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Protecting the privacy of social network data using graph correction Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-17 Amir Dehaki Toroghi, Javad Hamidzadeh
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An approach for fuzzy group decision making and consensus measure with hesitant judgments of experts Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-17 Chao Huang, Xiaoyue Wu, Mingwei Lin, Zeshui Xu
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A fuzzy rough set-based horse herd optimization algorithm for map reduce framework for customer behavior data Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-16 D. Sudha, M. Krishnamurthy
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Range control-based class imbalance and optimized granular elastic net regression feature selection for credit risk assessment Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-16 Vadipina Amarnadh, Nageswara Rao Moparthi
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Argumentation-based multi-agent distributed reasoning in dynamic and open environments Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-15 Helio Monte-Alto, Mariela Morveli-Espinoza, Cesar Tacla
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Graph neural architecture search with heterogeneous message-passing mechanisms Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-12 Yili Wang, Jiamin Chen, Qiutong Li, Changlong He, Jianliang Gao
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Adaptive semi-supervised learning from stronger augmentation transformations of discrete text information Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-11 Xuemiao Zhang, Zhouxing Tan, Fengyu Lu, Rui Yan, Junfei Liu
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Deep graph clustering via mutual information maximization and mixture model Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-10 Maedeh Ahmadi, Mehran Safayani, Abdolreza Mirzaei
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Enhancing Multi-Attribute Similarity Join using Reduced and Adaptive Index Trees Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-09 Vítor Bezerra Silva, Dimas Cassimiro Nascimento
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Enhancing knowledge discovery and management through intelligent computing methods: a decisive investigation Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-09 Rayees Ahamad, Kamta Nath Mishra
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A Rényi-type quasimetric with random interference detection Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-09 Roy Cerqueti, Mario Maggi
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Noise-free sampling with majority framework for an imbalanced classification problem Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-09 Neni Alya Firdausanti, Israel Mendonça, Masayoshi Aritsugi
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Efficient parameter learning for Bayesian Network classifiers following the Apache Spark Dataframes paradigm Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-08 Ioannis Akarepis, Agorakis Bompotas, Christos Makris
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Dynamic bipartite network model based on structure and preference features Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-06 Hehe Lv, Guobing Zou, Bofeng Zhang, Shengxiang Hu, Chenyang Zhou, Liangrui Wu
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Entity linking for English and other languages: a survey Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-02
Abstract Extracting named entities text forms the basis for many crucial tasks such as information retrieval and extraction, machine translation, opinion mining, sentiment analysis and question answering. This paper presents a survey of the research literature on named entity linking, including named entity recognition and disambiguation. We present 200 works by focusing on 43 papers (5 surveys and
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Local soft rough approximations and their applications to conflict analysis problems Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-04-01 Moin Akhter Ansari, Noor Rehman, Abbas Ali, Kostaq Hila, Tahira Mubeen
Local rough sets are an efficient model to analyze large-scale datasets with finite labels because they are an essential development in classical rough sets. The objective of this paper, we put forth the idea of a local soft rough approximation measure (LSRAM), which preserves rough approximation measure associated characteristics from the context of traditional rough set theory. In order to account
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Influential users identification under the non-progressive LTIRS model Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-28
Abstract Identification of the key influencers is one of the most important strategies for initiating any transmission process in a social network. However, many of the current studies on influence transmission concentrate primarily on the progressive dissemination phenomenon. Furthermore, the various methods for selecting key influencers that are being explored so far either depend on the structure
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MMUIL: enhancing multi-platform user identity linkage with multi-information Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-28 Qian Zhou, Yihan Hei, Wei Chen, Shangfei Zheng, Lei Zhao
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A quality-of-service aware composition-method for cloud service using discretized ant lion optimization algorithm Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-28 Bahman Arasteh, Babak Aghaei, Asgarali Bouyer, Keyvan Arasteh
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Evaluating the effectiveness of machine learning models for performance forecasting in basketball: a comparative study Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-24
Abstract Sports analytics (SA) incorporate machine learning (ML) techniques and models for performance prediction. Researchers have previously evaluated ML models applied on a variety of basketball statistics. This paper aims to benchmark the forecasting performance of 14 ML models, based on 18 advanced basketball statistics and key performance indicators (KPIs). The models were applied on a filtered
