Towards Technological Approaches for Concept Maps Mining from Text
DOI:
https://doi.org/10.19153/cleiej.21.1.7Keywords:
concept map, concept map mining, Knowledge RepresentationAbstract
Concept maps are resources for the representation and construction of knowledge. They allow showing, through concepts and relationships, how knowledge about a subject is organized. Technological advances have boosted the development of approaches for the automatic construction of a concept map, to facilitate and provide the benefits of that resource more broadly. Due to the need to better identify and analyze the functionalities and characteristics of those approaches, we conducted a detailed study on technological approaches for automatic construction of concept maps published between 1994 and 2016 in the IEEE Xplore, ACM and Elsevier Science Direct data bases. From this study, we elaborate a categorization defined on two perspectives, Data Source and Graphic Representation, and fourteen categories. That study collected 30 relevant articles, which were applied to the proposed categorization to identify the main features and limitations of each approach. A detailed view on these approaches, their characteristics and techniques are presented enabling a quantitative analysis. In addition, the categorization has given us objective conditions to establish new specification requirements for a new technological approach aiming at concept maps mining from texts.
References
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K. Petersen, R. Feldt, S. Mujtaba, & M. Mattsson. Systematic mapping studies in software engineering. In 12th international conference on evaluation and assessment in software engineering (Vol. 17, No. 1). 2008.
L. Y. Lee, Y. S. Lin, & C. P. Chu. Enhancement of personal concept map constructing for effective assessment. In Teaching, Assessment and Learning for Engineering (TALE), 2012 IEEE International Conference on (pp. W1A-1). IEEE. 2012. DOI: 10.1109/tale.2012.6360395.
M. de la Villa, F. Aparicio, M. J. Maña, & M. de Buenaga. A learning support tool with clinical cases based on concept maps and medical entity recognition. In Proceedings of the 2012 ACM international conference on Intelligent User Interfaces (pp. 61-70). ACM, 2012. DOI: 10.1145/2166966.2166978
M. Al-Sarem, M. Bellafkih, & M. Ramdeni. An approach for mining concepts’ relationships based on historical assessment records. Procedia Engineering, 15, 3245-3249, 2011. DOI: 10.1016/j.proeng.2011.08.609.
M. Elhoseiny, & A. Elgammal. English2mindmap: An automated system for mindmap generation from english text. In Multimedia (ISM), 2012 IEEE International Symposium on (pp. 326-331). IEEE. 2012. DOI: 10.1109/ism.2012.103.
M. Kantardzic, H. Hamdan, & B. Djulbegovic. Artificial Neural Networks (ANN) Approach in Diagnostics of Polycythemia Vera. International Journal of Computers and their Applications, 8, 74-79. 2001.
N. S. Chen, C. W. Wei, & H. J. Chen. Mining e-Learning domain concept map from academic articles. Computers & Education, 50(3), 1009-1021. 2008. DOI: 10.1016/j.compedu.2006.10.001.
N. S. Chen, P. Kinshuk, C. W. Wei, & H. J. Chen. Mining e-learning domain concept map from academic articles. In Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06) (pp. 694-698). IEEE, 2006. DOI: 10.1109/icalt.2006.1652537
N. Yi, & H. Li. A practical approach for automatically constructing concept map in E-learning environments. In Progress in Informatics and Computing (PIC), 2014 International Conference on (pp. 582-586). IEEE. 2014. DOI: 10.1109/pic.2014.6972401
P. Pirnay-Dummer, & D. Ifenthaler. Reading guided by automated graphical representations: How model-based text visualizations facilitate learning in reading comprehension tasks. Instructional Science, 901-919. 2011. DOI: 10.1007/s11251-010-9153-2
R. Richardson, & E. A. Fox . Using concept maps in digital libraries as a cross-language resource discovery tool. In Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries (pp. 256-257). ACM, 2005. DOI: 10.1145/1065385.1065443.
R. Y. Lau, D. Song, Y. Li, T. C. Cheung, & J. X. Hao. Toward a fuzzy domain ontology extraction method for adaptive e-learning. IEEE Transactions on Knowledge and Data Engineering, 21(6), 800-813. 2009. DOI: 10.1109/tkde.2008.137
R. Mitkov. Anaphora resolution: the state of the art. School of Languages and European Studies, University of Wolverhampton. 1999.
