201 10 3575 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Aljammal, Ashraf H. taamneh , Salah Qawasmeh, Ahmad Bani Salameh, Hani Date A point or period of time associated with an event in the lifecycle of the resource 2023-03-07 Description An account of the resource Nowadays, individuals and organizations are increasingly targeted by phishing attacks, so an accurate phishing detection system is required. Therefore, many phishing detection techniques have been proposed as well as phishing datasets have been collected. In this paper, three datasets have been used to train and test machine learning classifiers. The datasets have been archived by Phish-Tank and UCI Machine Learning Repository. Furthermore, Information Gain algorithm have been used for features reduction and selection purpose. In addition, six machine learning classifiers have been evaluated, namely NaiveBayes, ANN, DecisionStump, KNN, J48 and RandomForest. However, the classifiers have been trained and tested over the three datasets in two stages. The first stage is using all features included in each dataset while the second stage using selected features by IG algorithm. At the first stage RandomForest classifier has shown the best performance over Dataset-1 and Dataset-2, while J48 has shown the best performance over Dataset-3. On the other hand, after features selection, the RandomForest classifier was the superior among the other five classifiers over Dataset-1 and Dataset-2 with accuracy of 98% and 93.66% respectively. While ANN classifier has shown the best performance with accuracy of 88.92% over Dataset-3. Because of the few number of instances as well as features in Dataset-3 comparing to the other two dataset; the performance of the classifiers has been affected. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37575 10.3991/ijim.v17i05.37575 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37575/12813 Rights Information about rights held in and over the resource Copyright (c) 2023 Ashraf Hamdan Aljammal https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 05 (2023); pp. 71-83 1865-7923 Subject The topic of the resource Phishing attack, phishing attack detection, Cybersecurity, Machine Learning, Web security Title A name given to the resource Machine Learning Based Phishing Attacks Detection Using Multiple Datasets Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Alegre-Veliz, Rosa Gaspar-Ortiz, Pedro Gamboa-Cruzado, Javier Rodriguez Baca, Liset Grandez Pizarro, Waldy Menéndez Mueras, Rosa Chávez Herrera, Carlos Date A point or period of time associated with an event in the lifecycle of the resource 2022-12-20 Description An account of the resource At present, sentiment analysis has become a trend; above all, in digital product development companies, as it is essential for rapid and automatic analysis. Sentiment analysis deals with emotions with the help of software, and it is playing an unavoidable role in workplaces. The constant growth of social networks, especially the Twitter social network, has made the ability to understand and comprehend users or clients take a greater scope regarding their needs; and therefore, increase the complexity of analysis of this social network, causing excessive expenses in time, personnel and money. This work presents a solution through the application of Machine Learning (ML) for sentiment analysis and thus improve analysis, execution time and customer satisfaction. The scope of this research is limited to using the Support Vector Machine (SVM) supervised learning technique for the intended analysis. The model derives from the ML technique making use of cross validation. The applied methodology is the CRISP-ML(Q) Methodology. The results show that the use of ML allows efficient sentiment analysis in Twitter communications. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/35493 10.3991/ijim.v16i24.35493 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/35493/12461 Rights Information about rights held in and over the resource Copyright (c) 2022 Javier Gamboa-Cruzado, Alegre-Veliz, Pedro Gaspar-Ortiz, Liset Rodriguez Baca, Waldy Grandez Pizarro, Rosa Menéndez Mueras, Carlos Chávez Herrera https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 24 (2022); pp. 126-142 1865-7923 Subject The topic of the resource algorithms classification CRISP-ML(Q) machine learning SVM analysis feelings Title A name given to the resource Machine Learning for Feeling Analysis in Twitter Communications: A Case Study in HEYDRU!, Perú Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Dirin, Amir Saballe, Charlese Adriana Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-18 Description An account of the resource Selecting a proper study path in higher education is a difficult task for many students. They either have a lack of knowledge on the study path offered or are unsure of their interest in the various options. The current educational setups enable us to collect valid and reliable data on student success and learning behaviour. This study explores and solves the problem of what path to select by proposing possible study paths with the help of machine learning algorithms.  Learning analytics (LA) and educational data mining (EDM) are technologies that aid in the analysis of educational data. In this quantitative study, we applied a questionnaire to collect data from students at the Business Information Technology Department (Bite) at the Haaga-Helia University of Applied Science. We managed to collect 101 samples from students during 2017–2018. We used various machine learning algorithms and prediction models to assess the best approach for study path selection.  We applied three performance scores of accuracy, Cohen’s Kappa, and ROC curve to measure the accuracy of the algorithm results. KNIME analytics was selected as a proper tool to pre-process, prepare, analyse, and model the data. The results indicate that Random Forest (94% accuracy) and Decision Tree (93% accuracy) are the best classification models for students’ study path selection. The contribution of this study is for educational data mining research to assess the comparison of various algorithms. Furthermore, this is a novel approach to predict students’ study path selection, which educational institutes should develop to assist students in their study path selection. