Pub Date : 2023-05-01DOI: 10.1007/s10844-023-00777-1
Andrea Chiorrini, C. Diamantini, Laura Genga, D. Potena
{"title":"Multi-perspective enriched instance graphs for next activity prediction through graph neural network","authors":"Andrea Chiorrini, C. Diamantini, Laura Genga, D. Potena","doi":"10.1007/s10844-023-00777-1","DOIUrl":"https://doi.org/10.1007/s10844-023-00777-1","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":"1 1","pages":"1-21"},"PeriodicalIF":3.4,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86277805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-29DOI: 10.1007/s10844-023-00787-z
Marcos Zampieri, Tharindu Ranasinghe, Diptanu Sarkar, Alex Ororbia
{"title":"Offensive language identification with multi-task learning","authors":"Marcos Zampieri, Tharindu Ranasinghe, Diptanu Sarkar, Alex Ororbia","doi":"10.1007/s10844-023-00787-z","DOIUrl":"https://doi.org/10.1007/s10844-023-00787-z","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":"36 1","pages":"1-18"},"PeriodicalIF":3.4,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88357018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-30DOI: 10.1007/s10844-023-00780-6
Ruizhe Ma, Xiao Han, Li Yan, Nasrullah Khan, Z. Ma
{"title":"Modeling and querying temporal RDF knowledge graphs with relational databases","authors":"Ruizhe Ma, Xiao Han, Li Yan, Nasrullah Khan, Z. Ma","doi":"10.1007/s10844-023-00780-6","DOIUrl":"https://doi.org/10.1007/s10844-023-00780-6","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":"8 1","pages":"1-41"},"PeriodicalIF":3.4,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84150310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-18DOI: 10.1007/s10844-023-00782-4
Filippo Lorè, Pierpaolo Basile, A. Appice, Marco de Gemmis, D. Malerba, G. Semeraro
{"title":"An AI framework to support decisions on GDPR compliance","authors":"Filippo Lorè, Pierpaolo Basile, A. Appice, Marco de Gemmis, D. Malerba, G. Semeraro","doi":"10.1007/s10844-023-00782-4","DOIUrl":"https://doi.org/10.1007/s10844-023-00782-4","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":"60 1","pages":"1-28"},"PeriodicalIF":3.4,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86616536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-06DOI: 10.1007/s10844-022-00775-9
Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park, Marco Pegoraro, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Abstract Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances. Such predictions are of significant interest to the process stakeholders. However, most of the state-of-the-art methods for predictive monitoring require the training of complex machine learning models, which is often inefficient. Moreover, most of these methods require a hyper-parameter optimization that requires several repetitions of the training process which is not feasible in many real-life applications. In this paper, we propose an instance selection procedure that allows sampling training process instances for prediction models. We show that our instance selection procedure allows for a significant increase of training speed for next activity and remaining time prediction methods while maintaining reliable levels of prediction accuracy.
{"title":"Performance-preserving event log sampling for predictive monitoring","authors":"Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park, Marco Pegoraro, Sebastiaan J. van Zelst, Wil M. P. van der Aalst","doi":"10.1007/s10844-022-00775-9","DOIUrl":"https://doi.org/10.1007/s10844-022-00775-9","url":null,"abstract":"Abstract Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances. Such predictions are of significant interest to the process stakeholders. However, most of the state-of-the-art methods for predictive monitoring require the training of complex machine learning models, which is often inefficient. Moreover, most of these methods require a hyper-parameter optimization that requires several repetitions of the training process which is not feasible in many real-life applications. In this paper, we propose an instance selection procedure that allows sampling training process instances for prediction models. We show that our instance selection procedure allows for a significant increase of training speed for next activity and remaining time prediction methods while maintaining reliable levels of prediction accuracy.","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135001685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-22DOI: 10.1007/s10844-023-00779-z
Marco Casavantes, Mario Ezra Aragón, Luis C. González, M. Montes-y-Gómez
{"title":"Leveraging posts’ and authors’ metadata to spot several forms of abusive comments in Twitter","authors":"Marco Casavantes, Mario Ezra Aragón, Luis C. González, M. Montes-y-Gómez","doi":"10.1007/s10844-023-00779-z","DOIUrl":"https://doi.org/10.1007/s10844-023-00779-z","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":"42 1","pages":"1-21"},"PeriodicalIF":3.4,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81032325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Over the last couple of decades, Social Networks have connected people on the web from across the globe and have become a crucial part of our daily life. These networks have also rapidly grown as platforms for propagating products, ideas, and opinions to target a wider audience. This calls for the need to find influential nodes in a network for a variety of reasons, including the curb of misinformation being spread across the networks, advertising products efficiently, finding prominent protein structures in biological networks, etc. In this paper, we propose Modified Community Diversity (MCD), a novel method for finding influential nodes in a network by exploiting community detection and a modified community diversity approach. We extend the concept of community diversity to a two-hop scenario. This helps us evaluate a node’s possible influence over a network more accurately and also avoids the selection of seed nodes with an overlapping scope of influence. Experimental results verify that MCD outperforms various other state-of-the-art approaches on eight datasets cumulatively across three performance metrics.