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Unifying Faceted Search and Analytics over RDF Knowledge Graphs Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-24 Maria-Evangelia Papadaki, Yannis Tzitzikas
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Multi-factor stock price prediction based on GAN-TrellisNet Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-22
Abstract Applying deep learning, especially time series neural networks, to predict stock price, has become one of the important applications in quantitative finance. Recently, some GAN-based stock prediction models are proposed, where LSTM or GRU is used as the generator. However, these generators lack the function of feature extraction, and the prediction accuracies are slightly low. Meanwhile, these
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GTHP: a novel graph transformer Hawkes process for spatiotemporal event prediction Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-19
Abstract The event sequences with spatiotemporal characteristics have been rapidly produced in various domains, such as earthquakes in seismology, electronic medical records in healthcare, and transactions in the financial market. These data often continue for weeks, months, or years, and the past events may trigger subsequent events. In this context, modeling the spatiotemporal event sequences and
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Exploring the potential of deep regression model for next-location prediction Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-18 Pushpak Shukla, Shailendra Shukla
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A deep learning-based disease diagnosis with intrusion detection for a secured healthcare system Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-15 S. K. Rajesh Kanna, Mantripragada Yaswanth Bhanu Murthy, Mahendra Bhatu Gawali, Saleh Muhammad Rubai, N. Srikanth Reddy, G. Brammya, N. S. Ninu Preetha
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A semantic-based methodology for the management of document workflows in e-government: a case study for judicial processes Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-14 Beniamino Di Martino, Luigi Colucci Cante, Mariangela Graziano, Salvatore D’Angelo, Antonio Esposito, Pietro Lupi, Rosario Ammendolia
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Argumentation effect of a chatbot for ethical discussions about autonomous AI scenarios Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-13 Christian Hauptmann, Adrian Krenzer, Justin Völkel, Frank Puppe
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Cost-sensitive learning using logical analysis of data Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-10
Abstract Classification is a common task in data mining that assigns a class label to an unseen situation. It has been widely used in decision making for various applications, and many machine learning algorithms have been developed to accomplish this task. Classification becomes critical when the problem under concern is related to serious situations such as fraud detection, cancer diseases, and quality
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Layer imbalance-aware multiplex network embedding Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-05 Ke-Jia Chen, Yinchu Qiu, Zheng Liu, Wenhui Mu
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Multi-behavior-based graph contrastive learning recommendation Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-05 Chenzhong Bin, Weiliang Li, Fangjian Wu, Liang Chang, Yimin Wen
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Explaining deep multi-class time series classifiers Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-04 Ramesh Doddaiah, Prathyush S. Parvatharaju, Elke Rundensteiner, Thomas Hartvigsen
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Framework for scoring the scientific reputation of researchers Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-02 Isaac Martín de Diego, Juan Carlos Prieto, Alberto Fernández-Isabel, Javier Gomez, César Alfaro
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SimGCL: graph contrastive learning by finding homophily in heterophily Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-01 Cheng Liu, Chenhuan Yu, Ning Gui, Zhiwu Yu, Songgaojun Deng
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SABeDM: a sliding adaptive beta distribution model for concept drift detection in a dynamic environment Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-01 Ature Angbera, Huah Yong Chan
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Neighborhood rough set with neighborhood equivalence relation for feature selection Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-01 Shangzhi Wu, Litai Wang, Shuyue Ge, Zhengwei Hao, Yulin Liu
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How to manage massive spatiotemporal dataset from stationary and non-stationary sensors in commercial DBMS? Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-01 Vincenzo Norman Vitale, Sergio Di Martino, Adriano Peron, Massimiliano Russo, Ermanno Battista
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BiMuF: a bi-directional recommender system with multi-semantic filter for online recruitment Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-03-01 Pei-Yuan Lai, Zhe-Rui Yang, Qing-Yun Dai, De-Zhang Liao, Chang-Dong Wang
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Multi-representation web service recommendation system based on attention mechanism Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-02-05
Abstract Recently, mashup developers seek to integrate multiple services with complementary functionalities from a large amount of web services. With so many available web services, it is difficult for developers to choose the right one to develop new mashups. Therefore, it is critical to create and recommend appropriate web services for mashup developers based on their development needs. In the past
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Enumerating all multi-constrained s–t paths on temporal graph Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-02-01 Yue Jin, Zijun Chen, Wenyuan Liu
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SS-WDRN: sparrow search optimization-based weighted dual recurrent network for software fault prediction Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-02-01 J. Brundha Elci, S. Nandagopalan
