Pub Date : 2022-05-23DOI: 10.1108/dta-09-2021-0240
Caihua Yu, Tonghui Lian, Hongbao Geng, Sixin Li
PurposeThis paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into the features of tourist flow network structure and flow characteristics in Guilin of China.Design/methodology/approachThe digital footprint of tourists can be applied to study the behaviors and laws of digital footprint. This research contributes to improving the understanding of demand-driven network relationships among tourist attractions in a destination.Findings(1) Yulong River, Yangshuo West Street, Longji Terraced Fields, Silver Rock and Four Lakes are the divergent and agglomerative centers of tourist flow, which are the top tourist attractions for transiting tourists. (2) The core-periphery structure of the network is clearly stratified. More specifically, the core nodes in the network are prominent and the core area of the network has weak interaction with the peripheral area. (3) There are eight cohesive subgroups in the network structure, which contains certain differences in the radiation effects.Originality/valueThis research aims at exploring the spatial network structure characteristics of tourism flows in Guilin by analyzing the online footprints of tourists. It takes a good try to analyze the application of network footprint with the research of tourism flow characteristics, and also provides a theoretical reference for the design of tourist routes and the cooperative marketing among various attractions.
{"title":"Analyzing the structure of tourism destination network based on digital footprints: taking Guilin, China as a case","authors":"Caihua Yu, Tonghui Lian, Hongbao Geng, Sixin Li","doi":"10.1108/dta-09-2021-0240","DOIUrl":"https://doi.org/10.1108/dta-09-2021-0240","url":null,"abstract":"PurposeThis paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into the features of tourist flow network structure and flow characteristics in Guilin of China.Design/methodology/approachThe digital footprint of tourists can be applied to study the behaviors and laws of digital footprint. This research contributes to improving the understanding of demand-driven network relationships among tourist attractions in a destination.Findings(1) Yulong River, Yangshuo West Street, Longji Terraced Fields, Silver Rock and Four Lakes are the divergent and agglomerative centers of tourist flow, which are the top tourist attractions for transiting tourists. (2) The core-periphery structure of the network is clearly stratified. More specifically, the core nodes in the network are prominent and the core area of the network has weak interaction with the peripheral area. (3) There are eight cohesive subgroups in the network structure, which contains certain differences in the radiation effects.Originality/valueThis research aims at exploring the spatial network structure characteristics of tourism flows in Guilin by analyzing the online footprints of tourists. It takes a good try to analyze the application of network footprint with the research of tourism flow characteristics, and also provides a theoretical reference for the design of tourist routes and the cooperative marketing among various attractions.","PeriodicalId":56156,"journal":{"name":"Data Technologies and Applications","volume":"1 1","pages":"56-83"},"PeriodicalIF":1.6,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89735602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2022-05-04DOI: 10.1108/dta-02-2022-0083
Dhanya Pramod
PurposeThis study explores privacy challenges in recommender systems (RSs) and how they have leveraged privacy-preserving technology for risk mitigation. The study also elucidates the extent of adopting privacy-preserving RSs and postulates the future direction of research in RS security.Design/methodology/approachThe study gathered articles from well-known databases such as SCOPUS, Web of Science and Google scholar. A systematic literature review using PRISMA was carried out on the 41 papers that are shortlisted for study. Two research questions were framed to carry out the review.FindingsIt is evident from this study that privacy issues in the RS have been addressed with various techniques. However, many more challenges are expected while leveraging technology advancements for fine-tuning recommenders, and a research agenda has been devised by postulating future directions.Originality/valueThe study unveils a new comprehensive perspective regarding privacy preservation in recommenders. There is no promising study found that gathers techniques used for privacy protection. The study summarizes the research agenda, and it will be a good reference article for those who develop privacy-preserving RSs.
