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  • 2017

    Case Studies

    Liu, H. & Cocea, M., 23 Nov 2017, Granular Computing Based Machine Learning : A Big Data Processing Approach. Liu, H. & Cocea, M. (eds.). Springer Nature, p. 77-88 12 p. (Studies in Big Data; vol. 35).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Conclusion

    Liu, H. & Cocea, M., 23 Nov 2017, Granular Computing Based Machine Learning: A Big Data Processing Approach. Liu, H. & Cocea, M. (eds.). Springer Nature, p. 89-99 11 p. (Studies in Big Data; vol. 35).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Fuzzy classification through generative multi-task learning

    Liu, H. & Cocea, M., 23 Nov 2017, Granular Computing Based Machine Learning: A Big Data Processing Approach. Liu, H. & Cocea, M. (eds.). Springer Nature, p. 37-47 11 p. (Studies in Big Data; vol. 35).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Introduction

    Liu, H. & Cocea, M., 23 Nov 2017, Granular Computing Based Machine Learning: A Big Data Processing Approach. Liu, H. & Cocea, M. (eds.). Springer Nature, p. 1-10 10 p. (Studies in Big Data; vol. 35).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Multi-granularity rule learning

    Liu, H. & Cocea, M., 23 Nov 2017, Granular Computing Based Machine Learning: A Big Data Processing Approach. Liu, H. & Cocea, M. (eds.). Springer Nature, p. 67-76 10 p. (Studies in Big Data; vol. 35).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Multi-granularity semi-random data partitioning

    Liu, H. & Cocea, M., 5 Nov 2017, Granular Computing Based Machine Learning. Springer, p. 49-65 17 p. (Studies in Big Data; vol. 35).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Nature inspired semi-heuristic learning

    Liu, H. & Cocea, M., 5 Nov 2017, Granular Computing Based Machine Learning. Springer, p. 29-36 8 p. (Studies in Big Data; vol. 35).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Semi-supervised learning through machine based labelling

    Liu, H. & Cocea, M., 5 Nov 2017, Semi-supervised Learning Through Machine Based Labelling. In: Granular Computing Based Machine Learning. Springer, p. 23-28 6 p. (Studies in Big Data; vol. 35).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Traditional machine learning

    Liu, H. & Cocea, M., 5 Nov 2017, Granular Computing Based Machine Learning. Springer, p. 11-22 12 p. (Studies in Big Data; vol. 35).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Unified framework for control of machine learning tasks towards effective and efficient processing of big data

    Liu, H., Gegov, A. & Cocea, M., 2017, Data Science and Big Data: An Environment of Computational Intelligence. Pedrycz, W. & Chen, S-M. (eds.). Springer, p. 123-140 18 p. (Studies in Big Data; vol. 24).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • 2016

    Interpretability of computational models for sentiment analysis

    Liu, H., Cocea, M. & Gegov, A. E., 23 Mar 2016, Sentiment analysis and ontology engineering: An environment of computational intelligence . Pedrycz, W. & Chen, S-M. (eds.). Switzerland: Springer, p. 199-220 22 p. (Studies in Computational Intelligence; vol. 639).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

    Open Access
  • 2015

    Case studies

    Liu, H., Gegov, A. & Cocea, M., 17 Sept 2015, Rule Based Systems for Big Data: A Machine Learning Approach. 1st ed. Springer, p. 81-95 15 p. (Studies in Big Data; vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Conclusion

    Liu, H., Gegov, A. & Cocea, M., 17 Sept 2015, Rule Based Systems for Big Data: A Machine Learning Approach. 1st ed. Springer, p. 97-114 18 p. (Studies in Big Data; vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Ensemble learning approaches

    Liu, H., Gegov, A. & Cocea, M., 17 Sept 2015, Rule Based Systems for Big Data: A Machine Learning Approach. 1st ed. Springer, p. 63-73 11 p. (Studies in Big Data; vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Generation of classification rules

    Liu, H., Gegov, A. & Cocea, M., 17 Sept 2015, Rule Based Systems for Big Data: A Machine Learning Approach. 1st ed. Springer, p. 29-42 14 p. (Studies in Big Data; vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Interpretability analysis

    Liu, H., Gegov, A. & Cocea, M., 17 Sept 2015, Rule Based Systems for Big Data: A Machine Learning Approach. 1st ed. Springer, p. 75-80 6 p. (Studies in Big Data; vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Introduction

    Liu, H., Gegov, A. & Cocea, M., 17 Sept 2015, Rule Based Systems for Big Data: A Machine Learning Approach. 1st ed. Springer, p. 1-9 9 p. (Studies in Big Data; vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Predicting learning-related emotions from students' textual classroom feedback via Twitter.

