Journal of Intelligent & Fuzzy Systems - Volume 32, issue 2

Authors: Nguyen, Ngoc-Thanh | Núñez, Manuel | Trawiński, Bogdan

Article Type: Editorial

Abstract: Collective intelligence is most often understood as group intelligence which arises on the basis of intelligences of the group members. This paper presents an overview of application of collective intelligence methods in knowledge engineering and in processing collective data. It also introduces papers included in this issue.

Keywords: Collective intelligence, intelligent systems, knowledge engineering

DOI: 10.3233/JIFS-169115

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1157-1160, 2017

Authors: Kozierkiewicz-Hetmańska, Adrianna | Pietranik, Marcin

Article Type: Research Article

Abstract: Nowadays, due to the high level of data distribution, it is frequently impossible to generate a unified representation of a variety of heterogenous data sources in a single step. Dividing the integration process into smaller subtasks and their parallelization can solve this problem. Unfortunately, it entails difficulties concerning the initial classification of data sources into groups that can be independently integrated, and serve as an input for the final integration step. The problem becomes even more complicated when not only raw data is required to be integrated, but the designed system is expected to perform more expressive integration of heterogenous …knowledge representations, such as ontologies. In our previous work [10 ] we have proved both analytically and experimentally that such approach to the integration task can increase its effectiveness in terms of the time required to obtain the final result. In this article we intend to explore the issue of selecting initial classes of ontologies based on the novel notion of the knowledge increase. This indicator can be computed before the integration and moreover answer the question concerning whether this integration is viable. This not only simplifies the initial distribution of aforementioned subtasks, but can also be used as a stop condition during subsequent steps of the integration. Show more

Keywords: Ontology integration, knowledge management, consensus theory

DOI: 10.3233/JIFS-169116

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1161-1172, 2017

Authors: Nguyen, Quang Vu | Madeyski, Lech

Article Type: Research Article

Abstract: Traditional mutation testing is a powerful technique to evaluate the quality of test suites. Unfortunately, it is not yet widely used due to the problems of a large number of generated mutants, limited realism (mutants not necessarily reflect real software defects), and equivalent mutants problem. Higher order mutation (HOM) testing has been proposed to overcome these limitations of first order mutation testing. We present an empirical evaluation of our approach to higher order mutation testing. We apply different multi-objective optimization algorithms (including one modified by us), as well as our classification of HOMs, proposed objectives and fitness functions. We search …for “High Quality and Reasonable HOMs” able to replace all of its constituent FOMs without scarifying test effectiveness and to reflect complex defects requiring more than one change to correct them. Our approach leads to: 1) reduced cost of mutation testing due to reduced number of HOMs, 2) harder to kill mutants (which mimic harder to find defects), 3) reduced cost of mutation testing as it does not waste resources for creating easy-to-kill mutants. Furthermore, we establish a relevant upper bound on mutation order in higher order mutation testing and thus reduce the cost of mutation even further. Show more

Keywords: Mutation testing, higher order mutation testing, higher order mutants, multi-objective optimization algorithm, upper bound order

DOI: 10.3233/JIFS-169117

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1173-1182, 2017

Authors: Hnatkowska, Bogumiła

Article Type: Research Article

Abstract: Ontologies can be used to represent the semantics of the information interchanged between heterogeneous information systems. Their quality expressed regarding 3C: consistency, completeness, and conciseness, is of primary importance. The paper defines a set of static semantics rules for evaluating the quality of ontology defined with the use of a meta-model. The rules themselves are expressed formally in OCL language. The meta-model and the rules were successfully implemented in the checker tool and used for verification of SUMO ontology. Results show that the files that constitute two upper layers of SUMO ontology suffer from some errors which should be eliminated. …The ontology verification method together with the tool can also be applied for SUMO domain ontologies as well as be adapted for other ontologies. Show more

Keywords: Ontology, verification, static semantics rules, SUMO, meta-model, UML, OCL

DOI: 10.3233/JIFS-169118

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1183-1192, 2017

Authors: Strobin, Lukasz | Niewiadomski, Adam

Article Type: Research Article

Abstract: An approach to performing linguistic summaries of graph datasets, with particular focus on usage of ontologies is presented in this paper. This well-known mining technique is based on fuzzy set theory, which is used to model natural language words (e.g. ‘many’, ‘tall’), and in result - generates natural-like sentences describing the data. Although intensely developed, before our work this method has been applied only to relational databases, while more and more data is available in graph model. A special case of such graph datasets is the Semantic Web, in which ontologies provide meaning, therefore enabling advanced machine learning. In our …paper we analyze the problem of generating linguistic summaries for a graph data case (for which the method cannot be directly applied), with associated ontologies. The key element of ontologies are concept hierarchies, which are the core of our work. Firstly, due to heterogeneity and lack of schema we propose to use an ontological concept (including all sub-concepts in hierarchy) as a subject for summaries, and extract their attributes (neighboring vertexes). Then we show that by ascending these ontological concept hierarchies (so by attribute-based induction) we obtain additional, generalized summaries. We show this process for both summarizers and qualifiers, and propose an extension to their respective imprecision measures - T 2 and T 9 . We perform two experiments on DBPedia - one for summary subject ‘Artist’, and second for ‘Musical Album’. For the latter, we show the optimized process of obtaining the truth values using bottom-up approach. Show more

