Journal of Intelligent & Fuzzy Systems - Volume 34, issue 3

Authors: Remmiya Devi, G. | Anand Kumar, M. | Soman, K.P.

Article Type: Research Article

Abstract: Social media is considered to be a vibrant area where millions of individuals interact and share their views. Processing social media text in Indian languages is a challenging task, as it is a well-known fact that Indian languages are morphologically rich in structure. On transferring such an unstructured text into a consistent format, the data is exposed to feature extraction method. In the huge corpora, information units i.e. entities holds the basic idea of the content. The main aim of the system is to recognise and extract the named entities in the social media twitter text. The proposed system relies …on the proficient co-occurrence based word embedding models to extract the features for the words in the dataset. The proposed work makes use of text data from the Twitter resource in the Tamil language. In order to enhance the performance of the system, tri-gram features are extracted from the word embedding vectors. Hence, systems are trained using N-gram embedding features and named entity tags. Implementation of the system is using machine learning classifier, Support Vector Machine (SVM). On comparing the performance of the proposed systems, it can be seen that glove embedding shows better results with the accuracy of 96.93%, whereas the accuracy of word2vec embedding is 84.53%. The improvement in the performance of the system based on glove embedding with regard to the accuracy may be due to the imperative role of the co-occurrence information of glove embedding in recognising the entities. Show more

Keywords: Support Vector Machine, Word2vec, glove embedding, N-gram embedding, structured skip gram

DOI: 10.3233/JIFS-169439

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1435-1442, 2018

Authors: Ahmed, Khalifa | El-Alfy, El-Sayed M. | Awad, Wasan S.

Article Type: Research Article

Abstract: Parallel processing is crucial for accelerating computation in many high-performance applications and modern technologies including computational modeling, optimization and simulation, Web and DNS servers, peer-to-peer systems, grid computing and cloud computing. Due to the heterogeneity nature of various processing nodes and the differences of workloads of various tasks, some processors can be idle while others are overloaded. In this paper, we present a simple, yet efficient, solution inspired by the intelligence of ant colonies to adequately mitigate the load imbalance and communication overhead problems in multiprocessor environments. The proposed approach is based on defining and maintaining data structures to dynamically …track the load of each processor. We implemented the proposed algorithm and evaluated its performance under different scenarios against the baseline round-robin algorithm. The results showed that the proposed algorithm has more effective properties than the round-robin algorithm. Show more

Keywords: Parallel processing, cloud computing, grid computing, load balancing, artificial ant colony, optimization

DOI: 10.3233/JIFS-169440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1443-1451, 2018

Authors: Athira, U. | Thampi, Sabu M.

Article Type: Research Article

Abstract: Illegal cyber activities can be curbed by means of authorship analysis which intends to identify the authors of a document by scrutinizing the writing style involved in it. One of the major threats associated with online media is the propagation of false statements on behalf of celebrities with the aim of tarnishing their public image especially as a part of online political campaigns. The scenario calls for the need of analyzing the authorship of documents with less contents and capturing the author style from among a large number of candidate authors belonging to the same domain. This is a less …explored area of authorship analysis as the task is challenging because traditional methods fail to acquire accuracy when the contents of different authors are pertaining to same topic. Here we propose a method that accomplishes the task of analysis in such an environment, by employing psycholinguistic, lexical, and syntactic aspects of an author combined with word co-occurrences obtained by modeling the style word pattern of the text. The method identifies an author’s individualistic form of expression of emotional aspects, sociolinguistic aspects and word co-occurrences, to obtain an author-style pattern for each candidate author. An author-specific model is generated. The questioned document is fed into the different models so formed, and the final decision regarding the authorship is made based on the ensembled learning method. The experimental results of the proposed method has secured a precision of 0.98 in best case and 0.45 in worst case, thereby illustrating an improvement in the accuracy of authorship attribution of short texts, in comparison with the existing methods. Show more

Keywords: Authorship attribution, computational linguistics, cyber forensics, psycholinguistic features, topic modelling, stylometry, ensembled learning

