Corpus Linguistics, Network Analysis and Co-occurrence Matrices

被引:0
|
作者
Stuart, Keith [1 ]
Botella, Ana [1 ]
机构
[1] Univ Politecn Valencia, Valencia, Spain
来源
INTERNATIONAL JOURNAL OF ENGLISH STUDIES | 2009年 / 9卷 / 03期
关键词
corpus linguistics; co-occurrence matrices; semantic networks; knowledge discovery;
D O I
暂无
中图分类号
H [语言、文字];
学科分类号
05 ;
摘要
This article describes research undertaken in order to design a methodology for the reticular representation of knowledge of a specific discourse community. To achieve this goal, a representative corpus of the scientific production of the members of this discourse community (Universidad Politecnica de Valencia, UPV) was created. The article presents the practical analysis (frequency, keyword, collocation and cluster analysis) that was carried out in the initial phases of the study aimed at establishing the theoretical and practical background and framework for our matrix and network analysis of the scientific discourse of the UPV. In the methodology section, the processes that have allowed us to extract from the corpus the linguistic elements needed to develop co-occurrence matrices, as well as the computer tools used in the research, are described. From these co-occurrence matrices, semantic networks of subject and discipline knowledge were generated. Finally, based on the results obtained, we suggest that it may be viable to extract and to represent the intellectual capital of an academic institution using corpus linguistics methods in combination with the formulations of network theory.
引用
收藏
页码:1 / 20
页数:20
相关论文
共 50 条
  • [1] Co-occurrence matrices for volumetric data
    Kurani, AS
    Xu, DH
    Furst, J
    Raicu, DS
    Proceedings of the Seventh IASTED International Conference on Computer Graphics and Imaging, 2004, : 447 - 452
  • [2] The reflection of hierarchical cluster analysis of co-occurrence matrices in SPSS
    Qiuju ZHOU
    Fuhai LENG
    Loet LEYDESDORFF
    Journal of Data and Information Science, 2015, 8 (02) : 11 - 24
  • [3] TEXTURE CLASSIFICATION WITH FUZZY COLOR CO-OCCURRENCE MATRICES
    Ledoux, Audrey
    Losson, Olivier
    Macaire, Ludovic
    2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2015, : 1429 - 1433
  • [4] Valence extraction using EM selection and co-occurrence matrices
    Łukasz Dębowski
    Language Resources and Evaluation, 2009, 43 : 301 - 327
  • [5] Iris Authentication Utilizing Co-occurrence Matrices and Textile Features
    Triantafyllou, Dimitra
    Stavropoulos, Georgios
    Tzovaras, Dimitrios
    2019 10TH INTERNATIONAL CONFERENCE ON SPEECH TECHNOLOGY AND HUMAN-COMPUTER DIALOGUE (SPED), 2019,
  • [6] Valence extraction using EM selection and co-occurrence matrices
    Debowski, Lukasz
    LANGUAGE RESOURCES AND EVALUATION, 2009, 43 (04) : 301 - 327
  • [7] A multilayer network analysis of hashtags in twitter via co-occurrence and semantic links
    Turker, Ilker
    Sulak, Eyub Ekmel
    INTERNATIONAL JOURNAL OF MODERN PHYSICS B, 2018, 32 (04):
  • [8] Barrett's Esophagus Identification Using Color Co-occurrence Matrices
    de Souza, Luis A., Jr.
    Ebigbo, Alanna
    Probst, Andreas
    Messmann, Helmut
    Papa, Joao P.
    Mendel, Robert
    Palm, Christoph
    PROCEEDINGS 2018 31ST SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 2018, : 166 - 173
  • [9] Action recognition using graph embedding and the co-occurrence matrices descriptor
    Zheng, Feng
    Shao, Ling
    Song, Zhan
    Chen, Xi
    INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, 2011, 88 (18) : 3896 - 3914
  • [10] Analysis of Three Dimensional Textures Through use of Photometric Stereo, Co-occurrence Matrices and Neural Networks
    Smith, Lyndon N.
    Smith, Melvyn L.
    INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2009 (ICCMSE 2009), 2012, 1504 : 1205 - 1209