Int. J. Web Inf. Syst.最新文献

{"title":"Output regeneration defense against membership inference attacks for protecting data privacy","authors":"Yong Ding, Peixiong Huang, Hai Liang, Fang Yuan, Huiyong Wang","doi":"10.1108/ijwis-03-2023-0050","DOIUrl":"https://doi.org/10.1108/ijwis-03-2023-0050","url":null,"abstract":"\u0000Purpose\u0000Recently, deep learning (DL) has been widely applied in various aspects of human endeavors. However, studies have shown that DL models may also be a primary cause of data leakage, which raises new data privacy concerns. Membership inference attacks (MIAs) are prominent threats to user privacy from DL model training data, as attackers investigate whether specific data samples exist in the training data of a target model. Therefore, the aim of this study is to develop a method for defending against MIAs and protecting data privacy.\u0000\u0000\u0000Design/methodology/approach\u0000One possible solution is to propose an MIA defense method that involves adjusting the model’s output by mapping the output to a distribution with equal probability density. This approach effectively preserves the accuracy of classification predictions while simultaneously preventing attackers from identifying the training data.\u0000\u0000\u0000Findings\u0000Experiments demonstrate that the proposed defense method is effective in reducing the classification accuracy of MIAs to below 50%. Because MIAs are viewed as a binary classification model, the proposed method effectively prevents privacy leakage and improves data privacy protection.\u0000\u0000\u0000Research limitations/implications\u0000The method is only designed to defend against MIA in black-box classification models.\u0000\u0000\u0000Originality/value\u0000The proposed MIA defense method is effective and has a low cost. Therefore, the method enables us to protect data privacy without incurring significant additional expenses.\u0000","PeriodicalId":295184,"journal":{"name":"Int. J. Web Inf. Syst.","volume":"57 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126141103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"STCGCN: a spatio-temporal complete graph convolutional network for remaining useful life prediction of power transformer","authors":"Mengda Xing, Weilong Ding, Tianpu Zhang, Hantang Li","doi":"10.1108/ijwis-02-2023-0023","DOIUrl":"https://doi.org/10.1108/ijwis-02-2023-0023","url":null,"abstract":"\u0000Purpose\u0000Remaining useful life (RUL) prediction for power transformer maintenance is a challenging task on heterogeneous data. Monitoring data of power transformers are not always compatible or in an identical format; therefore, RUL predictions traditionally work separately on different data. Moreover, chemical molecules used in RUL prediction can be transformed into each other under different conditions, thus forming a complete graph with uncertain adjacency matrix (UAM). This study aims to find and evaluate a new model to achieve better results of RUL prediction than the other baselines.\u0000\u0000\u0000Design/methodology/approach\u0000In this work, the authors propose a spatiotemporal complete graph convolutional network (STCGCN) for RUL prediction in two branches, in which daily and hourly features are extracted from correlated heterogeneous data separately. This study provides a thorough evaluation of the proposed model on real-world data and compare the proposed model with state-of-the-art RUL prediction models.\u0000\u0000\u0000Findings\u0000By using the multibranch structure and EucCos similarity aggregation, STCGCN was able to capture the dynamic spatiotemporal patterns on a variety of heterogeneous data and obtain more accurate prediction results, compared to other time series prediction methods.\u0000\u0000\u0000Originality/value\u0000In this work, the authors propose a novel multibranch structure to compute feature maps from two heterogeneous data sources efficiently and a novel similarity aggregation method to compute the spatial UAM within the complete graph. Compared with traditional time series prediction models, the model pays attention to the spatial relationships in time series data.\u0000","PeriodicalId":295184,"journal":{"name":"Int. J. Web Inf. Syst.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115342837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating user behavior flow for user risk assessment","authors":"Yuxiang Shan, Qin Ren, Gang Yu, Tiantian Li, Bin Cao","doi":"10.1108/ijwis-02-2023-0025","DOIUrl":"https://doi.org/10.1108/ijwis-02-2023-0025","url":null,"abstract":"\u0000Purpose\u0000Internet marketing underground industry users refer to people who use technology means to simulate a large number of real consumer behaviors to obtain marketing activities rewards illegally, which leads to increased cost of enterprises and reduced effect of marketing. Therefore, this paper aims to construct a user risk assessment model to identify potential underground industry users to protect the interests of real consumers and reduce the marketing costs of enterprises.\u0000\u0000\u0000Design/methodology/approach\u0000Method feature extraction is based on two aspects. The first aspect is based on traditional statistical characteristics, using density-based spatial clustering of applications with noise clustering method to obtain user-dense regions. According to the total number of users in the region, the corresponding risk level of the receiving address is assigned. So that high-quality address information can be extracted. The second aspect is based on the time period during which users participate in activities, using frequent item set mining to find multiple users with similar operations within the same time period. Extract the behavior flow chart according to the user participation, so that the model can mine the deep relationship between the participating behavior and the underground industry users.