本研究探讨了推荐系统(RSs)中的隐私挑战，以及它们如何利用隐私保护技术来降低风险。该研究还阐明了采用隐私保护RSs的程度，并对RS安全的未来研究方向进行了展望。设计/方法/方法本研究从SCOPUS、Web of Science和Google scholar等知名数据库中收集文章。采用PRISMA对入选的41篇论文进行系统的文献综述。为了进行审查，我们提出了两个研究问题。从这项研究中可以明显看出，RS中的隐私问题已经通过各种技术得到了解决。然而，在利用技术进步进行微调推荐时，预计会遇到更多挑战，并且通过假设未来的方向设计了一个研究议程。独创性/价值该研究揭示了关于推荐人隐私保护的一个新的综合视角。没有一项有希望的研究发现收集了用于隐私保护的技术。该研究总结了研究议程，对于开发保护隐私RSs的人来说是一篇很好的参考文章。
{"title":"Privacy-preserving techniques in recommender systems: state-of-the-art review and future research agenda","authors":"Dhanya Pramod","doi":"10.1108/dta-02-2022-0083","DOIUrl":"https://doi.org/10.1108/dta-02-2022-0083","url":null,"abstract":"PurposeThis study explores privacy challenges in recommender systems (RSs) and how they have leveraged privacy-preserving technology for risk mitigation. The study also elucidates the extent of adopting privacy-preserving RSs and postulates the future direction of research in RS security.Design/methodology/approachThe study gathered articles from well-known databases such as SCOPUS, Web of Science and Google scholar. A systematic literature review using PRISMA was carried out on the 41 papers that are shortlisted for study. Two research questions were framed to carry out the review.FindingsIt is evident from this study that privacy issues in the RS have been addressed with various techniques. However, many more challenges are expected while leveraging technology advancements for fine-tuning recommenders, and a research agenda has been devised by postulating future directions.Originality/valueThe study unveils a new comprehensive perspective regarding privacy preservation in recommenders. There is no promising study found that gathers techniques used for privacy protection. The study summarizes the research agenda, and it will be a good reference article for those who develop privacy-preserving RSs.","PeriodicalId":56156,"journal":{"name":"Data Technologies and Applications","volume":"21 1","pages":"32-55"},"PeriodicalIF":1.6,"publicationDate":"2022-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87140677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2022-04-22DOI: 10.1108/dta-06-2021-0160
Heng-yang Lu, Jun Yang, Wei Fang, Xiaoning Song, Chongjun Wang
PurposeThe COVID-19 has become a global pandemic, which has caused large number of deaths and huge economic losses. These losses are not only caused by the virus but also by the related rumors. Nowadays, online social media are quite popular, where billions of people express their opinions and propagate information. Rumors about COVID-19 posted on online social media usually spread rapidly; it is hard to analyze and detect rumors only by artificial processing. The purpose of this paper is to propose a novel model called the Topic-Comment-based Rumor Detection model (TopCom) to detect rumors as soon as possible.Design/methodology/approachThe authors conducted COVID-19 rumor detection from Sina Weibo, one of the most widely used Chinese online social media. The authors constructed a dataset about COVID-19 from January 1 to June 30, 2020 with a web crawler, including both rumor and non-rumors. The rumor detection task is regarded as a binary classification problem. The proposed TopCom model exploits the topical memory networks to fuse latent topic information with original microblogs, which solves the sparsity problems brought by short-text microblogs. In addition, TopCom fuses comments with corresponding microblogs to further improve the performance.FindingsExperimental results on a publicly available dataset and the proposed COVID dataset have shown superiority and efficiency compared with baselines. The authors further randomly selected microblogs posted from July 1–31, 2020 for the case study, which also shows the effectiveness and application prospects for detecting rumors about COVID-19 automatically.Originality/valueThe originality of TopCom lies in the fusion of latent topic information of original microblogs and corresponding comments with DNNs-based models for the COVID-19 rumor detection task, whose value is to help detect rumors automatically in a short time.