R. Feldman, & J. Sanger . The text mining handbook: advanced approaches in analyzing unstructured data. Cambridge University Press. 2007. DOI: 10.1017/cbo9780511546914
R. Tavares. "Aprendizagem significativa, codificação dual e objetos de aprendizagem." Revista Brasileira de Informática na Educação 18.2. 2010. DOI: 10.5753/rbie.2010.18.02.04
S. S. Tseng, P. C. Sue, J. M. Su, J. F. Weng, & W. N. Tsai. A new approach for constructing the concept map. Computers & Education, 49(3), 691-707. 2007. DOI: 10.1016/j.compedu.2005.11.020
S. M. Chen, & P. J. Sue. Constructing concept maps for adaptive learning systems based on data mining techniques. Expert Systems with Applications, 40(7), 2746-2755, 2013. DOI: 10.1016/j.eswa.2012.11.018
S. Lee, Y. Park, & W. C Yoon. Burst analysis for automatic concept map creation with a single document. Expert Systems With Applications, 42(22), 8817-8829, 2015.
S. M. Bai, & S. M. Chen. Automatically constructing concept maps based on fuzzy rules for adapting learning systems. Expert systems with Applications, 35(1), 41-49. 2008. DOI: 10.1016/j.eswa.2007.06.013
S. Wang, & L. Liu. Prerequisite Concept Maps Extraction for Automatic Assessment. In Proceedings of the 25th International Conference Companion on World Wide Web (pp. 519-521). International World Wide Web Conferences Steering Committee, 2016. DOI: 10.1145/2872518.2890463
S. M. Bai and S. M. Bai. A new method for automatically constructing concept maps based on data mining techniques. In: 7th International Conference on Machine Learning and Cybernetics, ICMLC. p. 3078-3083. 2008. DOI: 10.1109/icmlc.2008.4620937
T. B. S. Gava, C. S. de Menezes, and D. Cury. "Aplicações de mapas conceituais na educação como ferramenta metacognitiva." III International Conference on Engineering and Computer Education-ICECE 2003. 2003.
T. Strzalkowski. Natural language information retrieval (Vol. 7). Springer Science & Business Media. 1999. DOI: 10.1007/978-94-017-2388-6
I. Vekiri. What is the value of graphical displays in learning?. Educational Psychology Review, v. 14, n. 3, p. 261-312, 2002.
Y.F. Le Coadic. A ciência da informação. Briquet de lemos Livros, 1996.
W. M. Wang, C. F. Cheung, W. B. Lee, & S. K. Kwok. Mining knowledge from natural language texts using fuzzy associated concept mapping. Information Processing & Management, 44(5), 1707-1719. 2008. DOI: 10.1016/j.ipm.2008.05.002
G. Li, B. C. Ooi, J. Feng, J. Wang, & L. Zhou. EASE: an effective 3-in-1 keyword search method for unstructured, semi-structured and structured data. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data (pp. 903-914). ACM. 2008.
E. K. Jacob. Classification and categorization: a difference that makes a difference. Library trends, 52(3), 515. 2004.
T. T. Gruber et al. A translation approach to portable ontology specifications. Knowledge acquisition, v. 5, n. 2, p. 199-220, 1993. DOI: 10.1006/knac.1993.1008
A. Zouaq, & R. Nkambou. Evaluating the generation of domain ontologies in the knowledge puzzle project. IEEE Transactions on Knowledge and Data Engineering, 21(11), 1559-1572. 2009. DOI: 10.1109/TKDE.2009.25.
A. Pipitone, V. Cannella, & R. Pirrone. Automatic concept maps generation in support of educational processes. Journal of e-Learning and Knowledge Society, 10(1), 2014.
A. M. Olney, W. L. Cade, & C. Williams. Generating concept map exercises from textbooks. In Proceedings of the 6th workshop on innovative use of NLP for building educational applications (pp. 111-119). Association for Computational Linguistics, 2011.
A. Cañas, M. J. Carnot, P. Feltovich, R. R. Hoffman, J. Feltovich, & J. D. Novak. A summary of literature pertaining to the use of concept mapping techniques and technologies for education and performance support. Pensacola, FL. 2003.
C. H. Lee, G. G. Lee, & Y. Leu. Application of automatically constructed concept map of learning to conceptual diagnosis of e-learning. Expert Systems with Applications, 36(2), 1675-1684. 2009. DOI: 10.1016/j.eswa.2007.11.049.
C. Z. Aguiar, & D. Cury. A categorization of technological approaches to concept maps construction. In Learning Objects and Technology (LACLO), Latin American Conference on Learning Objects (pp. 1-9). IEEE. 2016. DOI: 10.1109/LACLO.2016.7751743.
C. Lipizzi, D. G. Dessavre, L. Iandoli, & J. E. R. Marquez. Towards computational discourse analysis: A methodology for mining Twitter backchanneling conversations. Computers in Human Behavior, 782-792, 2016. DOI: 10.1016/j.chb.2016.07.030.
C. C. C. Pérez, & R. Vieira. Mapas Conceituais: geração e avaliação. In Anais do III Workshop em Tecnologia da Informação e da Linguagem Humana. 2005.
D. Biber, S. Conrad, & R. Reppen. Corpus linguistics: Investigating language structure and use. Cambridge University Press. 1998.