\u0000\u0000\u0000Findings\u0000Based on the real underground industry user data set, the features of the data set are extracted by the proposed method. The features are experimentally verified by different models such as random forest, fully-connected layer network, SVM and XGBOST, and the proposed method is comprehensively evaluated. Experimental results show that in the best case, our method can improve the F1-score of traditional models by 55.37%.\u0000\u0000\u0000Originality/value\u0000This paper investigates the relative importance of static information and dynamic behavior characteristics of users in predicting underground industry users, and whether the absence of features of these categories affects the prediction results. This investigation can go a long way in aiding further research on this subject and found the features which improved the accuracy of predicting underground industry users.\u0000","PeriodicalId":295184,"journal":{"name":"Int. J. Web Inf. Syst.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125427884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Chinese nested named entity recognition approach using sequence labeling","authors":"Maojian Chen, Xiong Luo, H. Shen, Ziyang Huang, Qiaojuan Peng, Yuqi Yuan","doi":"10.1108/ijwis-04-2023-0070","DOIUrl":"https://doi.org/10.1108/ijwis-04-2023-0070","url":null,"abstract":"\u0000Purpose\u0000This study aims to introduce an innovative approach that uses a decoder with multiple layers to accurately identify Chinese nested entities across various nesting depths. To address potential human intervention, an advanced optimization algorithm is used to fine-tune the decoder based on the depth of nested entities present in the data set. With this approach, this study achieves remarkable performance in recognizing Chinese nested entities.\u0000\u0000\u0000Design/methodology/approach\u0000This study provides a framework for Chinese nested named entity recognition (NER) based on sequence labeling methods. Similar to existing approaches, the framework uses an advanced pre-training model as the backbone to extract semantic features from the text. Then a decoder comprising multiple conditional random field (CRF) algorithms is used to learn the associations between granularity labels. To minimize the need for manual intervention, the Jaya algorithm is used to optimize the number of CRF layers. Experimental results validate the effectiveness of the proposed approach, demonstrating its superior performance on both Chinese nested NER and flat NER tasks.\u0000\u0000\u0000Findings\u0000The experimental findings illustrate that the proposed methodology can achieve a remarkable 4.32% advancement in nested NER performance on the People’s Daily corpus compared to existing models.\u0000\u0000\u0000Originality/value\u0000This study explores a Chinese NER methodology based on the sequence labeling ideology for recognizing sophisticated Chinese nested entities with remarkable accuracy.\u0000","PeriodicalId":295184,"journal":{"name":"Int. J. Web Inf. Syst.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121740555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced weighted hybridized approach for recommendation system","authors":"Debajyoty Banik, S. Satapathy, Mansheel Agarwal","doi":"10.1108/ijwis-01-2022-0006","DOIUrl":"https://doi.org/10.1108/ijwis-01-2022-0006","url":null,"abstract":"\u0000Purpose\u0000This paper aims to describe the usage of a hybrid weightage-based recommender system focused on books and implementing it at an industrial level, using various recommendation approaches. Additionally, it focuses on integrating the model into the most widely used platform application.\u0000\u0000\u0000Design/methodology/approach\u0000It is an industrial level implementation of a recommendation system by applying different recommendation approaches. This study describes the usage of a hybrid weightage-based recommender system focused on books and putting a model into the most used platform application.\u0000\u0000\u0000Findings\u0000This paper deals with the phases of software engineering from the analysis of the requirements, the actual making of the recommender model to deployment and testing of the application at the user end. Finally, the hybridized system outperforms over other existing recommender system.\u0000\u0000\u0000Originality/value\u0000The proposed recommendation system is an industrial level implementation of a recommendation system by applying different recommendation approaches. The recommendation system is centralized to books and its recommendation. In this paper, the authors also describe the usage of a hybrid weightage-based recommender system focused on books and putting a model into the most used platform application. This paper deals with the phases of software engineering from the analysis of the requirements, the actual making of the recommender model to deployment and testing of the application at the user end. Finally, the newly created hybridized system outperforms the Netflix recommendation model as well as the Hybrid book recommendation system model as has been clearly shown in the Results Analysis section of the book. The source-code can be available at https://github.com/debajyoty/recomender-system.git.