Analysis of SIGMOD's co-authorship graph

Nascimento, Mário A.; Pound, Jeffrey

doi:10.1145/945721.945722

Cited by 112 publications

(79 citation statements)

References 2 publications

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“…Currently, the scriptLattes is being improved with the purpose of have a more general and efficient system. Future improvements aims at exploring the analysis about co-authoring networks 2,17,20,28 , measuring and extracting proximity in networks 14 , finding and evaluating community structure in networks 21 , and applying ontologies 4,25 . We believe that these new approaches will allow more contributions to the extraction and management of knowledge from the Lattes platform.…”

Section: Discussionmentioning

confidence: 99%

“…In the generated graph, it is possible to observe the collaboration among members and clusters of cooperation. This graph is an instrument that helps to discover the researchers with more activity of co-authoring within the group and could be used in detailed analysis of co-authoring as 17,20,28 .…”

Section: Collaboration Graph Generationmentioning

confidence: 99%

“…Many of the issues in this research appear from the low degree of structure of the data as well as the ambiguities often present 9,22,27 . Another important issue is the analysis of the networks themselves 14,17,20,28 .…”

Section: Introductionmentioning

confidence: 99%

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ScriptLattes: an open-source knowledge extraction system from the Lattes platform

Mena‐Chalco¹,

César²

2009

J. Braz. Comp. Soc.

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Abstract:The Lattes platform is the major scientific information system maintained by the National Council for Scientific and Technological Development (CNPq). This platform allows to manage the curricular information of researchers and institutions working in Brazil based on the so called Lattes Curriculum. However, the public information is individually available for each researcher, not providing the automatic creation of reports of several scientific productions for research groups. It is thus difficult to extract and to summarize useful knowledge for medium to large size groups of researchers. This paper describes the design, implementation and experiences with scriptLattes: an open-source system to create academic reports of groups based on curricula of the Lattes Database. The scriptLattes system is composed by the following modules: (a) data selection, (b) data preprocessing, (c) redundancy treatment, (d) collaboration graph generation among group members, (e) research map generation based on geographical information, and (f) automatic report creation of bibliographical, technical and artistic production, and academic supervisions. The system has been extensively tested for a large variety of research groups of Brazilian institutions, and the generated reports have shown an alternative to easily extract knowledge from data in the context of Lattes platform. The source code, usage instructions and examples are available at http://scriptlattes.sourceforge.net/.

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Section: Discussionmentioning

confidence: 99%

Section: Collaboration Graph Generationmentioning

confidence: 99%

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ScriptLattes: an open-source knowledge extraction system from the Lattes platform

Mena‐Chalco¹,

César²

2009

J. Braz. Comp. Soc.

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“…Important results on researcher community mining have been revealed by analysis of a co-relation (e.g., co-authorship in a paper or co-starring in a movie) graph. Nascimento et al [15] and Smeaton et al [21] show co-authorship graphs for several selected conferences are small world graphs 3 and calculate the average distance between pairs of authors. Similarly, the Erdös Number Project 4 and the Oracle of Bacon 5 compute the minimum path length between one fixed person and all other people in the graph.…”

Section: Community Miningmentioning

confidence: 99%

Mining Research Communities in Bibliographical Data

Zaı̈ane

Chen

Goebel

2009

Advances in Web Mining and Web Usage Analysis

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Abstract. Extracting information from very large collections of structured, semistructured or even unstructured data can be a considerable challenge when much of the hidden information is implicit within relationships among entities in the data. Social networks are such data collections in which relationships play a vital role in the knowledge these networks can convey. A bibliographic database is an essential tool for the research community, yet finding and making use of relationships comprised within such a social network is difficult. In this paper we introduce DBconnect, a prototype that exploits the social network coded within the DBLP database by drawing on a new random walk approach to reveal interesting knowledge about the research community and even recommend collaborations.

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“…Their objective was to determine the topics that appear most frequently; however, they did not visualize the results or include any citation analysis. Nascimento et al [8] constructed a co-authorship graph of all the papers published by SIGMOD between 1975 and 2002. Lee et al [9] developed a visualization tool called PaperLens, which allows researchers to identify the trends and topics in a field.…”

Section: Literature Reviewmentioning

confidence: 99%

Using “Cited by” Information to Find the Context of Research Papers

Wang

Day

et al. 2008

Intelligence and Security Informatics

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Abstract. This paper proposes a novel method of analyzing data to find important information about the context of research papers. The proposed CCTVA (Collecting, Cleaning, Translating, Visualizing, and Analyzing) method helps researchers find the context of papers on topics of interest. Specifically, the method provides visualization information that maps a research topic's evolution and links to other papers based on the results of Google Scholar and CiteSeer. CCTVA provides two types of information: one type shows the paper's title and the author, while the other shows the paper's title and the reference. The goal of CCTVA is enable both novices and experts to gain insight into how a field's topics evolve over time. In addition, by using linkage analysis and visualization, we identify five special phenomena that can help researchers conduct literature reviews.

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Analysis of SIGMOD's co-authorship graph

Cited by 112 publications

References 2 publications

ScriptLattes: an open-source knowledge extraction system from the Lattes platform

ScriptLattes: an open-source knowledge extraction system from the Lattes platform

Mining Research Communities in Bibliographical Data

Using “Cited by” Information to Find the Context of Research Papers

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