Six degrees of cohesion in patent citation network

While the phrase “six degrees of separation” is widely used to characterize a variety of humanderived networks, in this study we show that in patent citation network, related patents are connected with an average distance of 6, whereas an average distance for a random pair of nodes in the graph is approximately 15. We use this information to improve the recall level in prior-art retrieval in the setting of blind relevance feedback without any textual knowledge.

Ordered weighted averaging operators 1988-2014:a citation-based literature survey

This study surveys the ordered weighted averaging (OWA) operator literature using a citation network analysis. The main goals are the historical reconstruction of scientific development of the OWA field, the identification of the dominant direction of knowledge accumulation that emerged since the publication of the first OWA paper, and to discover the most active lines of research. The results suggest, as expected, that Yager's paper (IEEE Trans. Systems Man Cybernet, 18(1), 183-190, 1988) is the most influential paper and the starting point of all other research using OWA. Starting from his contribution, other lines of research developed and we describe them.

Tracing the evolution of physics on the backbone of citation networks

Many innovations are inspired by past ideas in a nontrivial way. Tracing these origins and identifying scientific branches is crucial for research inspirations. In this paper, we use citation relations to identify the descendant chart, i.e., the family tree of research papers. Unlike other spanning trees that focus on cost or distance minimization, we make use of the nature of citations and identify the most important parent for each publication, leading to a treelike backbone of the citation network. Measures are introduced to validate the backbone as the descendant chart. We show that citation backbones can well characterize the hierarchical and fractal structure of scientific development, and lead to an accurate classification of fields and subfields. © 2011 American Physical Society.

Investigadores de mayor visibilidad en Organización y Representación del Conocimiento: un estudio desde el análisis de cocitaciones

The most visible researchers in Knowledge Organization and Representation were identified, from the perspective of Brazilian researchers, based on cocitations from the papers presented in the last five meetings of the Encontros Nacionais de Pesquisa of the Associação Nacional de Pesquisa e Pós- Graduação em Ciência da Informação (ENANCIBs) from 2003 to 2008. First, the total number of references was identified, a total of 134 articles. Second, a citation analysis was conducted, being considered the most cited authors those who received 12 citations or more, which resulted in 31 most cited authors. Third, the Pajek software was used for the construction of the co-citation network and, thereafter, some indicators were calculated with the Ucinet software, which describe the structure and cohesion of the generated network, and, particularly, its density, and its degree of centrality, betweenness and proximity. The high cohesion of the network and the compliance between the most co-cited authors and the calculated indicators were verified.

Estudos de Análise de Cocitação de Autores: uma abordagem teórico-metodológica para a compreensão de um domínio

This piece of research aims at analyzing the absolute and relative co-citation indicators, especially Salton’s Cosine and comparing the contribution of these indicators to the understanding of a domain, applying them to the universe of "Metric Studies" at the BRAPCI base. It also aims at presenting the co-citation network generated from the absolute frequencies and highlighting the groupings of co-cited authors, depending on the relative values, integrating and explaining the information from the two indexes. The domain analysis, by means of its 11 approaches, including “Bibliometric Studies”, focuses on the science characterization and evaluation, in that it allows us to identify and to analyze the conditions under which the scientific knowledge is constructed and socialized. In these studies, the contribution of citation and co-citation analysis is highlighted. Of the total of 147 articles retrieved at BRAPCI base, the authors cited in at least 11 articles, in a total of 38 researchers, were selected. The 38 x 38 symmetric matrix with the absolute frequencies of co-citation and the matrix with the relative values of Salton’s Cosine were generated. The co-citation network with absolute frequency values were constructed, through Ucinet software. Cluster analysis of data with relative values wer performed, using the SPSS software. Significant differences between the absolute and relative indexes, with some high absolute values of co-citation were observed; when considered in relation to the presence of each author, their significance is decreased. As to the generated network, seven groups were determined, in which only one is established for close themes and comes from co-citations in the original sense of the term. Five groups present closeness in absolute and relative indicators. It can be concluded about the importance of the studies of authors' co-citation analysis, which associate the two indexes, absolute and relative, in order to visualize and understand the underlying structures of a scientific domain.