Keywords: Linguistic summaries, fuzzy logic, ontology, Semantic Web

DOI: 10.3233/JIFS-169119

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1193-1202, 2017

Authors: Nguyen, Linh Anh | Nguyen, Thi Hong Khanh | Nguyen, Ngoc-Thanh | Ha, Quang-Thuy

Article Type: Research Article

Abstract: We introduce comparisons w.r.t. information between interpretations in paraconsistent description logics and use them to define bisimilarity for such logics. This notion is useful for concept learning in description logics when inconsistencies occur. We give preservation results and the Hennessy-Milner property for comparisons w.r.t. information in paraconsistent description logics. As consequences, we obtain also invariance results and the Hennessy-Milner property for bisimilarity in paraconsistent description logics.

Keywords: Description logics, paraconsistent logics, bisimulation, bisimilarity

DOI: 10.3233/JIFS-169120

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1203-1215, 2017

Authors: Nguyen, Ngoc Thanh | Nguyen, Van Du | Hwang, Dosam

Article Type: Research Article

Abstract: Collective knowledge is understood as the common knowledge state of a collective consisting of autonomous units. The knowledge states referred from these autonomous units to some degree reflect the real knowledge state of a subject in the real world, but it is not known to what degree because of incompleteness and uncertainty. Although collective knowledge determination is an important task because these knowledge states can be different from each other, there exists another important issue with its quality. The quality of collective knowledge is based on the difference between the real knowledge state and the collective knowledge. In this study, …we investigate the influence of the number of collective members on the quality of collective knowledge. Through experimental analysis, the larger collective we use, the better the quality of collective knowledge will be. In other words, the large number of collective members positively affects the quality of collective knowledge. Besides, some theorems about the relationship between the collective knowledge and the knowledge states in a collective, the influence of adding or removing members on the quality of collective knowledge are also proved. Show more

Keywords: Collective knowledge, consensus choice, inconsistency knowledge

DOI: 10.3233/JIFS-169121

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1217-1228, 2017

Authors: Tran, Quang Dieu | Hwang, Dosam | Jung, Jason J.

Article Type: Research Article

Abstract: Various content-based methods (e.g., audio-visual feature recognition and dialogs analysis) have been proposed for analyzing, indexing and understanding movies. Our previous approach introduced a method for character indexing based on manual annotation. However, this method has shown several unsatisfactoriness on performing of indexing. For addressing this issue, in this work, we take into account using image processing techniques for semi-automatically character-based indexing. Besides, a movie ontological model is created for connecting character appearances and character’s roles in the movie. Moreover, we propose a system for assist user indexing manually. On the other hand, a searching and browsing tool is also …introduced. Using this tool, user can query character-based semantic indexing. Experimental results are shown that our proposed method is able to assist user in consuming index time and providing a method for automatic indexing, searching and browsing based on semantic queries. Show more

Keywords: Video analysis, video indexing, character network, character-based analysis, social network, ontology

DOI: 10.3233/JIFS-169122

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1229-1240, 2017

Authors: Maleszka, Marcin

Article Type: Research Article

Abstract: Integration of collective knowledge becomes a more and more common task, but research rarely focuses on how it is influenced by the time dimension. In this paper we describe expanding conflict profile – a method to model the changes in collective knowledge consensus when the group is slowly adding new members with new opinions. We also describe the asynchronous aspect of group communication in a decentralized multi-agent system. We provide simulation experiments for both parts, as well as a prototype application using the results of our research. We show that our approach may be successfully used in applications, where previously …only a centralized multi-agent systems were used. Show more

Keywords: Knowledge integration, multiagent system, collective knowledge, consensus theory

DOI: 10.3233/JIFS-169123

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1241-1252, 2017

Authors: Maleszka, Bernadetta

Article Type: Research Article

Abstract: Information overload has become a very important aspect of information retrieval domain. Even if a user knows where to look for interesting information, he can have a problem with precisely formulating his information needs. A solution of the problem is personalization and recommendation system – they observe user activities, analyze them to discover important preferences. Based on these information the system can improve the effectiveness of the results. In this paper we present a method for determining user profile in a document retrieval system. We propose ontology-based profile. Such a structure allows to process semantic relations between users’ queries. We …focus on methods for adapting profile because only up-to-date profile can help the user to obtained results that correspond with his information needs. We present a set of postulates for adaptation methods. Performed experimental evaluations of developed methods are promising. Show more

Keywords: Document retrieval, knowledge integration, user profile adaptation, ontology-based user profile

DOI: 10.3233/JIFS-169124

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 2, pp. 1253-1263, 2017