    Altrabsheh, N., Cocea, M. & Fallahkhair, S., 2015, The 8th International Conference on Educational Data Mining : EDM 2015. Santos, O. C., Boticario, J. G., Romero, C., Pechenizkiy, M., Merceron, A., Mitros, P., Luna, J. M., Mihaescu, C., Moreno, P., Hershkovitz, A., Ventura, S. & Desmarais, M. (eds.). International Educational Data Mining Society, p. 436-440

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Representation of classification rules

    Liu, H., Gegov, A. & Cocea, M., 17 Sept 2015, Rule Based Systems for Big Data: A Machine Learning Approach. 1st ed. Springer, p. 51-62 12 p. (Studies in Big Data; vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Simplification of classification rules

    Liu, H., Gegov, A. & Cocea, M., 17 Sept 2015, Rule Based Systems for Big Data: A Machine Learning Approach. 1st ed. Springer, p. 43-50 8 p. (Studies in Big Data; vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Theoretical preliminaries

    Liu, H., Gegov, A. & Cocea, M., 17 Sept 2015, Rule Based Systems for Big Data: A Machine Learning Approach. 1st ed. Springer, p. 11-27 17 p. (Studies in Big Data; vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Towards gathering initial requirements of developing a mobile service to support informal learning at cultural heritage sites

    Alkhafaji, A., Fallahkhair, S. & Cocea, M., 24 Oct 2015, International Conference on Cognition and Exploratory Learning in Digital Age 2015. Sampson, D. G., Spector, J. M., Ifenthaler, D. & Isaías, P. (eds.). IADIS Press, (CELDA ).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

    Open Access
  • 2014

    Learning sentiment from students’ feedback for real-time interventions in classrooms

    Altrabsheh, N., Cocea, M. & Fallahkhair, S., 2014, Adaptive and intelligent systems: Third International Conference, ICAIS 2014, Bournemouth, UK, September 8-10, 2014. proceedings. Bouchachia, A. (ed.). Heidleberg: Springer, p. 40-49 (Lecture Notes in Computer Science ; vol. 8779).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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  • 2013

    Modeling and studying gaming the system with educational data mining

    Baker, R. S. J. D., Corbett, A. T., Roll, I., Koedinger, K. R., Aleven, V., Cocea, M., Hershkovitz, A., Caravalho, A. M. J. B. D., Mitrovic, A. & Mathews, M., 2013, International handbook of metacognition and learning technologies. Azevedo, R. & Aleven, V. (eds.). New York: Springer, p. 97-115 (Springer international handbooks of education; no. 28).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • 2012

    Learning task-related strategies from user data through clustering

    Cocea, M. & Magoulas, G., 2012, IEEE 12th International Conference on Advanced Learning Technologies. Los Alamitos, CA, USA: Institute of Electrical and Electronics Engineers Inc., Vol. 0. p. 400-404 5 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • 2011

    Case-based reasoning approach to adaptive modelling in exploratory learning

    Cocea, M., Gutierrez-Santos, S. & Magoulas, G., 30 Sept 2011, Innovations in Intelligent Machines – 2. Watanabe, T. & Jain, L. (eds.). 376 ed. Berlin: Springer, p. 167-184 18 p. (Studies in Computational Intelligence; no. 376).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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  • Context-dependent feedback prioritisation in exploratory learning revisited

    Cocea, M. & Magoulas, G., 2011, User modeling, adaption and personalization: 19th international conference, UMAP 2011, Girona, Spain, July 11-15, 2011. proceedings. Konstan, J., Conejo, R., Marzo, J. & Oliver, N. (eds.). 6787 ed. Berlin: Springer, Vol. 6787. p. 62-74 13 p. (Lecture Notes in Computer Science; no. 6787).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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  • Modelling affect by mining students' interactions within learning environments