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Microaneurysms detection in fundus images using local Fourier transform and neighbourhood analysis Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-02-01 T. Sudarson Rama Perumal, A. Jayachandran, S. Ratheesh Kumar
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Online influence maximization under continuous independent cascade model with node-edge-level feedback Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-02-01 Chao Liu, Haichao Xu, Xiaoyang Liu
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Mixed membership distribution-free model Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-02-01 Huan Qing, Jingli Wang
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A systematic literature review on the application of process mining to Industry 4.0 Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-01-16 Katsiaryna Akhramovich, Estefanía Serral, Carlos Cetina
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An automated approach for binary classification on imbalanced data Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-01-12 Pedro Marques Vieira, Fátima Rodrigues
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Simple knowledge graph completion model based on PU learning and prompt learning Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-01-12
Abstract Knowledge graphs (KGs) are important resources for many artificial intelligence tasks but usually suffer from incompleteness, which has prompted scholars to put forward the task of knowledge graph completion (KGC). Embedding-based methods, which use the structural information of the KG for inference completion, are mainstream for this task. But these methods cannot complete the inference for
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-01-11 Donghui Shi, Zhigang Li, Jozef Zurada, Andrew Manikas, Jian Guan, Pawel Weichbroth
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A label propagation community discovery algorithm combining seed node influence and neighborhood similarity Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-01-10 Miaomiao Liu, Jinyun Yang, Jingfeng Guo, Jing Chen
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An efficient automatic modulation recognition using time–frequency information based on hybrid deep learning and bagging approach Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-01-09
Abstract Determining the type of modulation is an important task in military communications, satellite communications systems, and submarine communications. In this study, a new digital modulation classification model is presented for detecting various types of modulated signals. The continuous wavelet transform is used in the first step to create a visual representation of the spectral density of
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On-grid and off-grid photovoltaic systems forecasting using a hybrid meta-learning method Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-01-09 Simona-Vasilica Oprea, Adela Bâra
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Logical assessment formula and its principles for evaluations with inaccurate ground-truth labels Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-01-06 Yongquan Yang
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Optimized neural attention mechanism for aspect-based sentiment analysis framework with optimal polarity-based weighted features Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-01-02
Abstract In recent years, sentimental analysis has been broadly investigated to extract information to identify whether it is positive, negative or neutral. Sentimental analysis can be broadly performed in social media content, survey response and review. Still, it faces issues while detecting and analyzing social media content. Moreover, a social media network contains indirect sentiments and natural
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A configurable mining approach for enhancing the business processes' performance Knowl. Inf. Syst. (IF 2.7) Pub Date : 2024-01-02 Noha Ahmed Bayomy, Ayman E. Khedr, Laila A. Abd-Elmegid
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A smart intelligent approach based on hybrid group search and pelican optimization algorithm for data stream clustering Knowl. Inf. Syst. (IF 2.7) Pub Date : 2023-12-30 Swathi Agarwal, C. R. K. Reddy
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Improving stock trend prediction with pretrain multi-granularity denoising contrastive learning Knowl. Inf. Syst. (IF 2.7) Pub Date : 2023-12-28 Mingjie Wang, Siyuan Wang, Jianxiong Guo, Weijia Jia
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A unified framework for backpropagation-free soft and hard gated graph neural networks Knowl. Inf. Syst. (IF 2.7) Pub Date : 2023-12-26 Luca Pasa, Nicolò Navarin, Wolfgang Erb, Alessandro Sperduti
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Optimal online time-series segmentation Knowl. Inf. Syst. (IF 2.7) Pub Date : 2023-12-26
Abstract When time series are processed, the difficulty increases with the size of the series. This fact is aggravated when time series are processed online, since their size increases indefinitely. Therefore, reducing their number of points, without significant loss of information, is an important field of research. This article proposes an optimal online segmentation method, called OSFS-OnL, which
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Online active learning method for multi-class imbalanced data stream Knowl. Inf. Syst. (IF 2.7) Pub Date : 2023-12-23 Ang Li, Meng Han, Dongliang Mu, Zhihui Gao, Shujuan Liu
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Node and edge dual-masked self-supervised graph representation Knowl. Inf. Syst. (IF 2.7) Pub Date : 2023-12-23 Peng Tang, Cheng Xie, Haoran Duan
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Integrating semantic similarity with Dirichlet multinomial mixture model for enhanced web service clustering Knowl. Inf. Syst. (IF 2.7) Pub Date : 2023-12-22
Abstract With accelerated advancement of web 2.0, developers generally describe the functionality of services in short natural text. Keyword-based searching techniques are not an efficient way of discovering services from repositories. It suffers from vocabulary problems. Latent Dirichlet allocation (LDA) with word embedding techniques is widely adopted for efficiently extracting latent features from