{"title":"A deep neural networks-based fusion model for COVID-19 rumor detection from online social media","authors":"Heng-yang Lu, Jun Yang, Wei Fang, Xiaoning Song, Chongjun Wang","doi":"10.1108/dta-06-2021-0160","DOIUrl":"https://doi.org/10.1108/dta-06-2021-0160","url":null,"abstract":"PurposeThe COVID-19 has become a global pandemic, which has caused large number of deaths and huge economic losses. These losses are not only caused by the virus but also by the related rumors. Nowadays, online social media are quite popular, where billions of people express their opinions and propagate information. Rumors about COVID-19 posted on online social media usually spread rapidly; it is hard to analyze and detect rumors only by artificial processing. The purpose of this paper is to propose a novel model called the Topic-Comment-based Rumor Detection model (TopCom) to detect rumors as soon as possible.Design/methodology/approachThe authors conducted COVID-19 rumor detection from Sina Weibo, one of the most widely used Chinese online social media. The authors constructed a dataset about COVID-19 from January 1 to June 30, 2020 with a web crawler, including both rumor and non-rumors. The rumor detection task is regarded as a binary classification problem. The proposed TopCom model exploits the topical memory networks to fuse latent topic information with original microblogs, which solves the sparsity problems brought by short-text microblogs. In addition, TopCom fuses comments with corresponding microblogs to further improve the performance.FindingsExperimental results on a publicly available dataset and the proposed COVID dataset have shown superiority and efficiency compared with baselines. The authors further randomly selected microblogs posted from July 1–31, 2020 for the case study, which also shows the effectiveness and application prospects for detecting rumors about COVID-19 automatically.Originality/valueThe originality of TopCom lies in the fusion of latent topic information of original microblogs and corresponding comments with DNNs-based models for the COVID-19 rumor detection task, whose value is to help detect rumors automatically in a short time.","PeriodicalId":56156,"journal":{"name":"Data Technologies and Applications","volume":"60 1","pages":"806-824"},"PeriodicalIF":1.6,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74968915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2022-04-20DOI: 10.1108/dta-01-2022-0047
T. Banditwattanawong, A. Jankasem, Masawee Masdisornchote
PurposeFair grading produces learning ability levels that are understandable and acceptable to both learners and instructors. Norm-referenced grading can be achieved by several means such as z score, K-means and a heuristic. However, these methods typically deliver the varied degrees of grading fairness depending on input score data.Design/methodology/approachTo attain the fairest grading, this paper proposes a hybrid algorithm that integrates z score, K-means and heuristic methods with a novel fairness objective function as a decision function.FindingsDepending on an experimented data set, each of the algorithm's constituent methods could deliver the fairest grading results with fairness degrees ranging from 0.110 to 0.646. We also pointed out key factors in the fairness improvement of norm-referenced achievement grading.Originality/valueThe main contributions of this paper are four folds: the definition of fair norm-referenced grading requirements, a hybrid algorithm for fair norm-referenced grading, a fairness metric for norm-referenced grading and the fairness performance results of the statistical, heuristic and machine learning methods.