DOI: 10.3233/JIFS-169441

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1453-1466, 2018

Authors: Mohan, Vijay | Chhabra, Himanshu | Rani, Asha | Singh, Vijander

Article Type: Research Article

Abstract: A novel Non-Linear Fractional order PID controller (NLF-PID) is designed for control of coupled and non-linear 2-link rigid robot. The structure of proposed controller comprises of non-linear hyperbolic function of instantaneous error and current state cascaded with Fractional Order PID (FO-PID). Non-linear function provides adaptive control ability while incorporation of fractional operator enhances flexibility of designed controller. To examine the comparative merits of NLF-PID controller, Non-linear PID (NL-PID), FO-PID and traditional PID schemes are also implemented. Design variables of controllers are optimally tuned using multi objective Non-dominated Sorting Genetic Algorithm II (NSGA-II) for small variation in control and error signal. …Results prove that NLF-PID provides robust and efficient control of robotic arm as compared to other designed controllers for reference tracking, model uncertainty, disturbance and noise due to inherent shortcoming of sensor. Show more

Keywords: Fractional order PID (FO-PID), non-linear PID (NL-PID), non-linear fractional order PID (NLF-PID), robustness analysis, NSGA-II

DOI: 10.3233/JIFS-169442

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1467-1478, 2018

Authors: Kumar, Abhishek | Sharma, Rajneesh | Varshney, Pragya

Article Type: Research Article

Abstract: Markov game based controllers are robust but lack guarantee on the stability of the designed controller. In this work, we attempt to address this shortcoming by proposing a lyapunov fuzzy Markov game controller for safe and stable tracking control of two link robotic manipulators. Lyapunov theory has been used to generate fuzzy linguistic rules for implementing a reinforcement learning (RL) based Markov game controller. We employ fuzzy inference system as a generic function approximator to deal with the “curse of dimensionality” issue. Proposed RL based Markov game controller is self-learning, adaptive and optimal. We implement the proposed control paradigm on: …a) Two link robot manipulator and b) SCARA manipulator for the cases: i) controller handles disturbances and parameter variations, and ii) disturbances and no parameter variations. We give comparative evaluation of our approach against: a) fuzzy Q learning controller, and b) fuzzy Markov game controller. Simulation results illustrate stable and superior tracking performance and advantage in terms of lower control torque requirements. Show more

Keywords: Reinforcement learning, fuzzy Q learning, fuzzy Markov game control, lyapunov fuzzy control, two link robotic manipulator, SCARA

DOI: 10.3233/JIFS-169443

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1479-1490, 2018

Authors: Nangrani, S.P. | Singh, Arvind R. | Chandan, Ajaysingh

Article Type: Research Article

Abstract: Engineering systems are governed by set of differential equations and work under various uncertainties of parameters. Type–1 fuzzy logic controller are widely used in engineering systems for expert control of system using logic and mathematics together. This paper proposes the first-ever use of Interval Type–2 fuzzy logic controller design to control chaos and associated instability in a nonlinear dynamical power system. Interval Type–2 fuzzy designs have an edge over type-1 fuzzy sets and interval type–2 fuzzy logic controller is well suited for the uncertainty present in weak and chaos sensitive systems. Uncertainty in parameters affects differential equation very badly for …such systems. Uncertainty in engineering applications needs an extra layer of handling system control mathematically and logically. Comparison of Type–1 and Type–2 fuzzy logic controller based on time domain waveform, phase plane trajectory and integral square error, clearly proves the efficacy of Type–2 fuzzy logic controller in controlling dynamic behavior of a nonlinear dynamical system as demonstrated through results discussed in the paper. This paper discusses control of chaos driven voltage instability issue in the case of nonlinear dynamical power system, as an application. Show more

Keywords: Type-2 fuzzy logic controller, interval type-2 fuzzy logic controller, fuzzy logic set, nonlinear dynamical system

