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bibtex [2019/03/22 13:53]
anton
bibtex [2019/10/21 07:34] (current)
anton
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 +@article{SYCHEV2020,​
 +title = "​Automatic grading and hinting in open-ended text questions",​
 +journal = "​Cognitive Systems Research",​
 +volume = "​59",​
 +pages = "264 - 272",
 +year = "​2020",​
 +issn = "​1389-0417",​
 +doi = "​https://​doi.org/​10.1016/​j.cogsys.2019.09.025",​
 +url = "​http://​www.sciencedirect.com/​science/​article/​pii/​S1389041719304978",​
 +author = "Oleg Sychev and Anton Anikin and Artem Prokudin",​
 +thanks = {rfbr-18-07-00032}
 +}
 +
 +@InProceedings{10.1007/​978-3-030-29750-3_33,​
 +doi="​10.1007/​978-3-030-29750-3_33",​
 +author="​Kultsova,​ Marina
 +and Potseluico, Anastasiya
 +and Dvoryankin, Alexander",​
 +editor="​Kravets,​ Alla G.
 +and Groumpos, Peter P.
 +and Shcherbakov,​ Maxim
 +and Kultsova, Marina",​
 +title="​Ontology Based Personalization of Mobile Interfaces for People with Special Needs",​
 +booktitle="​Creativity in Intelligent Technologies and Data Science",​
 +year="​2019",​
 +publisher="​Springer International Publishing",​
 +address="​Cham",​
 +pages="​422--433",​
 +abstract="​The paper is devoted to a problem of interface personification for people with special needs on the base of information about their behavior during interaction with mobile applications. This work evolves our previous researches on the development of adaptive user interfaces. Much attention in this paper was given to the investigation of existing approaches to collecting and analyzing the information about user behavior and interaction context data as well as interface adaptation recommendations. The improved interface adaptation mechanism was developed and described based on the ontological representation of the interface patterns and knowledge about users and their interaction with a mobile application. The set of adaptation rules was developed and implemented in the ontology knowledge base. In the paper, we described the improved ontology model and some examples of ontological representation of interface patterns.",​
 +isbn="​978-3-030-29750-3",​
 +thanks = {rfbr-18-07-00032}
 +}
 +
 +
 +@InProceedings{10.1007/​978-3-030-29750-3_7,​
 +doi="​10.1007/​978-3-030-29750-3_7",​
 +author="​Litovkin,​ Dmitry
 +and Anikin, Anton
 +and Kultsova, Marina",​
 +editor="​Kravets,​ Alla G.
 +and Groumpos, Peter P.
 +and Shcherbakov,​ Maxim
 +and Kultsova, Marina",​
 +title="​Semantic Zooming Approach to Semantic Link Network Visualization",​
 +booktitle="​Creativity in Intelligent Technologies and Data Science",​
 +year="​2019",​
 +publisher="​Springer International Publishing",​
 +address="​Cham",​
 +pages="​81--95",​
 +abstract="​In the paper, we described a semantic zooming approach to the visualization of special kind structures - semantic link networks (SLN), represented as a visual graph. The proposed approach allows decreasing semantic noise in SLN overview and navigation and also simplifies the process of understanding the domain studied with SLN by means of semantic zooming. We proposed priori importance levels of SLN items and semantic zooming scale to visualize the SLN with different details level. We designed an interactive SLN visualization process including the following SLN transformations:​ filtering SLN items, context collapse and expansion for SLN item, and changing the details in the visualized object representation in the geometric SLN graph. The transformation algorithms were developed, and also examples of SNL semantic zooming were described in details in the paper.",​
 +isbn="​978-3-030-29750-3",​
 +thanks = {rfbr-18-07-00032,​ rfbr-18-47-340014}
 +}
 +
 +
 +@incollection{Anikin2019_2,​
 +  doi = {10.1007/​978-3-030-25719-4_4},​
 +  url = {https://​doi.org/​10.1007/​978-3-030-25719-4_4},​
 +  year = {2019},
 +  month = jul,
 +  publisher = {Springer International Publishing},​
 +  pages = {22--27},
 +  author = {Anton Anikin and Oleg Sychev},
 +  title = {Ontology-Based Modelling for Learning on Bloom'​s Taxonomy Comprehension Level},
 +  booktitle = {Advances in Intelligent Systems and Computing}
 +}
 +@incollection{Anikin2019_3,​
 +  doi = {10.1007/​978-3-030-25719-4_67},​
 +  url = {https://​doi.org/​10.1007/​978-3-030-25719-4_67},​
 +  year = {2019},
 +  month = jul,
 +  publisher = {Springer International Publishing},​
 +  pages = {521--526},
 +  author = {Oleg Sychev and Anton Anikin and Artem Prokudin},
 +  title = {Methods of Determining Errors in Open-Ended Text Questions},
 +  booktitle = {Advances in Intelligent Systems and Computing}
 +}
 @article{Anikin_2019_1,​ @article{Anikin_2019_1,​
  doi = {10.1088/​1757-899x/​483/​1/​012074},​  doi = {10.1088/​1757-899x/​483/​1/​012074},​