{"title":"Hybrid data analytic technique for grading fairness","authors":"T. Banditwattanawong, A. Jankasem, Masawee Masdisornchote","doi":"10.1108/dta-01-2022-0047","DOIUrl":"https://doi.org/10.1108/dta-01-2022-0047","url":null,"abstract":"PurposeFair grading produces learning ability levels that are understandable and acceptable to both learners and instructors. Norm-referenced grading can be achieved by several means such as z score, K-means and a heuristic. However, these methods typically deliver the varied degrees of grading fairness depending on input score data.Design/methodology/approachTo attain the fairest grading, this paper proposes a hybrid algorithm that integrates z score, K-means and heuristic methods with a novel fairness objective function as a decision function.FindingsDepending on an experimented data set, each of the algorithm's constituent methods could deliver the fairest grading results with fairness degrees ranging from 0.110 to 0.646. We also pointed out key factors in the fairness improvement of norm-referenced achievement grading.Originality/valueThe main contributions of this paper are four folds: the definition of fair norm-referenced grading requirements, a hybrid algorithm for fair norm-referenced grading, a fairness metric for norm-referenced grading and the fairness performance results of the statistical, heuristic and machine learning methods.","PeriodicalId":56156,"journal":{"name":"Data Technologies and Applications","volume":"34 1","pages":"18-31"},"PeriodicalIF":1.6,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83654519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2022-04-15DOI: 10.1108/dta-07-2021-0182
Rahul Shrivastava, Dilip Singh Sisodia, N. K. Nagwani
PurposeIn a multi-stakeholder recommender system (MSRS), stakeholders are the multiple entities (consumer, producer, system, etc.) benefited by the generated recommendations. Traditionally, the exclusive focus on only a single stakeholders' (for example, only consumer or end-user) preferences obscured the welfare of the others. Two major challenges are encountered while incorporating the multiple stakeholders' perspectives in MSRS: designing a dedicated utility function for each stakeholder and optimizing their utility without hurting others. This paper proposes multiple utility functions for different stakeholders and optimizes these functions for generating balanced, personalized recommendations for each stakeholder.Design/methodology/approachThe proposed methodology considers four valid stakeholders user, producer, cast and recommender system from the multi-stakeholder recommender setting and builds dedicated utility functions. The utility function for users incorporates enhanced side-information-based similarity computation for utility count. Similarly, to improve the utility gain, the authors design new utility functions for producer, star-cast and system to incorporate long-tail and diverse items in the recommendation list. Next, to balance the utility gain and generate the trade-off recommendation solution, the authors perform the evolutionary optimization of the conflicting utility functions using NSGA-II. Experimental evaluation and comparison are conducted over three benchmark data sets.FindingsThe authors observed 19.70% of average enhancement in utility gain with improved mean precision, diversity and novelty. Exposure, hit, reach and target reach metrics are substantially improved.Originality/valueA new approach considers four stakeholders simultaneously with their respective utility functions and establishes the trade-off recommendation solution between conflicting utilities of the stakeholders.
{"title":"Utility optimization-based multi-stakeholder personalized recommendation system","authors":"Rahul Shrivastava, Dilip Singh Sisodia, N. K. Nagwani","doi":"10.1108/dta-07-2021-0182","DOIUrl":"https://doi.org/10.1108/dta-07-2021-0182","url":null,"abstract":"PurposeIn a multi-stakeholder recommender system (MSRS), stakeholders are the multiple entities (consumer, producer, system, etc.) benefited by the generated recommendations. Traditionally, the exclusive focus on only a single stakeholders' (for example, only consumer or end-user) preferences obscured the welfare of the others. Two major challenges are encountered while incorporating the multiple stakeholders' perspectives in MSRS: designing a dedicated utility function for each stakeholder and optimizing their utility without hurting others. This paper proposes multiple utility functions for different stakeholders and optimizes these functions for generating balanced, personalized recommendations for each stakeholder.Design/methodology/approachThe proposed methodology considers four valid stakeholders user, producer, cast and recommender system from the multi-stakeholder recommender setting and builds dedicated utility functions. The utility function for users incorporates enhanced side-information-based similarity computation for utility count. Similarly, to improve the utility gain, the authors design new utility functions for producer, star-cast and system to incorporate long-tail and diverse items in the recommendation list. Next, to balance the utility gain and generate the trade-off recommendation solution, the authors perform the evolutionary optimization of the conflicting utility functions using NSGA-II. Experimental evaluation and comparison are conducted over three benchmark data sets.FindingsThe authors observed 19.70% of average enhancement in utility gain with improved mean precision, diversity and novelty. Exposure, hit, reach and target reach metrics are substantially improved.Originality/valueA new approach considers four stakeholders simultaneously with their respective utility functions and establishes the trade-off recommendation solution between conflicting utilities of the stakeholders.","PeriodicalId":56156,"journal":{"name":"Data Technologies and Applications","volume":"45 1","pages":"782-805"},"PeriodicalIF":1.6,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81241359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2022-04-13DOI: 10.1108/dta-08-2021-0205