\u0000","PeriodicalId":295184,"journal":{"name":"Int. J. Web Inf. Syst.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122492610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient keyword search on graph data for finding diverse and relevant answers","authors":"Chang-Sup Park","doi":"10.1108/ijwis-09-2022-0157","DOIUrl":"https://doi.org/10.1108/ijwis-09-2022-0157","url":null,"abstract":"\u0000Purpose\u0000This paper studies a keyword search over graph-structured data used in various fields such as semantic web, linked open data and social networks. This study aims to propose an efficient keyword search algorithm on graph data to find top-k answers that are most relevant to the query and have diverse content nodes for the input keywords.\u0000\u0000\u0000Design/methodology/approach\u0000Based on an aggregative measure of diversity of an answer set, this study proposes an approach to searching the top-k diverse answers to a query on graph data, which finds a set of most relevant answer trees whose average dissimilarity should be no lower than a given threshold. This study defines a diversity constraint that must be satisfied for a subset of answer trees to be included in the solution. Then, an enumeration algorithm and a heuristic search algorithm are proposed to find an optimal solution efficiently based on the diversity constraint and an A* heuristic. This study also provides strategies for improving the performance of the heuristic search method.\u0000\u0000\u0000Findings\u0000The results of experiments using a real data set demonstrate that the proposed search algorithm can find top-k diverse and relevant answers to a query on large-scale graph data efficiently and outperforms the previous methods.\u0000\u0000\u0000Originality/value\u0000This study proposes a new keyword search method for graph data that finds an optimal solution with diverse and relevant answers to the query. It can provide users with query results that satisfy their various information needs on large graph data.\u0000","PeriodicalId":295184,"journal":{"name":"Int. J. Web Inf. Syst.","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116208291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guest editorial: Special issue on \"current topics of knowledge graphs and semantic web\"","authors":"S. Tiwari, Fernando Ortiz-Rodríguez, B. Villazón-Terrazas","doi":"10.1108/ijwis-12-2022-142","DOIUrl":"https://doi.org/10.1108/ijwis-12-2022-142","url":null,"abstract":"","PeriodicalId":295184,"journal":{"name":"Int. J. Web Inf. Syst.","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122444868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applied personal profile ontology for personnel appraisals","authors":"P. U. Usip, E. Udo, I. Umoeka","doi":"10.1108/ijwis-03-2022-0048","DOIUrl":"https://doi.org/10.1108/ijwis-03-2022-0048","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to apply the earlier enhanced personal profile ontology (e-PPO) developed by the authors as a case study for the appraisal of the lecturers in the department of computer science, University of Uyo, Uyo for the purposes of promotions. The developed e-PPO was a sample smart résumé for the selection of the best among three personnel using linguistic variables and formal rules representing the combination of the criteria and subcriteria was illustrated which was used to allocate competent personnel for software requirement engineering tasks. The need for the use of the smart resume for appraisal purposes was pointed out in the conference paper, calling for the applicant’s data to be inputted into the enhanced personal profile ontology (e-PPO) for personnel appraisa.\u0000\u0000\u0000Design/methodology/approach\u0000Appraisal is a regular review of employees’ performances and their overall contribution to the organization they are working for. The availability of a web application for personnel appraisal requires PPO which includes both static and dynamic features. Personal profile is often modified for several purposes calling for augmentation and annotation when needs arise. Resume is one resulting extract from personal profile and often contain slightly different information based on needs. The urgent preparation of resume may introduce bias and incorrect information for the sole aim of projecting the personnel as being qualified for the available job. Religious and gender biases may sometimes be observed during appointments of new personnel, which may not be the case during appraisals for promotions or reassignment of tasks because such biases become insignificant given the fact that job targets and the skills needed are already set and the appraisals passes through several phases that are not determined by a single individual. This work therefore applied the earlier developed e-PPO for appraisal of the academic staff of the department of computer science, university of Uyo, Uyo, Nigeria. A mixed approach of existing ontologies like Methontology and Neon have been followed in the creation of the e-PPO, which is a constraint-based semantic data model tested using Protégé inbuilt reasoner with its updated plugins. Upon application of e-PPO on personnel appraisals, promotion and selection of employee for specific assignments in any organization is possible using the smart resume.\u0000\u0000\u0000Findings\u0000The use of the smart resume reduces the numerous task that would have been taken up by the human resource team, thereby reducing the processing time for the appraisals. The appraisal task is done void of biases of any kind such as gender and religion.