Visibilidade dos pesquisadores no periódico Scientometrics a partir da perspectiva brasileira: um estudo de cocitação

This research aims at verifying the authors who have given basis to the brazilian researches internationally inserted in the area of Bibliometrics and Scientometrics through the analysis of citation and co-citation of the brazilian articles published in the journal Scientometrics. We used the Scopus data base, with the terms Scientometrics in source title and Brasil or Brazil in affiliation country. We found 53 articles, with 741 references and 19 authors cited 3 or more times. In general, the researchers come from the biologic and health areas. Using the Ucinet software, we build the co-citation network and calculated its indicators. We calculated the co-citation normalized index. The density and average of normalized degree centrality were 65,5%. We concluded the research highlighting the significant presence of brazilians (32%) and the dialogicity occurring between cited Brazilians and foreigners within a balance, where brazilians already dialog with renowned international researchers of the Bibliometrics and Scientometrics area.

Visibilidade dos pesquisadores no GT7 da ANCIB: um estudo de cocitações

This research aims at analyzing the researchers with major insertion and impact within the GT7 ENANCIB community, through an analysis study of citation and co-citation from 2003 to 2010. We propose to highlight the researchers cited in a greater number of papers, as well as the number of citations received. Also, to describe the co-citation network intending to analyze the interlocution network built by the writers towards the cited ones and calculate the indicators of density and centrality of the network. As for the theoretical-methodological basis, we used the Domain Analysis (D.A.), seen as the reflexion of a discourse community. Among the 11 approaches about D.A, the bibliometric studies stand out. Data from the 124 researches presented in the period of this study showed 1446 cited researches for a total of 2307 citations. From the total number of cited researchers in a greater number of papers, 33 were considered authors of major impact and visibility, being cited in at least 8 papers, thus getting at least 8 citations. The software Ucinet was used to map and visualize the net of interlocution established by the citing papers. As for the results, we could notice that, from the total of 33 researchers, 23 are Brazilian, 20 take part in Post-Graduation Programs and 11 are granted CNPq scholarships of productivity. Furthermore, we highlighted the most cited themes and analyzed the relationship involving the number of citations according to the number of papers in which the researcher was cited and the number of researches cited from each researcher. Regarding the network structure, we could observe that the authors form a single component, indicating that the group of researchers co-cited reveals proximity and theoretical, conceptual and methodological articulations. We concluded that the citing community adopts ordinary theoretical schools; moreover, we might characterize the core of the known researchers as a foundation for the knowledge of the GT7 theme.

A construção do conhecimento sobre governança corporativa: uma análise bibliométrica

Presents a survey of scientific production about the subject corporate governance, using the Bibliometric analysis of theses and dissertations collected in the digital libraries of the Sao Paulo State University (Unesp), Campinas State University (UNICAMP) and University of Sao Paulo (USP). Through the data collected were identified, based on Bibliometric indicators, the origin of authors, the authors more cited, the thematic area of authors, and the construction of co-citation network.

Using complex networks concepts to assess approaches for citations in scientific papers

The number of citations received by authors in scientific journals has become a major parameter to assess individual researchers and the journals themselves through the impact factor. A fair assessment therefore requires that the criteria for selecting references in a given manuscript should be unbiased with regard to the authors or journals cited. In this paper, we assess approaches for citations considering two recommendations for authors to follow while preparing a manuscript: (i) consider similarity of contents with the topics investigated, lest related work should be reproduced or ignored; (ii) perform a systematic search over the network of citations including seminal or very related papers. We use formalisms of complex networks for two datasets of papers from the arXiv and the Web of Science repositories to show that neither of these two criteria is fulfilled in practice. By representing the texts as complex networks we estimated a similarity index between pieces of texts and found that the list of references did not contain the most similar papers in the dataset. This was quantified by calculating a consistency index, whose maximum value is one if the references in a given paper are the most similar in the dataset. For the areas of "complex networks" and "graphenes", the consistency index was only 0.11-0.23 and 0.10-0.25, respectively. To simulate a systematic search in the citation network, we employed a traditional random walk search (i.e. diffusion) and a random walk whose probabilities of transition are proportional to the number of the ingoing edges of the neighbours. The frequency of visits to the nodes (papers) in the network had a very small correlation with either the actual list of references in the papers or with the number of downloads from the arXiv repository. Therefore, apparently the authors and users of the repository did not follow the criterion related to a systematic search over the network of citations. Based on these results, we propose an approach that we believe is fairer for evaluating and complementing citations of a given author, effectively leading to a virtual scientometry.