Xiaofan Liu, Yupeng Zhou, Minghao Yin, Shuai Lv
PurposeThe paper aims to provide an efficient meta-heuristic algorithm to solve the partial set covering problem (PSCP). With rich application scenarios, the PSCP is a fascinating and well-known non-deterministic polynomial (NP)-hard problem whose goal is to cover at least k elements with as few subsets as possible.Design/methodology/approachIn this work, the authors present a novel variant of the ant colony optimization (ACO) algorithm, called Argentine ant system (AAS), to deal with the PSCP. The developed AAS is an integrated system of different populations that use the same pheromone to communicate. Moreover, an effective local search framework with the relaxed configuration checking (RCC) and the volatilization-fixed weight mechanism is proposed to improve the exploitation of the algorithm.FindingsA detailed experimental evaluation of 75 instances reveals that the proposed algorithm outperforms the competitors in terms of the quality of the optimal solutions. Also, the performance of AAS gradually improves with the growing instance size, which shows the potential in handling complex practical scenarios. Finally, the designed components of AAS are experimentally proved to be beneficial to the whole framework. Finally, the key components in AAS have been demonstrated.Originality/valueAt present, there is no heuristic method to solve this problem. The authors present the first implementation of heuristic algorithm for solving PSCP and provide competitive solutions.
{"title":"An Argentine ant system algorithm for partial set covering problem","authors":"Xiaofan Liu, Yupeng Zhou, Minghao Yin, Shuai Lv","doi":"10.1108/dta-08-2021-0205","DOIUrl":"https://doi.org/10.1108/dta-08-2021-0205","url":null,"abstract":"PurposeThe paper aims to provide an efficient meta-heuristic algorithm to solve the partial set covering problem (PSCP). With rich application scenarios, the PSCP is a fascinating and well-known non-deterministic polynomial (NP)-hard problem whose goal is to cover at least k elements with as few subsets as possible.Design/methodology/approachIn this work, the authors present a novel variant of the ant colony optimization (ACO) algorithm, called Argentine ant system (AAS), to deal with the PSCP. The developed AAS is an integrated system of different populations that use the same pheromone to communicate. Moreover, an effective local search framework with the relaxed configuration checking (RCC) and the volatilization-fixed weight mechanism is proposed to improve the exploitation of the algorithm.FindingsA detailed experimental evaluation of 75 instances reveals that the proposed algorithm outperforms the competitors in terms of the quality of the optimal solutions. Also, the performance of AAS gradually improves with the growing instance size, which shows the potential in handling complex practical scenarios. Finally, the designed components of AAS are experimentally proved to be beneficial to the whole framework. Finally, the key components in AAS have been demonstrated.Originality/valueAt present, there is no heuristic method to solve this problem. The authors present the first implementation of heuristic algorithm for solving PSCP and provide competitive solutions.","PeriodicalId":56156,"journal":{"name":"Data Technologies and Applications","volume":"19 1","pages":"762-781"},"PeriodicalIF":1.6,"publicationDate":"2022-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85384157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2022-03-28DOI: 10.1108/dta-08-2021-0209
Ze-Han Fang, C. Chen
PurposeThe purpose of this paper is to propose a novel collaborative trend prediction method to estimate the status of trending topics by crowdsourcing the wisdom in web search engines. Government officials and decision makers can take advantage of the proposed method to effectively analyze various trending topics and make appropriate decisions in response to fast-changing national and international situations or popular opinions.Design/methodology/approachIn this study, a crowdsourced-wisdom-based feature selection method was designed to select representative indicators showing trending topics and concerns of the general public. The authors also designed a novel prediction method to estimate the trending topic statuses by crowdsourcing public opinion in web search engines.FindingsThe authors’ proposed method achieved better results than traditional trend prediction methods and successfully predict trending topic statuses by using the crowdsourced wisdom of web search engines.Originality/valueThis paper proposes a novel collaborative trend prediction method and applied it to various trending topics. The experimental results show that the authors’ method can successfully estimate the trending topic statuses and outperform other baseline methods. To the best of the authors’ knowledge, this is the first such attempt to predict trending topic statuses by using the crowdsourced wisdom of web search engines.
