| 1. |
- Andersson, Robin, et al.
(author)
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RoSy : A Rough Knowledge Base System
- 2005
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In: Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing,2005. - Berlin : Springer. ; , s. 48-
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Conference paper (peer-reviewed)
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| 2. |
- Andersson, Robin, et al.
(author)
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RoSy: A Rough Knowledge Base System
- 2005
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In: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783540286608 ; , s. 48-58
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Conference paper (peer-reviewed)abstract
- This paper presents a user-oriented view of RoSy, a Rough Knowledge Base System. The system tackles two problems not fully answered by previous research: the ability to define rough sets in terms of other rough sets and incorporation of domain or expert knowledge. We describe two main components of RoSy: knowledge base creation and query answering. The former allows the user to create a knowledge base of rough concepts and checks that the definitions do not cause what we will call a model failure. The latter gives the user a possibility to query rough concepts defined in the knowledge base. The features of RoSy are described using examples. The system is currently available on a web site for online interactions.
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| 3. |
- Dell-Acqua, Pierangelo, et al.
(author)
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User Preference Information in Query Answering
- 2002
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In: Flexible Query Answering Systems. - : Springer Berlin/Heidelberg. - 3540000747 - 9783540000747 - 9783540361091 ; , s. 163-173
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Book chapter (peer-reviewed)abstract
- This paper discusses the use of usage information to enhance cooperative behaviour from query answering systems. A user can pose a query to the system by providing (at query time) update and preference information. Updates allow us to model dynamically evolving worlds and preferences allow us to facilitate the. retrieval of information by targeting the answers of the system with respect to users' interests in a given context.
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| 4. |
- Maluszynski, Jan, 1941-, et al.
(author)
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A Four-Valued Logic for Rough Set-Like Approximate Reasoning
- 2007
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In: Transactions on Rough Sets VI. - Berlin, Heidelberg : Springer. - 3540711988 - 9783540711988 ; , s. 176-190
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Book chapter (peer-reviewed)abstract
- Annotation The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume VI of the Transactions on Rough Sets (TRS) commemorates the life and work of Zdzislaw Pawlak (1926-2006). His legacy is rich and varied. Prof. Pawlak's research contributions have had far-reaching implications inasmuch as his works are fundamental in establishing new perspectives for scientific research in a wide spectrum of fields. This volume of the TRS presents papers that reflect the profound influence of a number of research initiatives by Professor Pawlak. In particular, this volume introduces a number of new advances in the foundations and applications of artificial intelligence, engineering, logic, mathematics, and science. These advances have significant implications in a number of research areas such as the foundations of rough sets, approximate reasoning, bioinformatics, computational intelligence, cognitive science, data mining, information systems, intelligent systems, machine intelligence, and security.
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| 5. |
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| 6. |
- Maluszynski, Jan, 1941-, et al.
(author)
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Paraconsistent Logic Programs with Four-valued Rough Sets
- 2008
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In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Germany : Springer. - 9783540884231 - 9783540884255 ; , s. 41-51
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Conference paper (peer-reviewed)abstract
- This paper presents a language for defining four-valued rough sets and to reason about them. Our framework brings together two major fields: rough sets and paraconsistent logic programming. On the one hand it provides a paraconsistent approach, based on four-valued rough sets, for integrating knowledge from different sources and reasoning in the presence of inconsistencies. On the other hand, it also caters for a specific type of uncertainty that originates from the fact that an agent may perceive different objects of the universe as being indiscernible. This paper extends the ideas presented in [9]. Our language allows the user to define similarity relations and use the approximations induced by them in the definition of other four-valued sets. A positive aspect is that it allows users to tune the level of uncertainty or the source of uncertainty that best suits applications.
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| 7. |
- Maluszynski, Jan, 1941-, et al.
(author)
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Towards Rough Datalog : Embedding Rough Sets in Prolog
- 2004
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In: Rough-Neural Computing: Techniques for Computing with Words. - Berlin : Springer Verlag. - 9783540430599 ; , s. 297-332
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Book chapter (other academic/artistic)abstract
- Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g., in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, and genetic algorithms.It is well understood now in the soft computing community that hybrid approaches combining various paradigms provide very promising attempts to solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neurocomputing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.
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| 8. |
- Muthumanickam, Prithiviraj, et al.
(author)
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Comparison of Attention Behaviour Across User Sets through Automatic Identification of Common Areas of Interest
- 2019
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In: Hawaii International Conference on System Sciences 2020. - 9780998133133
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Conference paper (peer-reviewed)abstract
- Eye tracking is used to analyze and compare user behaviour within numerous domains, but long duration eye tracking experiments across multiple users generate millions of eye gaze samples, making the data analysis process complex. Usually the samples are labelled into Areas of Interest (AoI) or Objects of Interest (OoI), where the AoI approach aims to understand how a user monitors different regions of a scene while OoI identification uncovers distinct objects in the scene that attract user attention. Using scalable clustering and cluster merging techniques that require minimal user input, we label AoIs across multiple users in long duration eye tracking experiments. Using the common AoI labels then allows direct comparison of the users as well as the use of such methods as Hidden Markov Models and Sequence mining to uncover common and distinct behaviour between the users which, until now, has been prohibitively difficult to achieve.
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| 9. |
- Muthumanickam, Prithiviraj, et al.
(author)
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Identification of Temporally Varying Areas of Interest in Long-Duration Eye-Tracking Data Sets
- 2019
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In: IEEE Transactions on Visualization and Computer Graphics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1077-2626 .- 1941-0506. ; , s. 87-97
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Journal article (peer-reviewed)abstract
- Eye-tracking has become an invaluable tool for the analysis of working practices in many technological fields of activity. Typically studies focus on short tasks and use static expected areas of interest (AoI) in the display to explore subjects’ behaviour, making the analyst’s task quite straightforward. In long-duration studies, where the observations may last several hours over a complete work session, the AoIs may change over time in response to altering workload, emergencies or other variables making the analysis more difficult. This work puts forward a novel method to automatically identify spatial AoIs changing over time through a combination of clustering and cluster merging in the temporal domain. A visual analysis system based on the proposed methods is also presented. Finally, we illustrate our approach within the domain of air traffic control, a complex task sensitive to prevailing conditions over long durations, though it is applicable to other domains such as monitoring of complex systems.
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| 10. |
- Vitoria, Aida
(author)
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A framework for reasoning with rough sets
- 2004
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Licentiate thesis (other academic/artistic)abstract
- Rough sets framework has two appealing aspects. First, it is a mathematical approach to deal with vague concepts. Second, rough set techniques can be used in data analysis to find patterns hidden in the data. The number of applications of rough sets to practical problems in different fields demonstrates the increasing interest in this framework and its applicability.Most of the current rough sets techniques and software systems based on them only consider rough sets defined explicitly by concrete examples given in tabular form. The previous research mostly disregards the following two problems. The first problem is related with how to define rough sets in terms of other rough sets. The second problem is related with how to incorporate domain or expert knowledge.This thesis proposes a language that caters for implicit definitions of rough sets obtained by combining different regions of other rough sets. In this way, concept approximations can be derived by taking into account domain knowledge. A declarative semantics for the language is also discussed. It is then shown that programs in the proposed language can be compiled to extended logic programs under the paraconsistent stable model semantics. The equivalence between the declarative semantics of the language and the declarative semantics of the compiled programs is proved. This transformation provides the computational basis for implementing our ideas. A query language for retrieving information about the concepts represented through the defined rough sets is also defined. Several motivating applications are described. Finally, an extension of the proposed language with numerical measures is discussed. This extension is motivated by the fact that numerical measures are an important aspect in data mining applications.
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