D. Nadeau, & S. Sekine. A survey of named entity recognition and classification. Lingvisticae Investigationes, 30(1), 3-26. 2007. DOI: 10.1075/li.30.1.03nad.
D. B. Leake, A. Maguitman, T. Reichherzer, A. J. Cañas, M. Carvalho, M. Arguedas and T. Eskridge. Aiding knowledge capture by searching for extensions of knowledge models. In Proceedings of the 2nd international conference on Knowledge capture (pp. 44-53). ACM, 2003. DOI: 10.1145/945645.945655
E. L. Karannagoda, H. M. T. C. Herath, K. N. J. Fernando, M. W. I. D. Karunarathne, N. H. N. D. De Silva, & A. S. Perera. Document analysis based automatic concept map generation for enterprises. In Advances in ICT for Emerging Regions (ICTer), 2013 International Conference on (pp. 154-159). IEEE. 2013. DOI: 10.1109/icter.2013.6761171.
H. Lee, A. Chang, Y. Peirsman, N. Chambers, M. Surdeanu, & D. Jurafsky. Deterministic coreference resolution based on entity-centric, precision-ranked rules. Computational Linguistics, 39(4), 885-916. 2013. DOI: 10.1162/coli_a_00152.
H. P. Luhn. A statistical approach to mechanized encoding and searching of literary information. IBM Journal of research and development, 1(4), 309-317. 1957. DOI: 10.1147/rd.14.0309
I. Bichindaritz, & S. Akkineni. Concept mining for indexing medical literature. Engineering Applications of Artificial Intelligence, 19(4), 411-417, 2006. DOI: 10.1007/11510888_68.
I. Qasim, J. W. Jeong, J. U. Heu, & D. H. Lee. Concept map construction from text documents using affinity propagation. Journal of Information Science, 39(6), 719-736. 2013. DOI: 10.1177/0165551513494645.
I. Vekiri. What is the value of graphical displays in learning?. Educational Psychology Review, 14(3). 2002.
J. H. Lee, & A. Segev. Knowledge maps for e-learning. Computers & Education, 59(2), 353-364, 2012. DOI: 10.1016/j.compedu.2012.01.017
J. D. Novak, & A. J. Cañas. A teoria subjacente aos mapas conceituais e como elaborá-los e usá-los. Práxis Educativa, 5(1), 9-29. 2010. DOI: 10.5212/praxeduc.v.5i1.009029.
K. McGarry and H. V. de Lemos. O contexto dinânico da informação: uma análise introdutória. Briquet de Lemos, 1999.
K. Zubrinic, D. Kalpic, & M. Milicevic (2012). The automatic creation of concept maps from documents written using morphologically rich languages. Expert systems with applications, 39(16), 12709-12718. DOI: 10.1016/j.eswa.2012.04.065
K. Žubrini?, I. Obradovi?, & T. Sjekavica. Implementation of method for generating concept map from unstructured text in the Croatian language. In Software, Telecommunications and Computer Networks (SoftCOM), 2015 23rd International Conference on (pp. 220-223). IEEE. 2015. DOI: 10.1109/softcom.2015.7314098.
K. Petersen, R. Feldt, S. Mujtaba, & M. Mattsson. Systematic mapping studies in software engineering. In 12th international conference on evaluation and assessment in software engineering (Vol. 17, No. 1). 2008.
L. Y. Lee, Y. S. Lin, & C. P. Chu. Enhancement of personal concept map constructing for effective assessment. In Teaching, Assessment and Learning for Engineering (TALE), 2012 IEEE International Conference on (pp. W1A-1). IEEE. 2012. DOI: 10.1109/tale.2012.6360395.
M. de la Villa, F. Aparicio, M. J. Maña, & M. de Buenaga. A learning support tool with clinical cases based on concept maps and medical entity recognition. In Proceedings of the 2012 ACM international conference on Intelligent User Interfaces (pp. 61-70). ACM, 2012. DOI: 10.1145/2166966.2166978
M. Al-Sarem, M. Bellafkih, & M. Ramdeni. An approach for mining concepts’ relationships based on historical assessment records. Procedia Engineering, 15, 3245-3249, 2011. DOI: 10.1016/j.proeng.2011.08.609.
M. Elhoseiny, & A. Elgammal. English2mindmap: An automated system for mindmap generation from english text. In Multimedia (ISM), 2012 IEEE International Symposium on (pp. 326-331). IEEE. 2012. DOI: 10.1109/ism.2012.103.
M. Kantardzic, H. Hamdan, & B. Djulbegovic. Artificial Neural Networks (ANN) Approach in Diagnostics of Polycythemia Vera. International Journal of Computers and their Applications, 8, 74-79. 2001.