{"title":"A collaborative trend prediction method using the crowdsourced wisdom of web search engines","authors":"Ze-Han Fang, C. Chen","doi":"10.1108/dta-08-2021-0209","DOIUrl":"https://doi.org/10.1108/dta-08-2021-0209","url":null,"abstract":"PurposeThe purpose of this paper is to propose a novel collaborative trend prediction method to estimate the status of trending topics by crowdsourcing the wisdom in web search engines. Government officials and decision makers can take advantage of the proposed method to effectively analyze various trending topics and make appropriate decisions in response to fast-changing national and international situations or popular opinions.Design/methodology/approachIn this study, a crowdsourced-wisdom-based feature selection method was designed to select representative indicators showing trending topics and concerns of the general public. The authors also designed a novel prediction method to estimate the trending topic statuses by crowdsourcing public opinion in web search engines.FindingsThe authors’ proposed method achieved better results than traditional trend prediction methods and successfully predict trending topic statuses by using the crowdsourced wisdom of web search engines.Originality/valueThis paper proposes a novel collaborative trend prediction method and applied it to various trending topics. The experimental results show that the authors’ method can successfully estimate the trending topic statuses and outperform other baseline methods. To the best of the authors’ knowledge, this is the first such attempt to predict trending topic statuses by using the crowdsourced wisdom of web search engines.","PeriodicalId":56156,"journal":{"name":"Data Technologies and Applications","volume":"13 1","pages":"741-761"},"PeriodicalIF":1.6,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80768703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2022-03-18DOI: 10.1108/dta-05-2021-0123
P. K. Sinha, Biswanath Dutta, Udaya Varadarajan
PurposeThe current work provides a framework for the ranking of ontology development methodologies (ODMs).Design/methodology/approachThe framework is a step-by-step approach reinforced by an array of ranking features and a quantitative tool, weighted decision matrix. An extensive literature investigation revealed a set of aspects that regulate ODMs. The aspects and existing state-of-the-art estimates facilitated in extracting the features. To determine weight to each of the features, an online survey was implemented to secure evidence from the Semantic Web community. To demonstrate the framework, the authors perform a pilot study, where a collection of domain ODMs, reported in 2000–2019, is used.FindingsState-of-the-art research revealed that ODMs have been accumulated, surveyed and assessed to prescribe the best probable ODM for ontology development. But none of the prevailing studies provide a ranking mechanism for ODMs. The recommended framework overcomes this limitation and gives a systematic and uniform way of ranking the ODMs. The pilot study yielded NeOn as the top-ranked ODM in the recent two decades.Originality/valueThere is no work in the literature that has investigated ranking the ODMs. Hence, this is a first of its kind work in the area of ODM research. The framework supports identifying the topmost ODMs from the literature possessing a substantial amount of features for ontology development. It also enables the selection of the best possible ODM for the ontology development.
