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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Maleszka, Bernadetta
Article Type: Research Article
Abstract: Traditional approaches to content-based recommendation and collaborative filtering do not suffer from cold-start problem, which is a challenge to recommend items for an unknown user. In this paper we present a Personalized Document Retrieval System which takes into account a social network information about the users. The overall idea of the system is to cluster users into groups of similar interests based on theirs usage data and to determine a representative profile for each of the groups. When a new user joins the system, he or she is classified into one of existing group based on his or her user …data and the representative profile of the group becomes a starting profile for the new user. This paper focuses on a method for updating ontology-based user profile using Bayesian network approach. We analyze some properties of proposed updating method and describe an idea of experimental evaluations. Show more
Keywords: Recommendation system, cold-start problem, user profile, social networks, collaborative filtering, Bayesian network
DOI: 10.3233/JIFS-179343
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7337-7346, 2019
Authors: Starzec, Mateusz | Starzec, Grażyna | Byrski, Aleksander | Turek, Wojciech | Kisiel-Dorohinicki, Marek
Article Type: Research Article
Abstract: Solving difficult, usually NP-hard problems, requires metaheuristic-based approach. Such algorithms are very often demanding from the point of view of computational power. Therefore various approaches to parallelize or distribute such systems were made. Many of such algorithms are structurally very easy to parallelize, e.g. evolutionary ones. However, swarm computing algorithms, in particular ACO (Ant Colony Optimization), in order to be implemented properly must use a significant amount of global knowledge (pheromones matrix). Therefore strict parallelization/distribution strategies for ACO are difficult to work-out. In the presented paper we propose a novel approach for parallelization and distribution of the most important element …of ACO, namely the pheromone table. Our prototype implementation is tested on a real-world HPC (High Performance Computing) infrastructure, with good observed scalability. At the end of this paper we present actual experimental results focusing on two class of problems, namely TSP (Travelling Salesman Problem) and VRPTW (Vehicle Routing Problem with Time Windows), using popular benchmarks. Show more
Keywords: parallel and distributed computing, ant colony optimization, swarm intelligence, high performance computing
DOI: 10.3233/JIFS-179344
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7347-7356, 2019
Authors: Bădică, Amelia | Bădică, Costin | Ivanović, Mirjana | Logofătu, Doina
Article Type: Research Article
Abstract: We analyze intermediation business processes that enable companies to use multiple distribution channels for expanding their market horizon of potential customers that are interested in purchasing their products and/or services. These distribution channels are represented by sequences of intermediation transactions supported by usually self-interested middle-agents that enable the connection of the providers with the end costumers. We propose a new formal model of network-structured intermediation business processes represented as Directed-Acyclic-Graphs. Using this model we obtained sound theoretical results of collectively profitable intermediation transactions. This paves the way for further proposal of optimal pricing strategies of the participating agents in semi-competitive …environments. Show more
Keywords: Welfare economics, intermediation networks, collective intelligence, multi-agent system, graph theory, linear algebra
DOI: 10.3233/JIFS-179345
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7357-7368, 2019
Authors: Floria, Sabina-Adriana | Leon, Florin | Logofătu, Doina
Article Type: Research Article
Abstract: Social networks currently belong to a vast area of research as information spreads at a remarkable speed due to technology, and social connections have become easily accessible in the online environment. Social networks are dynamic entities, which new individuals can join, or other links can be lost because members no longer interact with one-another. Dynamic analysis of social networks is important in topology changes of the network and also in information diffusion. Some information that spreads through the social network may be untrue, hence in this paper we propose a protocol based on evidence theory with Dempster-Shafer and Yager’s rules …in which the network becomes more immune to false information. We also analyze the impact of topology change for an initial network by adding new connections in the information diffusion process. We show information diffusion by coloring the nodes of the network and also illustrate the time evolution of messages for a better accuracy in our comparisons. The experimental results confirm that the proposed model fits the behavior of inhibiting false information. Show more
