2014 |
| 7. | Kawa Nazemi Adaptive Semantics Visualization PhD Thesis Technische Universität Darmstadt, 2014, (Reprint by Eugraphics Association (EG)). @phdthesis{Nazemi2014f,
title = {Adaptive Semantics Visualization},
author = {Kawa Nazemi},
url = {https://diglib.eg.org/handle/10.2312/12076, EG Lib
https://diglib.eg.org/bitstream/handle/10.2312/12076/nazemi.pdf, full text},
doi = {10.2312/12076},
year = {2014},
date = {2014-11-27},
school = {Technische Universität Darmstadt},
abstract = {Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users' behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field.
In this thesis, we introduce a novel model for adaptive visualization. In contrast to existing approaches, we have focused our investigation on the potentials of information visualization for adaptation. Our reference model for visual adaptation not only considers the entire transformation, from data to visual representation, but also enhances it to meet the requirements for visual adaptation. Our model adapts different visual layers that were identified based on various models and studies on human visual perception and information processing. In its adaptation process, our conceptual model considers the impact of both data and user on visualization adaptation. We investigate different approaches and models and their effects on system adaptation to gather implicit information about users and their behavior. These are than transformed and applied to affect the visual representation and model human interaction behavior with visualizations and data to achieve a more appropriate visual adaptation. Our enhanced user model further makes use of the semantic hierarchy to enable a domain-independent adaptation.
To face the problem of a system that requires to be trained by experts, we introduce the canonical user model that models the average usage behavior with the visualization environment. Our approach learns from the behavior of the average user to adapt the different visual layers and transformation steps. This approach is further enhanced with similarity and deviation analysis for individual users to determine similar behavior on an individual level and identify differing behavior from the canonical model. Users with similar behavior get similar visualization and data recommendations, while behavioral anomalies lead to a lower level of adaptation. Our model includes a set of various visual layouts that can be used to compose a multi-visualization interface, a sort of "visualization cockpit". This model facilitates various visual layouts to provide different perspectives and enhance the ability to solve difficult and exploratory search challenges. Data from different data-sources can be visualized and compared in a visual manner. These different visual perspectives on data can be chosen by users or can be automatically selected by the system.
This thesis further introduces the implementation of our model that includes additional approaches for an efficient adaptation of visualizations as proof of feasibility. We further conduct a comprehensive user study that aims to prove the benefits of our model and underscore limitations for future work. The user study with overall 53 participants focuses with its four conditions on our enhanced reference model to evaluate the adaptation effects of the different visual layers.},
note = {Reprint by Eugraphics Association (EG)},
keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Computer Based Learning, Data Analytics, E-Learning, Exploratory learning, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, Ontology visualization, personalization, Policy modeling, reference model, Semantic data modeling, Semantic visualization, Semantic web, Semantics visualization, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics},
pubstate = {published},
tppubtype = {phdthesis}
}
Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users' behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field.
In this thesis, we introduce a novel model for adaptive visualization. In contrast to existing approaches, we have focused our investigation on the potentials of information visualization for adaptation. Our reference model for visual adaptation not only considers the entire transformation, from data to visual representation, but also enhances it to meet the requirements for visual adaptation. Our model adapts different visual layers that were identified based on various models and studies on human visual perception and information processing. In its adaptation process, our conceptual model considers the impact of both data and user on visualization adaptation. We investigate different approaches and models and their effects on system adaptation to gather implicit information about users and their behavior. These are than transformed and applied to affect the visual representation and model human interaction behavior with visualizations and data to achieve a more appropriate visual adaptation. Our enhanced user model further makes use of the semantic hierarchy to enable a domain-independent adaptation.
To face the problem of a system that requires to be trained by experts, we introduce the canonical user model that models the average usage behavior with the visualization environment. Our approach learns from the behavior of the average user to adapt the different visual layers and transformation steps. This approach is further enhanced with similarity and deviation analysis for individual users to determine similar behavior on an individual level and identify differing behavior from the canonical model. Users with similar behavior get similar visualization and data recommendations, while behavioral anomalies lead to a lower level of adaptation. Our model includes a set of various visual layouts that can be used to compose a multi-visualization interface, a sort of "visualization cockpit". This model facilitates various visual layouts to provide different perspectives and enhance the ability to solve difficult and exploratory search challenges. Data from different data-sources can be visualized and compared in a visual manner. These different visual perspectives on data can be chosen by users or can be automatically selected by the system.