N. S. Chen, C. W. Wei, & H. J. Chen. Mining e-Learning domain concept map from academic articles. Computers & Education, 50(3), 1009-1021. 2008. DOI: 10.1016/j.compedu.2006.10.001.
N. S. Chen, P. Kinshuk, C. W. Wei, & H. J. Chen. Mining e-learning domain concept map from academic articles. In Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06) (pp. 694-698). IEEE, 2006. DOI: 10.1109/icalt.2006.1652537
N. Yi, & H. Li. A practical approach for automatically constructing concept map in E-learning environments. In Progress in Informatics and Computing (PIC), 2014 International Conference on (pp. 582-586). IEEE. 2014. DOI: 10.1109/pic.2014.6972401
P. Pirnay-Dummer, & D. Ifenthaler. Reading guided by automated graphical representations: How model-based text visualizations facilitate learning in reading comprehension tasks. Instructional Science, 901-919. 2011. DOI: 10.1007/s11251-010-9153-2
R. Richardson, & E. A. Fox . Using concept maps in digital libraries as a cross-language resource discovery tool. In Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries (pp. 256-257). ACM, 2005. DOI: 10.1145/1065385.1065443.
R. Y. Lau, D. Song, Y. Li, T. C. Cheung, & J. X. Hao. Toward a fuzzy domain ontology extraction method for adaptive e-learning. IEEE Transactions on Knowledge and Data Engineering, 21(6), 800-813. 2009. DOI: 10.1109/tkde.2008.137
R. Mitkov. Anaphora resolution: the state of the art. School of Languages and European Studies, University of Wolverhampton. 1999.
R. Feldman, & J. Sanger . The text mining handbook: advanced approaches in analyzing unstructured data. Cambridge University Press. 2007. DOI: 10.1017/cbo9780511546914
R. Tavares. "Aprendizagem significativa, codificação dual e objetos de aprendizagem." Revista Brasileira de Informática na Educação 18.2. 2010. DOI: 10.5753/rbie.2010.18.02.04
S. S. Tseng, P. C. Sue, J. M. Su, J. F. Weng, & W. N. Tsai. A new approach for constructing the concept map. Computers & Education, 49(3), 691-707. 2007. DOI: 10.1016/j.compedu.2005.11.020
S. M. Chen, & P. J. Sue. Constructing concept maps for adaptive learning systems based on data mining techniques. Expert Systems with Applications, 40(7), 2746-2755, 2013. DOI: 10.1016/j.eswa.2012.11.018
S. Lee, Y. Park, & W. C Yoon. Burst analysis for automatic concept map creation with a single document. Expert Systems With Applications, 42(22), 8817-8829, 2015.
S. M. Bai, & S. M. Chen. Automatically constructing concept maps based on fuzzy rules for adapting learning systems. Expert systems with Applications, 35(1), 41-49. 2008. DOI: 10.1016/j.eswa.2007.06.013
S. Wang, & L. Liu. Prerequisite Concept Maps Extraction for Automatic Assessment. In Proceedings of the 25th International Conference Companion on World Wide Web (pp. 519-521). International World Wide Web Conferences Steering Committee, 2016. DOI: 10.1145/2872518.2890463
S. M. Bai and S. M. Bai. A new method for automatically constructing concept maps based on data mining techniques. In: 7th International Conference on Machine Learning and Cybernetics, ICMLC. p. 3078-3083. 2008. DOI: 10.1109/icmlc.2008.4620937
T. B. S. Gava, C. S. de Menezes, and D. Cury. "Aplicações de mapas conceituais na educação como ferramenta metacognitiva." III International Conference on Engineering and Computer Education-ICECE 2003. 2003.
T. Strzalkowski. Natural language information retrieval (Vol. 7). Springer Science & Business Media. 1999. DOI: 10.1007/978-94-017-2388-6
I. Vekiri. What is the value of graphical displays in learning?. Educational Psychology Review, v. 14, n. 3, p. 261-312, 2002.
Y.F. Le Coadic. A ciência da informação. Briquet de lemos Livros, 1996.
W. M. Wang, C. F. Cheung, W. B. Lee, & S. K. Kwok. Mining knowledge from natural language texts using fuzzy associated concept mapping. Information Processing & Management, 44(5), 1707-1719. 2008. DOI: 10.1016/j.ipm.2008.05.002
G. Li, B. C. Ooi, J. Feng, J. Wang, & L. Zhou. EASE: an effective 3-in-1 keyword search method for unstructured, semi-structured and structured data. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data (pp. 903-914). ACM. 2008.
E. K. Jacob. Classification and categorization: a difference that makes a difference. Library trends, 52(3), 515. 2004.
T. T. Gruber et al. A translation approach to portable ontology specifications. Knowledge acquisition, v. 5, n. 2, p. 199-220, 1993. DOI: 10.1006/knac.1993.1008
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