Journal of Intelligent & Fuzzy Systems - Volume 37, issue 6

Authors: Pinto, José Pedro | Viana, Paula

Article Type: Research Article

Abstract: The development of efficient methods for searching and browsing large assets of video content has been considered by the academia and content owners for long. Different approaches that range from manual structured annotations, to unstructured metadata collected from several sources, as well as multimedia processing for automatic description of the content, can be identified. The growth on the number of hours of video content put online in video sharing platforms has however shown that video retrieval is still quite inefficient as rich contextual data that describes the content is most of the times still not available. Additionally, metadata is usually …not linked to timed moments of content, making direct access to the most relevant moments not possible. In this paper, an approach for making web videos available in the YouTube platform more accessible is presented. The solution is based on a collaborative process presented as a game that enables collecting metadata from the crowd while implementing mechanisms that remove erroneous information usually encountered in this type of information. Metadata, exported to YouTube in the form of captions and descriptions, contributes to enhance video retrieval, guaranteeing a better user experience and exposure of the content. Show more

Keywords: Video tag, video retrieval, crowdsourcing, multimedia content annotation, gamification, social media, YouTube

DOI: 10.3233/JIFS-179333

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7207-7221, 2019

Authors: Jureczko, Marian | Nguyen, Ngoc Trung | Szymczyk, Marcin | Unold, Olgierd

Article Type: Research Article

Abstract: Defect prediction is a method of identifying possible locations of software defects without testing. Software tests can be laborious and costly thus one may expect defect prediction to be a first class citizen in software engineering. Nonetheless, the industry apparently does not see it that way as the level of practical usages is limited. The study describes the possible reasons of the low adoption and suggests a number of improvements for defect prediction, including a confusion matrix-based model for assessing the costs and gains. The improvements are designed to increase the level of practitioners acceptance of defect prediction by removing …the recognized by authors implementation obstacles. The obtained predictors showed acceptable performance. The results were processed through the suggested model for assessing the costs and gains and showed the potential of significant benefits, i.e. up to 90% of the overall cost of the considered test activities. Show more

Keywords: software metrics, software development process, defect prediction, re–open prediction, predicting feature defectiveness, defect prediction economy

DOI: 10.3233/JIFS-179334

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7223-7238, 2019

Authors: Czarnowski, Ireneusz | Jędrzejowicz, Piotr

Article Type: Research Article

Abstract: Class imbalance arises when the number of examples belonging to one class is much greater than the number of examples belonging to another. The discussed approach focuses on combining several techniques including data reduction and stacking with the aim of improving the performance of the machine classification in the case of imbalanced data. The paper proposes a cluster-based data reduction approach assuming that the instances are selected from a cluster, the data reduction is carried-out on instances belonging to the majority classes, and the aim of the instance selection is to reduce the imbalance ratio between the majority and minority …classes. The process of instance selection is carried out with using an agent-based population learning algorithm. To increase performance and generalization ability of the prototype-based machine learning classification it was decided to use the stacking technique. The proposed approach is validated experimentally using several benchmark datasets from the KEEL repository. Advantages and main features of the approach are discussed considering the results of the computational experiment. Show more

Keywords: Instance selection, clustering, stacking, imbalanced data, team of agents

DOI: 10.3233/JIFS-179335

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7239-7249, 2019

Authors: Phan, Huyen Trang | Nguyen, Ngoc Thanh | Tran, Van Cuong | Hwang, Dosam

Article Type: Research Article

Abstract: Sentiment analysis has been gaining importance in many applications such as recommendation systems, the decision making support and prediction models. Sentiment analysis helps to understand and evaluate public opinion regarding social events, product services, and political trends, especially the feelings expressed through comments by users in social networks such as Twitter, Facebook, and Instagram. There have been a lot of research attempts to address the tweets sentiment analysis problem with high accuracy, particularly in case of tweets that express a single sentiment towards a single object. However, the results of the classification are not highly accurate in cases such as …the following: a user expresses multiple sentiments towards a single object in a tweet; a user presents multiple sentiments towards multiple objects; and a user indicates a single sentiment towards multiple objects. Furthermore, the previous studies only analyze the sentiment of each tweet without considering the objects and the sentiment towards each object from an entire set of tweets. This study attempts to deal with the limitations of the previous methods; an approach is proposed herein, based on integrating the sentiment towards a particular object from all tweets related to that object. The proposed method focuses on determining the objects and indicating the sentiment towards the specific objects by combining the sentiments related to each object from the entire set of tweets. On experimental evaluation, the proposed method is observed to have achieved a fairly good result in terms of the error ratio and achieved information. Show more

Keywords: Sentiment-analysis, sentiment-integration, object-determination

DOI: 10.3233/JIFS-179336

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7251-7263, 2019

Authors: Nguyen, Van Tham | Nguyen, Ngoc Thanh | Tran, Trong Hieu

Article Type: Research Article

Abstract: In the stages of development of probabilistic expert systems, knowledge merging is a major concern. To deal with knowledge merging problems, several approaches have been put forward. However, in the proposed models, each original probabilistic knowledge base (PKB) is represented by a set of probabilistic functions fulfilling such knowledge base. The drawbacks of the solutions are that the output of model is also a set of probabilistic functions satisfying the resulting PKB and there is no algorithm for implementing the merging process of PKBs in which each of them consists of probabilistic constraints. In this paper, distance-based approach is utilized …to propose a new method of merging PKBs to ensure that both the input and output of methods are represented by sets of probabilistic constraints. To this aim, the relationship between the probability rules and the probabilistic constraints, and the several transformation methods for the representation of the original PKB are presented, a set of merging operators (MOs) is proposed, and several desirable logical properties are investigated and discussed. Several algorithms for merging PKBs are presented and the computational complexities of these algorithms are also analyzed and evaluated. Show more