在过去的几十年里，社交网络将世界各地的人们联系在一起，并成为我们日常生活中至关重要的一部分。这些网络也迅速发展成为宣传产品、思想和观点的平台，以瞄准更广泛的受众。这就需要在网络中找到有影响力的节点，原因有很多，包括抑制错误信息在网络中传播，有效地宣传产品，在生物网络中找到突出的蛋白质结构等。在本文中，我们提出了修正社区多样性(Modified Community Diversity, MCD)，这是一种利用社区检测和修正社区多样性方法来寻找网络中有影响节点的新方法。我们将社区多样性的概念扩展到两跳场景。这有助于我们更准确地评估节点对网络的可能影响，也避免了选择影响范围重叠的种子节点。实验结果证实，MCD在八个数据集上的三个性能指标累积优于其他各种最先进的方法。
{"title":"MCD: A modified community diversity approach for detecting influential nodes in social networks","authors":"Aaryan Gupta, Inder Khatri, Arjun Choudhry, Sanjay Kumar","doi":"10.1007/s10844-023-00776-2","DOIUrl":"https://doi.org/10.1007/s10844-023-00776-2","url":null,"abstract":"Over the last couple of decades, Social Networks have connected people on the web from across the globe and have become a crucial part of our daily life. These networks have also rapidly grown as platforms for propagating products, ideas, and opinions to target a wider audience. This calls for the need to find influential nodes in a network for a variety of reasons, including the curb of misinformation being spread across the networks, advertising products efficiently, finding prominent protein structures in biological networks, etc. In this paper, we propose Modified Community Diversity (MCD), a novel method for finding influential nodes in a network by exploiting community detection and a modified community diversity approach. We extend the concept of community diversity to a two-hop scenario. This helps us evaluate a node’s possible influence over a network more accurately and also avoids the selection of seed nodes with an overlapping scope of influence. Experimental results verify that MCD outperforms various other state-of-the-art approaches on eight datasets cumulatively across three performance metrics.","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135839835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-25DOI: 10.1007/s10844-022-00766-w
Lukas Malburg, Maximilian Hoffmann, R. Bergmann
{"title":"Applying MAPE-K control loops for adaptive workflow management in smart factories","authors":"Lukas Malburg, Maximilian Hoffmann, R. Bergmann","doi":"10.1007/s10844-022-00766-w","DOIUrl":"https://doi.org/10.1007/s10844-022-00766-w","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":"45 1","pages":"1-29"},"PeriodicalIF":3.4,"publicationDate":"2023-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74727354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-19DOI: 10.1007/s10844-022-00772-y
Guilherme Dal Bianco, Denio Duarte, Marcos André Gonçalves
{"title":"Reducing the user labeling effort in effective high recall tasks by fine-tuning active learning","authors":"Guilherme Dal Bianco, Denio Duarte, Marcos André Gonçalves","doi":"10.1007/s10844-022-00772-y","DOIUrl":"https://doi.org/10.1007/s10844-022-00772-y","url":null,"abstract":"","PeriodicalId":56119,"journal":{"name":"Journal of Intelligent Information Systems","volume":"20 1","pages":"1-20"},"PeriodicalIF":3.4,"publicationDate":"2023-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82437228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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