{"title":"Ranking the ontology development methodologies using the weighted decision matrix","authors":"P. K. Sinha, Biswanath Dutta, Udaya Varadarajan","doi":"10.1108/dta-05-2021-0123","DOIUrl":"https://doi.org/10.1108/dta-05-2021-0123","url":null,"abstract":"PurposeThe current work provides a framework for the ranking of ontology development methodologies (ODMs).Design/methodology/approachThe framework is a step-by-step approach reinforced by an array of ranking features and a quantitative tool, weighted decision matrix. An extensive literature investigation revealed a set of aspects that regulate ODMs. The aspects and existing state-of-the-art estimates facilitated in extracting the features. To determine weight to each of the features, an online survey was implemented to secure evidence from the Semantic Web community. To demonstrate the framework, the authors perform a pilot study, where a collection of domain ODMs, reported in 2000–2019, is used.FindingsState-of-the-art research revealed that ODMs have been accumulated, surveyed and assessed to prescribe the best probable ODM for ontology development. But none of the prevailing studies provide a ranking mechanism for ODMs. The recommended framework overcomes this limitation and gives a systematic and uniform way of ranking the ODMs. The pilot study yielded NeOn as the top-ranked ODM in the recent two decades.Originality/valueThere is no work in the literature that has investigated ranking the ODMs. Hence, this is a first of its kind work in the area of ODM research. The framework supports identifying the topmost ODMs from the literature possessing a substantial amount of features for ontology development. It also enables the selection of the best possible ODM for the ontology development.","PeriodicalId":56156,"journal":{"name":"Data Technologies and Applications","volume":"54 1","pages":"686-719"},"PeriodicalIF":1.6,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86877468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2022-02-18DOI: 10.1108/dta-11-2021-0315
C. Floriano, Valdecy Pereira, Brunno e Souza Rodrigues
PurposeAlthough the multi-criteria technique analytic hierarchy process (AHP) has successfully been applied in many areas, either selecting or ranking alternatives or to derive priority vector (weights) for a set of criteria, there is a significant drawback in using this technique if the pairwise comparison matrix (PCM) has inconsistent comparisons, in other words, a consistency ratio (CR) above the value of 0.1, the final solution cannot be validated. Many studies have been developed to treat the inconsistency problem, but few of them tried to satisfy different quality measures, which are minimum inconsistency (fMI), the total number of adjusted pairwise comparisons (fNC), original rank preservation (fKT), minimum average weights adjustment (fWA) and finally, minimum L1 matrix norm between the original PCM and the adjusted PCM (fLM).Design/methodology/approachThe approach is defined in four steps: first, the decision-maker should choose which quality measures she/he wishes to use, ranging from one to all quality measures. In the second step, the authors encode the PCM to be used in a many-objective optimization algorithm (MOOA), and each pairwise comparison can be adjusted individually. The authors generate consistent solutions from the obtained Pareto optimal front that carry the desired quality measures in the third step. Lastly, the decision-maker selects the most suitable solution for her/his problem. Remarkably, as the decision-maker can choose one (mono-objective), two (multi-objective), three or more (many-objectives) quality measures, not all MOOAs can handle or perform well in mono- or multi-objective problems. The unified non-sorting algorithm III (U-NSGA III) is the most appropriate MOOA for this type of scenario because it was specially designed to handle mono-, multi- and many-objective problems.FindingsThe use of two quality measures should not guarantee that the adjusted PCM is similar to the original PCM; hence, the decision-maker should consider using more quality measures if the objective is to preserve the original PCM characteristics.Originality/valueFor the first time, a many-objective approach reduces the CR to consistent levels with the ability to consider one or more quality measures and allows the decision-maker to adjust each pairwise comparison individually.