Keywords: Information credibility, information diffusion, social networks, confidence degree
DOI: 10.3233/JIFS-179346
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7369-7381, 2019
Authors: Mazur, Zygmunt | Pec, Janusz
Article Type: Research Article
Abstract: In this paper we describe a heuristic procedure for solving the travelling salesman problem in the symmetric case without using the triangle inequality c ij ≤ c ik + c kj . A complete proof of the correctness of the algorithm and example of the presentation how the method works are given. There is estimated computational complexity, which is at most O(m2 ), where m is a number of the edges of the complete graph with n vertices -K n . There is shown also, it is possible obtain the following bound that HEURISTIC SOLUTION …OPTIMAL SOLUTION < 3 , if some specific inequality considering weights (costs) of edges is satisfied. Show more
Keywords: Symmetric travelling salesman problem (STSP), assignment problem, hamiltonian circuit, simple graph, simple circuit, complete graph Kn , list Li , heuristics
DOI: 10.3233/JIFS-179347
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7383-7388, 2019
Authors: Calvo, Iván | Merayo, Mercedes G. | Núñez, Manuel
Article Type: Research Article
Abstract: Uncertainty and imprecision play an important role in the specification and analysis of complex systems. Therefore, it is important to provide methodologies and tools to support the correct development of these systems. In this paper we present a new formalism, based on fuzzy automata , to facilitate the different phases involved in the development of a system where information is fuzzy . The formal syntax and semantics of our formalism are based on previous work, which has been adapted to be easily implemented and automated. We introduce a methodology to analyze systems modelled with one of our fuzzy automata. Finally, …we show how our framework can be used to define a model of the heart based on electrocardiograms (ECGs) and use this model to analyze data of real patients. Show more
Keywords: Fuzzy automata, formal specification, ECG
DOI: 10.3233/JIFS-179348
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7389-7399, 2019
Authors: Karim, Redwanul | Islam, M. A. Muhiminul | Simanto, Sazid Rahman | Chowdhury, Saif Ahmed | Roy, Kalyan | Al Neon, Adnan | Hasan, Md. Sajid | Firoze, Adnan | Rahman, Rashedur M.
Article Type: Research Article
Abstract: Information Extraction allows machines to decipher natural language through using two tasks: Named Entity Recognition and Relation Extraction. In order to build such a system for Bangla Language, in this work a Named Entity Recognition (NER) System is proposed, which requires a minimum information to deliver a decent performance having less dependency on handcrafted features. The proposed model is based on Deep Learning, which is accomplished through the use of a Densely Connected Network (DCN) in collaboration with a Bidirectional-LSTM (BiLSTM) and word embedding, i.e., DCN-BiLSTM. Such a system, specific to the Bangla language, has never been done before. Furthermore, …a unique dataset was made since no Named Entity Recognition dataset exists for Bangla language till date. In the dataset, over 71 thousand Bangla sentences have been collected, annotated, and classified into four different groups using IOB tagging scheme. Those groups are person, location, organization, and object. Due to Bangla’s morphological structure, character level feature extraction is also applied so that we can access more features to determine relational structure between different words. This is initially done with the use of a Convolutional Neural Network but is later outperformed by our second approach which is through the use of a Densely Connected Network (DCN). As for the training portion, it has been done for two variations of word embedding which are word2vec and glove, the outcome being the largest vocabulary size known to both models. A detailed discussion in regard to the methodology of the NER system is explained in a comprehensive manner followed by an examination of the various evaluation scores achieved. The proposed model in this work resulted in having a F1 score of 63.37, which is evaluated at Named Entity Level. Show more
Keywords: Named entity recognition, information extraction, word embedding, sequence labelling, Bi-LSTM, densely connected network, Bangla, annotation, dataset, NLP, neural network, character level feature extraction, CNN
DOI: 10.3233/JIFS-179349
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7401-7413, 2019
