dynamic or static. So it would seem that our answer to the question, of what kind, of coordinate systems are we seeking, must be that we are looking for the same systems as are used in geophysics, and these systems are dynamic in nature already – that is, their definition involvestime.

Sign in / Sign up

Export Citation Format

Share Document