Institutional Persistence and Change in England's Common Law: 1700-1865

Institutions are widely regarded as important, even ultimate drivers of economic growth and performance. A recent mainstream of institutional economics has concentrated on the effect of persisting, often imprecisely measured institutions and on cataclysmic events as agents of noteworthy institutional change. As a consequence, institutional change without large-scale shocks has received little attention. In this dissertation I apply a complementary, quantitative-descriptive approach that relies on measures of actually enforced institutions to study institutional persistence and change over a long time period that is undisturbed by the typically studied cataclysmic events. By placing institutional change into the center of attention one can recognize different speeds of institutional innovation and the continuous coexistence of institutional persistence and change. Specifically, I combine text mining procedures, network analysis techniques and statistical approaches to study persistence and change in England’s common law over the Industrial Revolution (1700-1865). Based on the doctrine of precedent - a peculiarity of common law systems - I construct and analyze the apparently first citation network that reflects lawmaking in England. Most strikingly, I find large-scale change in the making of English common law around the turn of the 19th century - a period free from the typically studied cataclysmic events. Within a few decades a legal innovation process with low depreciation rates (1 to 2 percent) and strong past-persistence transitioned to a present-focused innovation process with significantly higher depreciation rates (4 to 6 percent) and weak past-persistence. Comparison with U.S. Supreme Court data reveals a similar U.S. transition towards the end of the 19th century. The English and U.S. transitions appear to have unfolded in a very specific manner: a new body of law arose during the transitions and developed in a self-referential manner while the existing body of law lost influence, but remained prominent. Additional findings suggest that Parliament doubled its influence on the making of case law within the first decades after the Glorious Revolution and that England’s legal rules manifested a high degree of long-term persistence. The latter allows for the possibility that the often-noted persistence of institutional outcomes derives from the actual persistence of institutions.

An intuitive dashboard for Bayesian network inference

Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.

Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific sub-regions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

Improving Performance of Result Caches in Network Processors

Digest caches have been proposed as an effective method tospeed up packet classification in network processors. In this paper, weshow that the presence of a large number of small flows and a few largeflows in the Internet has an adverse impact on the performance of thesedigest caches. In the Internet, a few large flows transfer a majority ofthe packets whereas the contribution of several small flows to the totalnumber of packets transferred is small. In such a scenario, the LRUcache replacement policy, which gives maximum priority to the mostrecently accessed digest, tends to evict digests belonging to the few largeflows. We propose a new cache management algorithm called SaturatingPriority (SP) which aims at improving the performance of digest cachesin network processors by exploiting the disparity between the number offlows and the number of packets transferred. Our experimental resultsdemonstrate that SP performs better than the widely used LRU cachereplacement policy in size constrained caches. Further, we characterizethe misses experienced by flow identifiers in digest caches.

Network Reconstruction from dynamic data

Over the past decade, many powerful data mining techniques have been developed to analyze temporal and sequential data. The time is now fertile for addressing problems of larger scope under the purview of temporal data mining. The fourth SIGKDD workshop on temporal data mining focused on the question: What can we infer about the structure of a complex dynamical system from observed temporal data? The goals of the workshop were to critically evaluate the need in this area by bringing together leading researchers from industry and academia, and to identify promising technologies and methodologies for doing the same. We provide a brief summary of the workshop proceedings and ideas arising out of the discussions.

Efficient Regular Expression Pattern Matching for Network Intrusion Detection Systems using Modified Word-based Automata

Network Intrusion Detection Systems (NIDS) intercept the traffic at an organization's network periphery to thwart intrusion attempts. Signature-based NIDS compares the intercepted packets against its database of known vulnerabilities and malware signatures to detect such cyber attacks. These signatures are represented using Regular Expressions (REs) and strings. Regular Expressions, because of their higher expressive power, are preferred over simple strings to write these signatures. We present Cascaded Automata Architecture to perform memory efficient Regular Expression pattern matching using existing string matching solutions. The proposed architecture performs two stage Regular Expression pattern matching. We replace the substring and character class components of the Regular Expression with new symbols. We address the challenges involved in this approach. We augment the Word-based Automata, obtained from the re-written Regular Expressions, with counter-based states and length bound transitions to perform Regular Expression pattern matching. We evaluated our architecture on Regular Expressions taken from Snort rulesets. We were able to reduce the number of automata states between 50% to 85%. Additionally, we could reduce the number of transitions by a factor of 3 leading to further reduction in the memory requirements.