\u0000\u0000\u0000Originality/value\u0000This work is an extension of the original work done by the authors.\u0000","PeriodicalId":295184,"journal":{"name":"Int. J. Web Inf. Syst.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129340046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Keyword-based faceted search interface for knowledge graph construction and exploration","authors":"Samir Sellami, N. Zarour","doi":"10.1108/ijwis-02-2022-0037","DOIUrl":"https://doi.org/10.1108/ijwis-02-2022-0037","url":null,"abstract":"Purpose\u0000Massive amounts of data, manifesting in various forms, are being produced on the Web every minute and becoming the new standard. Exploring these information sources distributed in different Web segments in a unified way is becoming a core task for a variety of users’ and companies’ scenarios. However, knowledge creation and exploration from distributed Web data sources is a challenging task. Several data integration conflicts need to be resolved and the knowledge needs to be visualized in an intuitive manner. The purpose of this paper is to extend the authors’ previous integration works to address semantic knowledge exploration of enterprise data combined with heterogeneous social and linked Web data sources.\u0000\u0000\u0000Design/methodology/approach\u0000The authors synthesize information in the form of a knowledge graph to resolve interoperability conflicts at integration time. They begin by describing KGMap, a mapping model for leveraging knowledge graphs to bridge heterogeneous relational, social and linked web data sources. The mapping model relies on semantic similarity measures to connect the knowledge graph schema with the sources' metadata elements. Then, based on KGMap, this paper proposes KeyFSI, a keyword-based semantic search engine. KeyFSI provides a responsive faceted navigating Web user interface designed to facilitate the exploration and visualization of embedded data behind the knowledge graph. The authors implemented their approach for a business enterprise data exploration scenario where inputs are retrieved on the fly from a local customer relationship management database combined with the DBpedia endpoint and the Facebook Web application programming interface (API).\u0000\u0000\u0000Findings\u0000The authors conducted an empirical study to test the effectiveness of their approach using different similarity measures. The observed results showed better efficiency when using a semantic similarity measure. In addition, a usability evaluation was conducted to compare KeyFSI features with recent knowledge exploration systems. The obtained results demonstrate the added value and usability of the contributed approach.\u0000\u0000\u0000Originality/value\u0000Most state-of-the-art interfaces allow users to browse one Web segment at a time. The originality of this paper lies in proposing a cost-effective virtual on-demand knowledge creation approach, a method that enables organizations to explore valuable knowledge across multiple Web segments simultaneously. In addition, the responsive components implemented in KeyFSI allow the interface to adequately handle the uncertainty imposed by the nature of Web information, thereby providing a better user experience.","PeriodicalId":295184,"journal":{"name":"Int. J. Web Inf. Syst.","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132726112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semiautomated process for generating knowledge graphs for marginalized community doctoral-recipients","authors":"N. Keshan, K. Fontaine, J. Hendler","doi":"10.1108/ijwis-02-2022-0046","DOIUrl":"https://doi.org/10.1108/ijwis-02-2022-0046","url":null,"abstract":"\u0000Purpose\u0000This paper aims to describe the “InDO: Institute Demographic Ontology” and demonstrates the InDO-based semiautomated process for both generating and extending a knowledge graph to provide a comprehensive resource for marginalized US graduate students. The knowledge graph currently consists of instances related to the semistructured National Science Foundation Survey of Earned Doctorates (NSF SED) 2019 analysis report data tables. These tables contain summary statistics of an institute’s doctoral recipients based on a variety of demographics. Incorporating institute Wikidata links ultimately produces a table of unique, clearly readable data.\u0000\u0000\u0000Design/methodology/approach\u0000The authors use a customized semantic extract transform and loader (SETLr) script to ingest data from 2019 US doctoral-granting institute tables and preprocessed NSF SED Tables 1, 3, 4 and 9. The generated InDO knowledge graph is evaluated using two methods. First, the authors compare competency questions’ sparql results from both the semiautomatically and manually generated graphs. Second, the authors expand the questions to provide a better picture of an institute’s doctoral-recipient demographics within study fields.\u0000\u0000\u0000Findings\u0000With some preprocessing and restructuring of the NSF SED highly interlinked tables into a more parsable format, one can build the required knowledge graph using a semiautomated process.\u0000\u0000\u0000Originality/value\u0000The InDO knowledge graph allows the integration of US doctoral-granting institutes demographic data based on NSF SED data tables and presentation in machine-readable form using a new semiautomated methodology.\u0000","PeriodicalId":295184,"journal":{"name":"Int. J. Web Inf. Syst.","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134193980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}