This thesis further introduces the implementation of our model that includes additional approaches for an efficient adaptation of visualizations as proof of feasibility. We further conduct a comprehensive user study that aims to prove the benefits of our model and underscore limitations for future work. The user study with overall 53 participants focuses with its four conditions on our enhanced reference model to evaluate the adaptation effects of the different visual layers. |
| 6. | Kawa Nazemi Adaptive Semantics Visualization PhD Thesis Technische Universität Darmstadt, 2014, (Department of Computer Science. Supervised by Dieter W. Fellner.). @phdthesis{Nazemi2014g,
title = {Adaptive Semantics Visualization},
author = {Kawa Nazemi},
url = {http://tuprints.ulb.tu-darmstadt.de/id/eprint/4319, TU Darmstadt Prints
http://tuprints.ulb.tu-darmstadt.de/4319/1/Nazemi_Diss.pdf, full text},
year = {2014},
date = {2014-11-23},
address = {Darmstadt, Germany},
school = {Technische Universität Darmstadt},
abstract = {Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users’ behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field.
In this thesis, we introduce a novel model for adaptive visualization. In contrast to existing approaches, we have focused our investigation on the potentials of information visualization for adaptation. Our reference model for visual adaptation not only considers the entire transformation, from data to visual representation, but also enhances it to meet the requirements for visual adaptation. Our model adapts different visual layers that were identified based on various models and studies on human visual perception and information processing. In its adaptation process, our conceptual model considers the impact of both data and user on visualization adaptation. We investigate different approaches and models and their effects on system adaptation to gather implicit information about users and their behavior. These are than transformed and applied to affect the visual representation and model human interaction behavior with visualizations and data to achieve a more appropriate visual adaptation. Our enhanced user model further makes use of the semantic hierarchy to enable a domain-independent adaptation.
To face the problem of a system that requires to be trained by experts, we introduce the canonical user model that models the average usage behavior with the visualization environment. Our approach learns from the behavior of the average user to adapt the different visual layers and transformation steps. This approach is further enhanced with similarity and deviation analysis for individual users to determine similar behavior on an individual level and identify differing behavior from the canonical model. Users with similar behavior get similar visualization and data recommendations, while behavioral anomalies lead to a lower level of adaptation. Our model includes a set of various visual layouts that can be used to compose a multi-visualization interface, a sort of "‘visualization cockpit"’. This model facilitates various visual layouts to provide different perspectives and enhance the ability to solve difficult and exploratory search challenges. Data from different data-sources can be visualized and compared in a visual manner. These different visual perspectives on data can be chosen by users or can be automatically selected by the system.
This thesis further introduces the implementation of our model that includes additional approaches for an efficient adaptation of visualizations as proof of feasibility. We further conduct a comprehensive user study that aims to prove the benefits of our model and underscore limitations for future work. The user study with overall 53 participants focuses with its four conditions on our enhanced reference model to evaluate the adaptation effects of the different visual layers.},
note = {Department of Computer Science. Supervised by Dieter W. Fellner.},
keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Computer Based Learning, Data Analytics, eGovernance, Exploratory learning, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction Design, Ontology visualization, personalization, Policy modeling, Semantic data modeling, Semantic visualization, Semantic web, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics},
pubstate = {published},
tppubtype = {phdthesis}
}
Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users’ behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field.
In this thesis, we introduce a novel model for adaptive visualization. In contrast to existing approaches, we have focused our investigation on the potentials of information visualization for adaptation. Our reference model for visual adaptation not only considers the entire transformation, from data to visual representation, but also enhances it to meet the requirements for visual adaptation. Our model adapts different visual layers that were identified based on various models and studies on human visual perception and information processing. In its adaptation process, our conceptual model considers the impact of both data and user on visualization adaptation. We investigate different approaches and models and their effects on system adaptation to gather implicit information about users and their behavior. These are than transformed and applied to affect the visual representation and model human interaction behavior with visualizations and data to achieve a more appropriate visual adaptation. Our enhanced user model further makes use of the semantic hierarchy to enable a domain-independent adaptation.