Authors: Smaïli, Kamel | Fohr, Dominique | González-Gallardo, Carlos-Emiliano | Grega, Michał | Janowski, Lucjan | Jouvet, Denis | Koźbiał, Arian | Langlois, David | Leszczuk, Mikołlaj | Mella, Odile | Menacer, Mohamed-Amine | Mendez, Amaia | Pontes, Elvys Linhares | SanJuan, Eric | Torres-Moreno, Juan-Manuel | Garcia-Zapirain, Begoña
Article Type: Research Article
Abstract: The aim of the work is to report the results of the Chist-Era project AMIS (Access Multilingual Information opinionS). The purpose of AMIS is to answer the following question: How to make the information in a foreign language accessible for everyone? This issue is not limited to translate a source video into a target language video since the objective is to provide only the main idea of an Arabic video in English. This objective necessitates developing research in several areas that are not, all arrived at a maturity state: Video summarization, Speech recognition, Machine translation, Audio summarization and Speech segmentation. …In this article we present several possible architectures to achieve our objective, yet we focus on only one of them. The scientific locks are be presented, and we explain how to deal with them. One of the big challenges of this work is to conceive a way to evaluate objectively a system composed of several components knowing that each of them has its limits and can propagate errors through the first component. Also, a subjective evaluation procedure is proposed in which several annotators have been mobilized to test the quality of the achieved summaries. Show more
Keywords: Automatic speech recognition, statistical machine translation, video summarization, text boundary segmentation, collecting data, text and audio summarization, objective and subjective evaluations
DOI: 10.3233/JIFS-179350
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7415-7426, 2019
Authors: Deb, Tonmoay | Ali, Mohammad Zariff Ahsham | Bhowmik, Sanchita | Firoze, Adnan | Ahmed, Syed Shahir | Tahmeed, Muhammad Abeer | Rahman, N.S.M. Rezaur | Rahman, Rashedur M.
Article Type: Research Article
Abstract: Understanding the context with generation of textual description from an input image is an active and challenging research topic in computer vision and natural language processing. However, in the case of Bengali language, the problem is still unexplored. In this paper, we address a standard approach for Bengali image caption generation though subsampling the machine translated dataset. Later, we use several pre-processing techniques with the state-of-the-art CNN-LSTM architecture-based models. The experiment is conducted on standard Flickr-8K dataset, along with several modifications applied to adapt with the Bengali language. The training caption subsampled dataset is computed for both Bengali and English …languages for further experiments with 16 distinct models developed in the entire training process. The trained models for both languages are analyzed with respect to several caption evaluation metrics. Further, we establish a baseline performance in Bengali image captioning defining the limitation of current word embedding approaches compared to internal local embedding. Show more
Keywords: Image captioning, CNN, LSTM, natural language processing, computer vision, Bengali image captioning, merge architecture, par-inject architecture, machine translated caption subsampling
DOI: 10.3233/JIFS-179351
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7427-7439, 2019
Authors: Anh, Kieu Que | Nagai, Yukari | Le Minh, Nguyen
Article Type: Research Article
Abstract: With the development of social networks and online shopping sites, we can easily obtain valuable feedback from users. The crucial question is how to utilize customer feedback for supporting the development of product design in the early phases. For product design, understanding user needs or user requirements would help designers design a better product for users. Therefore, user requirements is considered as an important role in product design. This paper proposes a framework for assessing user requirements from websites to support designers. They key idea is to extract user requirements from online customer reviews and represent them into an appropriate …form for designers. We show that a support system consisting of feature aspect extraction, opinion summarization, and sentiment classification would be an useful tool for product design. Experimental results on a the data collected from the Amazon website show that supporting of opinion extraction techniques would be useful for designers in product design. Show more
Keywords: Opinion mining, product design, sentiment classification, users requirements (URs)
DOI: 10.3233/JIFS-179352
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7441-7451, 2019
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