Keywords: Probabilistic knowledge base, knowledge merging, merging operator, algorithm

DOI: 10.3233/JIFS-179337

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7265-7278, 2019

Authors: Nguyen, Van Du | Truong, Hai Bang | Merayo, Mercedes G. | Nguyen, Ngoc Thanh

Article Type: Research Article

Abstract: Recently, the use of the wisdom of crowds (WoC) for finding solutions to a wide range of real-life problems has dramatically expanded. Prior studies have revealed that diversity, independence, decentralization, and aggregation are the determinants of collective wisdom. However, these findings are often based on the so-called point estimates - single values are used as the representations of individual predictions on the task of estimating unknown quantities or predicting outcomes of future events. In some situations, interval values, which are often called interval estimates , can be used for such representations. Accordingly, one can provide an individual …prediction in the form of an interval value including a lower and an upper bounds. Taking into account this kind of representation, in this paper, we present a case study in which collectives of randomly selected predictions can outperform those of most accurate predictions. Then, we evaluate the WoC level by taking into account diversity and cardinality. The computational experiments have indicated that diversity is positively related to collective wisdom. Finally, we discuss some related theoretical and practical implications for further research. Show more

Keywords: Collective intelligence, wisdom of crowds, interval estimates

DOI: 10.3233/JIFS-179338

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7279-7289, 2019

Authors: Kozierkiewicz, Adrianna | Pietranik, Marcin | Sitarczyk, Mateusz

Article Type: Research Article

Abstract: Data integration is one of the trending topics in the modern computer science. It is not an uncommon task to deliver a unified perspective on a set of heterogenous data that would serve as a consensus of participating elements. Many computationally expensive solutions can be found in the literature. Moreover, one cannot determine how potential changes applied to inputs of these methods impact their results. In this paper we present a framework of managing evolving data and handling the entailments of the unforeseen alterations of inputs in terms of performing sound data integration in an acceptable time. We base our …work on the consensus theory and provide theoretical foundations, an experimental evaluation and a statistical analysis of obtained results. Show more

Keywords: consensus theory, knowledge integration, knowledge management

DOI: 10.3233/JIFS-179339

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7291-7302, 2019

Authors: Łuszpaj, Adam | Dobrowolski, Grzegorz

Article Type: Research Article

Abstract: An enormous volume of well-structured data with explicit semantics, in accordance with W3C’s standards, becomes a reality in the Web of Linked Data. However, the Semantic Web promise to turn it into a machine-processable global graph of knowledge still encounters numerous impediments. Efficient access and discovery along with the semantic heterogeneity have been identified as major stumbling blocks. Following the design principles for Semantic Web and Linked Data, we present ActiveDiscovery, a decentralized infrastructure for distributed SPARQL query evaluation based on its terminological entities, namely the ontologies used in a query. ActiveDiscovery’s main goal is to facilitate distributed and transparent …semantic search based on structural rather than keyword-based querying in the Semantic Web. Key architectural extensions regarding metadata, indexing and ontology alignment are proposed to achieve transparency for federated query execution in a decentralized manner. The rewriting procedure for extensional SPARQL query is considered regarding the proposed components and SERVICE clause as a standard recommendation for query federation. We investigate the feasibility of our approach and present preliminary results of initial evaluation. We conclude by indicating questions which need to be addressed in future work. Show more

Keywords: Semantic Web, query federation, ontologies, SPARQL, decentralized architecture

DOI: 10.3233/JIFS-179340

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7303-7312, 2019

Authors: Maleszka, Marcin

Article Type: Research Article

Abstract: In this paper we present an extended model of an unsupervised collective, that is a group where each member communicates with others to form opinions, instead of a single supervisor determining the overall collective knowledge. We describe the social influence theories that are the basis of the proposed model, and how they translate to a multi-agent model of the collective. We define two measures of social influence that are formalizations of concepts presented in sociological research. We perform a simulation experiment, where we observe the behavior of the collective in relation to those measures. Finally, we present a road-map of …future improvements possible in the model, working towards a real world test of its feasibility. Show more

Keywords: Unsupervised collective, collective knowledge, social influence, knowledge diffusion

DOI: 10.3233/JIFS-179341

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7313-7323, 2019

Authors: Hernes, Marcin | Sobieska-Karpińska, Jadwiga

Article Type: Research Article

Abstract:  The supply chain is a key element of successful operation of businesses in a turbulent economic situation. Swift management of delivery of raw materials and finished products while keeping costs as low as possible and maintaining proper customer service is becoming as vital as the quality and price of a product when gaining competitive advantage. This leads companies to a wide search for the best strategies that allow efficient management of the supply chain. The basic problem, however, is the occurrence of the so-called Forrester effect (also known as the bullwhip effect). It involves intensified transposing of changes in demand …onto the execution of product flow in supply chains. The aim of this article is to develop a manner to reduce the Forrester effect using the consensus method. The first part of the article analyzed the current state of knowledge on the discussed problem. Then it presented basic elements of the developed prototype of a SCM system and defined the meth-od for reducing the Forrester effect using a consensus algorithm. The final part of the article de-scribes the way to conduct an experiment that involves verifying the consensus algorithm and analyzes the results of the verification and their influence on the reduction of the Forrester effect. Show more

Keywords: Supply chain management, Forrester effect, consensus methods

DOI: 10.3233/JIFS-179342

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7325-7335, 2019