To face the problem of a system that requires to be trained by experts, we introduce the canonical user model that models the average usage behavior with the visualization environment. Our approach learns from the behavior of the average user to adapt the different visual layers and transformation steps. This approach is further enhanced with similarity and deviation analysis for individual users to determine similar behavior on an individual level and identify differing behavior from the canonical model. Users with similar behavior get similar visualization and data recommendations, while behavioral anomalies lead to a lower level of adaptation. Our model includes a set of various visual layouts that can be used to compose a multi-visualization interface, a sort of "‘visualization cockpit"’. This model facilitates various visual layouts to provide different perspectives and enhance the ability to solve difficult and exploratory search challenges. Data from different data-sources can be visualized and compared in a visual manner. These different visual perspectives on data can be chosen by users or can be automatically selected by the system.
This thesis further introduces the implementation of our model that includes additional approaches for an efficient adaptation of visualizations as proof of feasibility. We further conduct a comprehensive user study that aims to prove the benefits of our model and underscore limitations for future work. The user study with overall 53 participants focuses with its four conditions on our enhanced reference model to evaluate the adaptation effects of the different visual layers. |
2011 |
| 5. | Dirk Burkhardt; Matthias Breyer; Christian Stab; Kawa Nazemi Facilitate Access to E-Knowledge for Adult People in Rural Areas Inproceedings In: Candel I Torres; Gómez L Chova; López A Martínez (Ed.): Proceedings of the 4th International Conference of Education, Research and Innovation (ICERI2011)., pp. 2050-2057, International Association of Technology, Education and Development, Madrid, Spain, 2011, ISBN: 978-84-615-3324-4. @inproceedings{Burkhardt2011b,
title = {Facilitate Access to E-Knowledge for Adult People in Rural Areas},
author = {Dirk Burkhardt and Matthias Breyer and Christian Stab and Kawa Nazemi},
editor = {Candel I Torres and Gómez L Chova and López A Martínez},
url = {https://library.iated.org/view/BURKHARDT2011FAC, IATED Digital Library},
doi = {10.5281/zenodo.3455891},
isbn = {978-84-615-3324-4},
year = {2011},
date = {2011-11-01},
booktitle = {Proceedings of the 4th International Conference of Education, Research and Innovation (ICERI2011).},
pages = {2050-2057},
publisher = {International Association of Technology, Education and Development},
address = {Madrid, Spain},
series = {4th International Conference of Education, Research and Innovation},
abstract = {The today society especially in the western world is stamped by a lifelong learning. This matter results because of an increasing technology development primary in Information Communication Technologies (ICT). These technology developments have their reasons in creating new effective and efficient systems that allows a higher productivity or quality and decreases the production cost, which is necessary for a stable and healthy company. But the goal of these new technologies is also to provide more possibilities for the “normal” users, so that they for instance can easily and cheap get updated about the status of their family members or friends over the internet. So ICT allows a wide range of possibilities, also for providing education with these technologies. So in this connection ICT can contribute to achieving universal education worldwide, through transfer of education and training, and offering improved conditions for lifelong learning, encompassing adults that are not participating to the formal education process, and improving professional skills (UNESCO, 2009). And skills are today the main factor for wealth in a society.
A modern established method to provide a flexible learning, especially for lifelong learning for adults, is learning over the internet. By this kind of eLearning it does not matter where a specific user or student lives or tries to learn, he only needs access to the internet and has with it access to a huge amount of information and eLearning materials. But in fact for this way of learning the user needs experiences in dealing with the internet and also with the learning platforms. Because of that fact often only younger students up to the age of ca. 30 years are able use the existing eLearning platforms in an efficient way. This young target group stands in opposition to the demographic effect that the average age of most of the European residents increases constantly. So it becomes to a national and European challenge to support also the middle-aged adults for holding them up-to-date educated. But to provide an advanced education for these adult people is difficult, because it can be very time consuming and expensive, if they are trained on the traditional way with courses and tutors or trainers. So another approach is useful, next to the traditional advanced education.