    Mavrikis, M., D'Mello, S., Porayska-Pomsta, K., Cocea, M. & Graesser, A., 2011, Handbook of educational data mining. Romero, C., Ventura, S., Pechenizkiy, M. & Baker, R. S. J. D. (eds.). Boca Raton: CRC Press Inc, p. 231-244 (Data mining and knowledge discovery series).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • 2010

    A case-based reasoning approach to provide adaptive feedback in microworlds

    Gutierrez-Santos, M., Cocea, M. & Magoulas, G., 2010, Intelligent Tutoring Systems. Aleven, V., Kay, J. & Mostow, J. (eds.). 6095 ed. New York: Springer, p. 330 - 333 4 p. (Lecture Notes in Computer Science 2; no. 6095).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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  • Adaptive modelling of users' strategies in exploratory learning using case-based reasoning

    Cocea, M., Gutierrez-Santos, S. & Magoulas, G., 2010, Knowledge-based and intelligent information and engineering systems: 14th international conference, KES 2010, Cardiff, UK, September 8-10, 2010, proceedings, part II. Setchi, R., Jordanov, I., Howlett, R. & Jain, L. (eds.). 6277 ed. Berlin, Heidelberg: Springer, p. 124-134 11 p. (Lecture notes in computer science; no. 6277).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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  • Group formation for collaboration in exploratory learning using group technology techniques

    Cocea, M. & Magoulas, G., 2010, Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II. Setchi, R. & Jordanov, I. (eds.). Berlin, Heidelberg: Springer, p. 103-113 11 p. (KES'10).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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  • Identifying user strategies in exploratory learning with evolving task modelling

    Cocea, M. & Magoulas, G., Jul 2010, 2010 5th IEEE International Conference on Intelligent Systems (IS 2010): Proceedings of a meeting held 7-9 July 2010, London, United Kingdom. Piscataway: Institute of Electrical and Electronics Engineers Inc., p. 13 -18 6 p.

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  • Modeling affect by mining students’ interactions within learning environments

    Mavrikis, M., D’Mello, S., Porayska-Pomsta, K., Cocea, M. & Graesser, A., 26 Oct 2010, Handbook of Educational Data Mining. Romero, C., Ventura, S., Pechenizkiy, M. & Baker, R. (eds.). 1st ed. CRC Press Inc, p. 231-244 14 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

    Open Access
  • Validation issues in educational data mining: the case of HTML-Tutor and iHelp

    Cocea, M. & Weibelzahl, S., 25 Oct 2010, Handbook of educational data mining. Romero, C., Ventura, S., Pechenizkiy, M. & Baker, R. S. J. D. (eds.). Boca Raton: CRC Press Inc, p. 377-388 (Chapman & Hall / CRC Data Mining and Knowledge Discovery Series).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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  • 2009

    Context-dependent personalised feedback prioritisation in exploratory learning for mathematical generalisation

    Cocea, M. & Magoulas, G., 2009, Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization. Houben, G-J., McCalla, G. & Pianesi, F. (eds.). 5535 ed. Berlin, Heidelberg: Springer, p. 271-282 12 p. (Lecture Notes in Computer Science; no. 5535).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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  • Enhancing modelling of users' strategies in exploratory learning through case-base maintenance

    Cocea, M., Gutierrez-Santos, S. & Magoulas, G., Dec 2009, Proceedings of 14th UK Workshop on Case-Based Reasoning (UKCBR 2009). BCS, p. 2-13 12 p.

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  • Identifying strategies in users' exploratory learning behaviour for mathematical generalisation

    Cocea, M. & Magoulas, G., 2009, Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling. Dimitrova, V., Mizoguchi, R., Du Boulay, B. & Graesser, A. (eds.). Amsterdam: IOS Press, p. 626-628 3 p. (Frontiers in Artificial Intelligence and Applications).

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  • Task-oriented modeling of learner behaviour in exploratory learning for mathematical generalisation

    Cocea, M. & Magoulas, G. D., 2009, The 2nd international workshop on intelligent support for exploratory environments (ISEE'09), in conjunction with the 14th international conference on artificial intelligence in education (AIED 2009). Mavrikis, M., Gutierrez, S. & Mulholland, P. (eds.). London: Teaching Enhanced Learning, p. 16-24

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  • The impact of off-task and gaming behaviors on learning: immediate or aggregate?