{"title":"3MO-AHP: an inconsistency reduction approach through mono-, multi- or many-objective quality measures","authors":"C. Floriano, Valdecy Pereira, Brunno e Souza Rodrigues","doi":"10.1108/dta-11-2021-0315","DOIUrl":"https://doi.org/10.1108/dta-11-2021-0315","url":null,"abstract":"PurposeAlthough the multi-criteria technique analytic hierarchy process (AHP) has successfully been applied in many areas, either selecting or ranking alternatives or to derive priority vector (weights) for a set of criteria, there is a significant drawback in using this technique if the pairwise comparison matrix (PCM) has inconsistent comparisons, in other words, a consistency ratio (CR) above the value of 0.1, the final solution cannot be validated. Many studies have been developed to treat the inconsistency problem, but few of them tried to satisfy different quality measures, which are minimum inconsistency (fMI), the total number of adjusted pairwise comparisons (fNC), original rank preservation (fKT), minimum average weights adjustment (fWA) and finally, minimum L1 matrix norm between the original PCM and the adjusted PCM (fLM).Design/methodology/approachThe approach is defined in four steps: first, the decision-maker should choose which quality measures she/he wishes to use, ranging from one to all quality measures. In the second step, the authors encode the PCM to be used in a many-objective optimization algorithm (MOOA), and each pairwise comparison can be adjusted individually. The authors generate consistent solutions from the obtained Pareto optimal front that carry the desired quality measures in the third step. Lastly, the decision-maker selects the most suitable solution for her/his problem. Remarkably, as the decision-maker can choose one (mono-objective), two (multi-objective), three or more (many-objectives) quality measures, not all MOOAs can handle or perform well in mono- or multi-objective problems. The unified non-sorting algorithm III (U-NSGA III) is the most appropriate MOOA for this type of scenario because it was specially designed to handle mono-, multi- and many-objective problems.FindingsThe use of two quality measures should not guarantee that the adjusted PCM is similar to the original PCM; hence, the decision-maker should consider using more quality measures if the objective is to preserve the original PCM characteristics.Originality/valueFor the first time, a many-objective approach reduces the CR to consistent levels with the ability to consider one or more quality measures and allows the decision-maker to adjust each pairwise comparison individually.","PeriodicalId":56156,"journal":{"name":"Data Technologies and Applications","volume":"35 1","pages":"645-670"},"PeriodicalIF":1.6,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77746376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2022-02-15DOI: 10.1108/dta-10-2021-0280
T. Bayrak
PurposeThis paper explores and examines the mission statements of the most ethical companies across the globe in terms of their main purposes, values, goals, and objective, and what they say about their vision and goals.Design/methodology/approachThis study is based on the data published by the Ethisphere Institute, the global leader in defining and advancing the standards of ethical business practices. Having compiled the mission statements into a text file, the authors conducted text mining using a commercially available text mining tool SAS Enterprise Miner to survey if the most ethical companies have valued the same vision and mission such as social responsibility and ethics.FindingsA review of their mission statements indicated that some of the most ethical companies surveyed in this study such as 3M and Voya strive to be “socially responsible and ethical,” support their “societies” and respect and protect the “nature,” “planet” and “environment.” The world's most ethical companies that stress these weighted terms in their mission statements may do so to show their commitment by being socially responsible and ethical, and delivering sustainable business solutions to their customers.Originality/valueThis study provides a systematic and comprehensive exploration of mission statements of the most ethical companies in an attempt to identify patterns of differences and similarities within these statements.
{"title":"Text mining the mission statements of the most ethical companies","authors":"T. Bayrak","doi":"10.1108/dta-10-2021-0280","DOIUrl":"https://doi.org/10.1108/dta-10-2021-0280","url":null,"abstract":"PurposeThis paper explores and examines the mission statements of the most ethical companies across the globe in terms of their main purposes, values, goals, and objective, and what they say about their vision and goals.Design/methodology/approachThis study is based on the data published by the Ethisphere Institute, the global leader in defining and advancing the standards of ethical business practices. Having compiled the mission statements into a text file, the authors conducted text mining using a commercially available text mining tool SAS Enterprise Miner to survey if the most ethical companies have valued the same vision and mission such as social responsibility and ethics.FindingsA review of their mission statements indicated that some of the most ethical companies surveyed in this study such as 3M and Voya strive to be “socially responsible and ethical,” support their “societies” and respect and protect the “nature,” “planet” and “environment.” The world's most ethical companies that stress these weighted terms in their mission statements may do so to show their commitment by being socially responsible and ethical, and delivering sustainable business solutions to their customers.Originality/valueThis study provides a systematic and comprehensive exploration of mission statements of the most ethical companies in an attempt to identify patterns of differences and similarities within these statements.","PeriodicalId":56156,"journal":{"name":"Data Technologies and Applications","volume":"25 1","pages":"671-685"},"PeriodicalIF":1.6,"publicationDate":"2022-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80594930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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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