In our paper we describe an approach to provide a facilitated access to eKnowledge and so to virtual learning. With the described approach we address especially older adults between the age of 30 and 40 to support them in advanced learning. This allows bringing them up-to-date, so that they can achieve a similar education level than younger once which e.g. coming from the university. For reducing the access barrier many aspects, next to the general strategy, have to be to regarded, e.g. usability and also user experience aspects to avoid that middle and older adults get overstrained, which results often that they dislike the entire online learning strategy. So these technical features need to be hidden or so far reduced and abstracted that also these kinds of adults will understand the usefulness. In this paper we also take care for such aspects and presenting a concept and implementation of an eLearning portal that is primary designed for supporting the needs and behaviours of middle-aged adults. The main contribution of this paper is the abstraction and reduction of learning functionalities, implemented in a well-known learning environment.},
keywords = {Adult Learning, E-Learning, E-Learning environments, Exploratory learning, Human Factors, Human-centered user interfaces},
pubstate = {published},
tppubtype = {inproceedings}
}
The today society especially in the western world is stamped by a lifelong learning. This matter results because of an increasing technology development primary in Information Communication Technologies (ICT). These technology developments have their reasons in creating new effective and efficient systems that allows a higher productivity or quality and decreases the production cost, which is necessary for a stable and healthy company. But the goal of these new technologies is also to provide more possibilities for the “normal” users, so that they for instance can easily and cheap get updated about the status of their family members or friends over the internet. So ICT allows a wide range of possibilities, also for providing education with these technologies. So in this connection ICT can contribute to achieving universal education worldwide, through transfer of education and training, and offering improved conditions for lifelong learning, encompassing adults that are not participating to the formal education process, and improving professional skills (UNESCO, 2009). And skills are today the main factor for wealth in a society.
A modern established method to provide a flexible learning, especially for lifelong learning for adults, is learning over the internet. By this kind of eLearning it does not matter where a specific user or student lives or tries to learn, he only needs access to the internet and has with it access to a huge amount of information and eLearning materials. But in fact for this way of learning the user needs experiences in dealing with the internet and also with the learning platforms. Because of that fact often only younger students up to the age of ca. 30 years are able use the existing eLearning platforms in an efficient way. This young target group stands in opposition to the demographic effect that the average age of most of the European residents increases constantly. So it becomes to a national and European challenge to support also the middle-aged adults for holding them up-to-date educated. But to provide an advanced education for these adult people is difficult, because it can be very time consuming and expensive, if they are trained on the traditional way with courses and tutors or trainers. So another approach is useful, next to the traditional advanced education.
In our paper we describe an approach to provide a facilitated access to eKnowledge and so to virtual learning. With the described approach we address especially older adults between the age of 30 and 40 to support them in advanced learning. This allows bringing them up-to-date, so that they can achieve a similar education level than younger once which e.g. coming from the university. For reducing the access barrier many aspects, next to the general strategy, have to be to regarded, e.g. usability and also user experience aspects to avoid that middle and older adults get overstrained, which results often that they dislike the entire online learning strategy. So these technical features need to be hidden or so far reduced and abstracted that also these kinds of adults will understand the usefulness. In this paper we also take care for such aspects and presenting a concept and implementation of an eLearning portal that is primary designed for supporting the needs and behaviours of middle-aged adults. The main contribution of this paper is the abstraction and reduction of learning functionalities, implemented in a well-known learning environment. |
| 4. | Kawa Nazemi; Matthias Breyer; Christian Stab; Dirk Burkhardt; Dieter W. Fellner Intelligent Exploration System - An Approach for User-Centered Exploratory Learning Inproceedings In: Argiris Tzikopoulos; Anna Zoakou (Ed.): Proceeding of the Workshop of the EDEN Open Classroom 2011 Conference. RURALeNTER - Lifelong Learning in Rural and Remote Areas, pp. 71 - 83, EPINOIA S.A., Pallini - Athens, Greece, 2011, ISBN: 978-960-473-323-1, (reprint). @inproceedings{Nazemi2011e,
title = {Intelligent Exploration System - An Approach for User-Centered Exploratory Learning},
author = {Kawa Nazemi and Matthias Breyer and Christian Stab and Dirk Burkhardt and Dieter W. Fellner},
editor = {Argiris Tzikopoulos and Anna Zoakou},