DOI: 10.3233/JIFS-169444

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1491-1501, 2018

Authors: Gupta, Shalini | Dixit, Veer Sain

Article Type: Research Article

Abstract: This article presents a scalable and optimized recommender system for e-commerce web sites to maintain a better customer relationship management and survive among its competitors. The proposed system analyses the clickstream data obtained from an ecommerce site and predicts the preference level of the customer for the products clicked but not purchased using efficient classifiers such as decision trees, artificial neural networks and extended trees. Collaborative filtering technique is used to recommend products in which similarity measures are used along with efficient rough set leader clustering algorithm which helps in making accurate and fast recommendations. To determine the effectiveness of …the proposed approach, an experimental evaluation has been done which clearly depicts the better performance of the system as compared to conventional approaches. Show more

Keywords: Recommender system, e-commerce, clickstream data, preference level, collaborative filtering, rough set leader clustering

DOI: 10.3233/JIFS-169445

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1503-1510, 2018

Authors: Sharma, Chhavi | Bedi, Punam

Article Type: Research Article

Abstract: The microblogging service Twitter has witnessed a rapid increase in its adopters ever since it’s discovery in October 2006. Today it has become a medium of communication as well as spread of information. Hashtags are created in twitter by users whenever an event of significant importance occurs and hence they become trending on twitter network. Once hashtags are created on twitter platform, the tweeters may communicate within a particular community of interest following and tweeting to any particular hashtag conversations. In this paper, we propose the design of Community based Hashtag Recommender System (CHRS) for twitter users. This will help …the users by expanding their hashtag base and hence strengthening the hashtag conversation for a particular event. The tweets collected over a period of time for some particular hashtags have been categorised to communities based on sentiment analysis of the tweets. Once the process of community detection completes, the existing users are found in the tweets. Further the idea of Hashtag frequency- Inverse Community Frequency (HF-ICF) has been suggested and deployed to find hashtags which uniquely distinguish the users found earlier. Finally relevance score is computed based on the idea of collaborative filtering approach to recommendation, for various hashtags used by the users. A prototype of the system is developed using the statistical tool R and experimental analysis has been carried out. Tweets of national concern in India pertaining to ‘demonetisation’ have been collected and used for experimental purposes. Show more

Keywords: Recommender system, demonetisation, twitter, hashtag, community detection, HF-ICF

DOI: 10.3233/JIFS-169446

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1511-1519, 2018

Authors: Richa, | Bedi, Punam

Article Type: Research Article

Abstract: Recommender systems (RS) suffer from cold start and data sparsity problem. Researchers have proposed various solutions to this problem in which cross domain recommendation is an effective approach. Cross domain recommender system (CDRS) utilizes user data from multiple domains to generate prediction for the target user. This paper proposes a proactive cross domain recommender system. This paper also introduces a parallel approach in cross domain recommendation using general purpose graphic processing unit (GPGPU). This will help to accelerate the computation in the multi-agent environment as data processing in multiple domains takes significant amount of time. A prototype of the system …is developed in tourism domain using Cuda, JCuda, Java, Android studio and Jade. The system uses four domains which is restaurant, tourist places, shopping places and hotels. The performance of the parallel CDRS system is compared with non-parallel CDRS in terms of their processing speed. Also the system is compared to the normal Collaborative Filtering approach to measure accuracy of the proposed system using MAE as well as precision, recall and F-measure. The results show a significant speedup for the presented system over non-parallel system. Show more

Keywords: Recommender system, cross domain, proactive recommender system, multi-agent system, parallel processing

DOI: 10.3233/JIFS-169447

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1521-1533, 2018

Authors: Vimala, J. | Reeta, J. Arockia | Ilamathi, V.S. Anusuya

Article Type: Research Article

Abstract: Aktas and Cagman propounded soft group in 2007 and Abdulkadir Aygunoglu and Halis Aygun defined fuzzy soft group in 2009. In 2016, J. Vimala and J. Arockia Reeta proposed lattice ordered fuzzy soft group and derived its pertinent properties. In this work, fuzzy soft cardinality and fuzzy soft relative cardinality are promoted in lattice ordered fuzzy soft group. Then we give decision making method that can be applied successfully for solving many problems with uncertainties.

Keywords: l-Fsg, fuzzy soft cardinality, fuzzy soft relative cardinality

DOI: 10.3233/JIFS-169448

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 3, pp. 1535-1542, 2018