    Cocea, M., Hershkovitz, A. & Baker, R. S. J. D., 2009, Proceedings of the 2009 Conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling. Dimitrova, V., Mizoguchi, R., Du Boulay, B. & Graesser, A. (eds.). Amsterdam: IOS Press, p. 507-514 (Frontiers in Artificial Intelligence and Applications).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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  • 2008

    A modelling framework for constructivist learning in exploratory learning environments

    Cocea, M., Jun 2008, Young Researchers Track Proceedings of the 9th International Conference on Intelligent Tutoring Systems, ITS 2008. Gouardères, G. & Vicari, R. M. (eds.). University of Quebec, p. 157-166

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Combining intelligent methods for learner modelling in exploratory learning environments

    Cocea, M. & Magoulas, G., 21 Jul 2008, Proceedings of the 1st International Workshop on Combinations of Intelligent Methods and Applications (CIMA 2008), in conjunction with the 18th European Conference on Artificial Intelligence (ECAI-08). Hatzilygeroudis, I., Koutsojannis, C. & Palade, V. (eds.). 375 ed. CEUR Workshop Proceedings, p. 13-18 6 p. (CEUR-WS; no. 375).

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  • Learner modelling in exploratory learning for mathematical generalisation

    Cocea, M., 2008, Adaptive hypermedia and adaptive web-based systems: 5th international conference, AH 2008, Hannover, Germany, July 29 - August 1, 2008, proceeding. Njedl, W., Kay, J., Pu, P. & Herder, E. (eds.). 5149 ed. Berlin: Springer, Vol. 5149. p. 394-399 6 p. (Lecture notes in computer science; no. 5149).

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  • 2007

    Cross-System validation of engagement prediction from log files

    Cocea, M. & Weibelzahl, S., 2007, Creating new learning experiences on a global scale: second European conference on technology enhanced learning, EC-TEL 2007, Crete, Greece, September 17-20, 2007, proceedings. Duval, E., Klamma, R. & Wolpers, M. (eds.). 4753 ed. Springer, p. 14-25 12 p. (Lecture notes in computer science; no. 4753).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  • Eliciting motivation knowledge from log files towards motivation diagnosis for adaptive systems

    Cocea, M. & Weibelzahl, S., 2007, User Modeling 2007: 11th International Conference, UM 2007, Corfu, Greece, June 25-29, 2007, Proceedings. Conati, C., McCoy, K. & Paliouras, G. (eds.). 4511 ed. Springer, p. 197-206 10 p. (Lecture notes in computer science; no. 4511).

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  • Learning engagement: what actions of learners could best predict it?

    Cocea, M., 2007, Artificial intelligence in education: building technology rich learning contexts that work. Luckin, R., Koedinger, K. & Greer, J. (eds.). 158 ed. Washington: IOS Press, p. 683-684 2 p. (Frontiers in artificial intelligence and applications; no. 158).

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  • 2006

    Assessment of motivation in online learning environments

    Cocea, M., 2006, Adaptive Hypermedia and Adaptive Web-Based Systems, 4th International Conference, AH 2006, Dublin, Ireland, June 21-23, 2006, Proceedings. Wade, V., Ashman, H. & Smyth, B. (eds.). 4018 ed. Berlin: Springer, p. 414-418 5 p. (Lecture notes in computer science; no. 4018).

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  • Can log files analysis estimate learners' level of motivation?

    Cocea, M. & Weibelzahl, S., 2006, LWA 2006: Lernen - Wissensentdeckung - Adaptivitat, 14th Workshop on Adaptivity and User Modeling in Interactive Systems (ABIS 2006). Hildesheim: University of Hildesheim, Institute of Computer Science, p. 32-35 (Hildesheimer Informatik-Berichte; no. 1/2006).

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  • Extendibility of educational systems to include a learner-adaptive motivational module

    Cocea, M., 2006, The 12th NETTIES (Networking Entities) International Conference: The Future of E:Advanced Educational Technologies for a Future e-Europe. Vasile, R., Kimari, R. & Andone, D. (eds.). Ed. Orizonturi Universitare, p. 195-198 4 p.

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  • Motivation: included or excluded from E-learning

    Cocea, M. & Weibelzahl, S., 2006, Cognition and exploratory learning in digital age, CELDA 2006 proceedings. Kinshuk, K., Sampson, D., Spector, J. & Isaias, P. (eds.). IADIS Press, p. 435-437 3 p.

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