url = {http://www.ea.gr/ep/ruenter/news/RURALeNTER_WP6_%20ProceedingsofEuropeanWorkshop%20_V1.0_30October2011_EA.pdf, full text},
doi = {10.5281/zenodo.3455885},
isbn = {978-960-473-323-1},
year = {2011},
date = {2011-01-01},
booktitle = {Proceeding of the Workshop of the EDEN Open Classroom 2011 Conference. RURALeNTER - Lifelong Learning in Rural and Remote Areas},
pages = {71 - 83},
publisher = {EPINOIA S.A.},
address = {Pallini - Athens, Greece},
abstract = {The following paper describes the conceptual design of an Intelligent Exploration System (IES) that offers a user-adapted graphical environment of web-based knowledge repositories, to support and optimize the explorative learning. The paper starts with a short definition of learning by exploring and introduces the Intelligent Tutoring System and Semantic Technologies for developing such an Intelligent Exploration System. The IES itself will be described with a short overview of existing learner or user analysis methods, visualization techniques for exploring knowledge with semantics technology and the explanation of the characteristics of adaptation to offer a more efficient learning environment.},
note = {reprint},
keywords = {E-Learning, Exploratory learning, Human Factors, Interaction Design, Semantic visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
The following paper describes the conceptual design of an Intelligent Exploration System (IES) that offers a user-adapted graphical environment of web-based knowledge repositories, to support and optimize the explorative learning. The paper starts with a short definition of learning by exploring and introduces the Intelligent Tutoring System and Semantic Technologies for developing such an Intelligent Exploration System. The IES itself will be described with a short overview of existing learner or user analysis methods, visualization techniques for exploring knowledge with semantics technology and the explanation of the characteristics of adaptation to offer a more efficient learning environment. |
2010 |
| 3. | Kawa Nazemi; Matthias Breyer; Dirk Burkhardt; Dieter W. Fellner Visualization Cockpit: Orchestration of Multiple Visualizations for Knowledge-Exploration Journal Article In: International Journal of Advanced Corporate Learning, vol. 3, no. 4, pp. 26-34, 2010, ISSN: 1867-5565. @article{C35-P-21710,
title = {Visualization Cockpit: Orchestration of Multiple Visualizations for Knowledge-Exploration},
author = {Kawa Nazemi and Matthias Breyer and Dirk Burkhardt and Dieter W. Fellner},
url = {http://online-journals.org/index.php/i-jac/article/view/1473, iJAC Journal
http://online-journals.org/index.php/i-jac/article/download/1473/1560.pdf, Full Paper},
issn = {1867-5565},
year = {2010},
date = {2010-01-01},
journal = {International Journal of Advanced Corporate Learning},
volume = {3},
number = {4},
pages = {26-34},
abstract = {Semantic-Web technologies and ontology-based information processing systems are established techniques, in more than only research areas and institutions. Different worldwide projects and enterprise companies identified already the added value of semantic technologies, so they work on different sub-topics for gathering and conveying knowledge. As the process of gathering and structuring semantic information plays a key role in the most developed applications, the process of transferring and adopting knowledge to and by humans is neglected, although the complex structure of knowledge-design opens many research-questions. The customization of the presentation itself and the interaction techniques with these presentation artifacts is a key question for gainful and effective work with semantic information. The following paper describes a new approach for visualizing semantic information as a composition of different adaptable ontology-visualization techniques. We start with a categorized description of existing ontology visualization techniques and show potential gaps.},
keywords = {Computer Based Learning, E-Learning, Exploratory learning, Human-computer interaction (HCI), Information visualization, Visual analytics},
pubstate = {published},
tppubtype = {article}
}
Semantic-Web technologies and ontology-based information processing systems are established techniques, in more than only research areas and institutions. Different worldwide projects and enterprise companies identified already the added value of semantic technologies, so they work on different sub-topics for gathering and conveying knowledge. As the process of gathering and structuring semantic information plays a key role in the most developed applications, the process of transferring and adopting knowledge to and by humans is neglected, although the complex structure of knowledge-design opens many research-questions. The customization of the presentation itself and the interaction techniques with these presentation artifacts is a key question for gainful and effective work with semantic information. The following paper describes a new approach for visualizing semantic information as a composition of different adaptable ontology-visualization techniques. We start with a categorized description of existing ontology visualization techniques and show potential gaps. |
| 2. | Kawa Nazemi; Dirk Burkhardt; Matthias Breyer; Christian Stab; Dieter W. Fellner Semantic Visualization Cockpit: Adaptable Composition of Semantics-Visualization Techniques for Knowledge-Exploration Conference International Conference on Interactive Collaborative Learning (ICL), Kassel University Press, 2010, 2010. @conference{C35-P-21605,
