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  • Expression of Interest

    Marmara University

    Dr. Altınel is an instructor and researcher at Computer Engineering Department.  Her recent research focuses in text mining and social media analysis including sentiment analysis, natural language processing, word sense disambiguation and anomaly detection problem.

    She studied in 3 research projects (Positions: researcher for 1 project and PI for 2 projects) funded by TÜBİTAK (The Scientific and Technological Research Council of Turkey ) related to textual data mining applications and social media analysis. Her profile at Google Scholar is:


    Her some of the related publications are listed below:

    • (2021) Altınel, B., Ranking influencers of social networks by semantic kernels and sentiment information. Expert Systems with Applications, 171, 114599.

    • (2020) Groavac, J., Altınel, B., (2020, July). Sentiment Classification of Movie Reviews Using Machine Learning Approaches. In 2020 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA) (pp. 1-6). IEEE.

    • (2019) Yüksel, A., Türkmen, Y.A., Özgür, A., Altınel, B., Turkish Tweet Classification with Transformer Encoder. In 2019 IEEE International Conference Recent Advances In Natural Language Processing (RANLP) (pp. 1381-1388). IEEE.

    • (2019) Rezarta Islamaj Doğan, Sun Kim, Andrew Chatr-aryamontri, Chih-Hsuan Wei, Donald C Comeau, Rui Antunes, Sérgio Matos, Qingyu Chen, Aparna Elangovan, Nagesh C Panyam, Karin Verspoor, Hongfang Liu, Yanshan Wang, Zhuang Liu, Berna Altınel, Zehra Melce Hüsünbeyi, Arzucan Özgür, Aris Fergadis, Chen-Kai Wang, Hong-Jie Dai, Tung Tran, Ramakanth Kavuluru, Ling Luo, Albert Steppi, Jinfeng Zhang, Jinchan Qu, Zhiyong Lu; Overview of the BioCreative VI Precision Medicine Track: mining protein interactions and mutations for precision medicine, Database, Volume 2019, 1 January 2019, bay147,

    • (2019) Altınel, B., Ganiz, M.C., Şipal, B., Erkaya, E., Yücedağ, O.C., Doğan, M.A. “Word sense disambiguation using semantic kernels with class-based term values”, Turkish Journal of Electrical Engineering & Computer Sciences, 27(4), 3180-3194.

    • (2018) Altınel, B. & Ganiz, M. C.. Semantic text classification: A survey of past and recent advances. Information Processing & Management, 54(6), 1129-1153.

    • (2017) Altınel, B., Ganiz, M.C., Diri, B., “Instance Labelling in Semi-Supervised Learning using Meaning Values of Terms”.  Engineering Applications of Artificial Intelligence. (doi: 10.1016/j.engappai.2017.04.003)

    • (2017) Altınel, B., Hüsünbeyi, M. Z., Özgür, A., Text Classification using Ontology and Semantic Values of Terms for Mining Protein Interactions and Mutations. Medicine Track of the BioCreative VI 2017.

    • (2016) Altınel, B., Ganiz, M.C., “A new hybrid semi-supervised algorithm for text classification with class-based values of terms”. Knowledge-Based Systems, Special Issue: New Avenues in Knowledge Bases for Natural Language Processing. (doi:10.1016/j.knosys.2016.06.021)

    • (2015) Altınel, B., Diri, B., Ganiz, M.C., “A Novel Semantic Smoothing Kernel for Text Classification with Class-based Weighting”. Knowledge-Based Systems, Vol. 89, pp. 265-177.( doi:10.1016/j.knosys.2015.07.008)

    • (2015) Altınel, B., Ganiz, M.C., Diri, B.,  “A Corpus-Based Semantic Kernel for Text Classification by using Meaning Values of Terms” , Elsevier, Engineering Applications of Artificial Intelligence Volume 43, August 2015, Pages 54–66.( doi:10.1016/j.engappai.2015.03.015)

    • (2009) Cataltepe, Z. and Altınel, B., "Music Recommendation by Modeling User’s Preferred Perspectives of Content, Singer/Genre and Popularity" in "Collaborative and Social Information Retrieval and Access: Techniques for Improved User Modeling" edited by M. Chevalier, C. Julien and C. Soulé-Dupuy, IGI Global, pp. 203-221, ISBN: 978-1-60566-306-7.

    As the research group we decided to work together on CHIST-ERA project (OSNEM) with a Turkish partner who is the one of the leading social news platforms on Turkey and has very huge classified data. We would like to collaborate with interested international partners on CHIST-ERA project with our expertise on text mining and social network analysis.