title = {Semantic Visualization Cockpit: Adaptable Composition of Semantics-Visualization Techniques for Knowledge-Exploration},
author = {Kawa Nazemi and Dirk Burkhardt and Matthias Breyer and Christian Stab and Dieter W. Fellner},
url = {https://pdfs.semanticscholar.org/46d4/1ca0256a1024fd32f5f37280a359f60ae2f1.pdf, Full text
https://www.semanticscholar.org/paper/Semantic-Visualization-Cockpit%3A-Adaptable-Composit-Nazemi-Burkhardt/46d41ca0256a1024fd32f5f37280a359f60ae2f1, Semantic Scholars},
year = {2010},
date = {2010-01-01},
booktitle = {International Conference on Interactive Collaborative Learning (ICL)},
pages = {163-173},
publisher = {Kassel University Press, 2010},
abstract = {Semantic-Web and ontology-based information processing systems are established technologies and techniques, in more than only research areas and institutions. Different worldwide projects and enterprise companies identified already the added value of semantic technologies and work on different sub-topics for gathering and conveying knowledge. As the process of gathering and structuring semantic information plays a key role in the most developed applications, the process of transferring and adopting knowledge to and by humans is neglected, although the complex structure of knowledge-design opens many research-questions. The following paper describes a new approach for visualizing semantic information as a composition of different adaptable ontology-visualization techniques. We start with a categorized description of existing ontology visualization techniques and show potential gaps. After that the new approach will be described and its added value to existing systems. A case
study within the greatest German program for semantic information processing will show the usage of the system in real scenarios.},
keywords = {Exploratory learning, Intelligent user interfaces, Semantic visualization, Semantic web},
pubstate = {published},
tppubtype = {conference}
}
Semantic-Web and ontology-based information processing systems are established technologies and techniques, in more than only research areas and institutions. Different worldwide projects and enterprise companies identified already the added value of semantic technologies and work on different sub-topics for gathering and conveying knowledge. As the process of gathering and structuring semantic information plays a key role in the most developed applications, the process of transferring and adopting knowledge to and by humans is neglected, although the complex structure of knowledge-design opens many research-questions. The following paper describes a new approach for visualizing semantic information as a composition of different adaptable ontology-visualization techniques. We start with a categorized description of existing ontology visualization techniques and show potential gaps. After that the new approach will be described and its added value to existing systems. A case
study within the greatest German program for semantic information processing will show the usage of the system in real scenarios. |
| 1. | Kawa Nazemi; Matthias Breyer; Christian Stab; Dirk Burkhardt; Dieter W. Fellner Intelligent Exploration System - an Approach for User-Centered Exploratory Learning Conference 2nd International Conference on Education and New Learning Technologies, 2010, ISBN: 978-84-613-9386-2. @conference{C35-P-21397,
title = {Intelligent Exploration System - an Approach for User-Centered Exploratory Learning},
author = {Kawa Nazemi and Matthias Breyer and Christian Stab and Dirk Burkhardt and Dieter W. Fellner},
editor = {Education International Association of Technology and Development},
url = {https://library.iated.org/view/NAZEMI2010INT, direct link to publisher},
doi = {10.5281/zenodo.3457233},
isbn = {978-84-613-9386-2},
year = {2010},
date = {2010-01-01},
booktitle = {2nd International Conference on Education and New Learning Technologies},
pages = {6476-6484},
abstract = {The following paper describes the conceptual design of an Intelligent Exploration System (IES) that offers a user-adapted graphical environment of web-based knowledge repositories, to support and optimize the explorative learning. The paper starts with a short definition of learning by exploring and introduces the Intelligent Tutoring System and Semantic Technologies for developing such an Intelligent Exploration System. The IES itself will be described with a short overview of existing learner or user analysis methods, visualization techniques for exploring knowledge with semantics technology and the explanation of the characteristics of adaptation to offer a more efficient learning environment.},
keywords = {Exploration, Exploratory learning, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Intelligent tutoring systems, Knowledge discovery},
pubstate = {published},
tppubtype = {conference}
}
The following paper describes the conceptual design of an Intelligent Exploration System (IES) that offers a user-adapted graphical environment of web-based knowledge repositories, to support and optimize the explorative learning. The paper starts with a short definition of learning by exploring and introduces the Intelligent Tutoring System and Semantic Technologies for developing such an Intelligent Exploration System. The IES itself will be described with a short overview of existing learner or user analysis methods, visualization techniques for exploring knowledge with semantics technology and the explanation of the characteristics of adaptation to offer a more efficient learning environment. |