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/20121 10.3991/ijim.v16i01.20121 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/20121/10563 Rights Information about rights held in and over the resource Copyright (c) 2021 Amir Dirin, Charlese Adriana Saballe https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 01 (2022); pp. 158-183 1865-7923 Subject The topic of the resource educational data mining decision trees random forest and logistic regressions Title A name given to the resource Machine Learning Models to Predict Students’ Study Path Selection Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Alqudah, Yazan Sababha, Belal Qaralleh, Esam Yousseff, Tarek Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-26 Description An account of the resource With the ever-increasing vehicle population and introduction of autonomous and self-driving cars, innovative research is needed to ensure safety and reliability on the road. This work introduces an innovative solution that aims at understanding vehicle behavior based on sensors data. The behavior is classified according to driving events. Understanding driving events can play a significant role in road safety and estimating the expense and risks of driving and consuming a vehicle. Rather than relying on the distance and time driven, driving events can provide a more accurate measure of vehicle driving consumption.  This measure will become more valuable as more autonomous vehicles and more ride sharing applications are introduced to roads around the world. Estimating driving events can also help better design the road infrastructure to reduce energy consumption.  By sharing data from official vehicles and volunteers, crowd sensing can be used to better understand congestion and road safety. This work studies driving events and proposes using machine learning to classify these events into different categories. The acquired data is collected using embedded mobile device motion sensors and are used to train machine learning algorithms to classify the events. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/18303 10.3991/ijim.v15i02.18303 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/18303/8647 Rights Information about rights held in and over the resource Copyright (c) 2021 Yazan Alqudah, Belal Sababha, Esam Qaralleh, Tarek Yousseff Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 02 (2021); pp. 124-136 1865-7923 Subject The topic of the resource Mobile Development Driving Events Machine Learning Classification Title A name given to the resource Machine Learning to Classify Driving Events Using Mobile Phone Sensors Data Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Czech Journal of International Relations Publisher An entity responsible for making the resource available Institute of International Relations Prague, Ministry of Foreign Affairs of the Czech Republic Relation A related resource ISSN 2788-2985 eISSN 2788-2993 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Petlach, Martin Date A point or period of time associated with an event in the lifecycle of the resource 2021-06-01 Description An account of the resource This edited volume is the first to discuss the methodological implications ofthe ‘emotional turn’ in International Relations. While emotions have becomeof increasing interest to IR theory, methodological challenges have yet toreceive proper attention. Acknowledging the plurality of ontologicalpositions, concepts and theories about the role of emotions in worldpolitics, this volume presents and discusses various ways to researchemotions empirically. Based on concrete research projects, the chaptersdemonstrate how social-scientific and humanitiesoriented methodologicalapproaches can be successfully adapted to the study of emotions in IR. Thevolume covers a diverse set of both well-established and innovativemethods, including discourse analysis, ethnography, narrative, and visualanalysis. Through a hands-on approach, each chapter sheds light onpractical challenges and opportunities, as well as lessons learnt for futureresearch. The volume is an invaluable resource for advanced graduate andpostgraduate students as well as scholars interested in developing theirown empirical research on the role of emotions. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://cjir.iir.cz/index.php/cjir/article/view/52 10.32422/mv-cjir.1776 Language A language of the resource eng Publisher An entity responsible for making the resource available Institute of International Relations Prague Relation A related resource https://cjir.iir.cz/index.php/cjir/article/view/52/41 Rights Information about rights held in and over the resource https://creativecommons.org/licenses/by-nd/4.0 Source A related resource from which the described resource is derived Czech Journal of International Relations; Vol. 56 No. 2 (2021); 89-96 2788-2993 2788-2985 10.32422/mv-cjir.56.2 Title A name given to the resource Maéva Clément and Eric Sangar (Eds): Researching Emotions in International Relations Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion book review Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Journal of Naval Architecture and Marine Engineering Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Maleque, Md Abdul Alam, Md Shariful Date A point or period of time associated with an event in the lifecycle of the resource 2009-02-11 Description An account of the resource An analysis of free convection and mass transfer unsteady magnetohydrodynamic flow of an electrically conducting viscous incompressible fluid past an infinite vertical porous plate is presented by taking into account the Dufour and Soret effects. With a goal to attain similarity solutions of the problem posed, similarity equations are derived by introducing a time dependent length scale. The non-linear similarity equations, which are locally similar, are solved numerically using shooting method. Dimensionless velocity, temperature and concentration profiles are displayed graphically for different values of the parameters entering into the problem. Finally, the corresponding local skin-friction, local Nusselt number and local Sherwood number, which are of physical interest are tabulated. Keywords: Magnetodydrodynamic, Free convection, Mass transfer, Dufour and Soret effects.   doi: 10.3329/jname.v1i1.2035 Journal of Naval Architecture and Marine Engineering 1(2004) 18-25 Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://www.banglajol.info/index.php/JNAME/article/view/2035 10.3329/jname.v1i1.2035 Language A language of the resource eng Publisher An entity responsible for making the resource available Association of Naval Architects and Marine Engineers Relation A related resource https://www.banglajol.info/index.php/JNAME/article/view/2035/1892 Source A related resource from which the described resource is derived Journal of Naval Architecture and Marine Engineering; Vol. 1 No. 1 (2004); 18-25 2070-8998 1813-8535 Subject The topic of the resource Magnetodydrodynamic Free convection Mass transfer Dufour and Soret effects Title A name given to the resource Magnetohydrodynamic free convection and mass transfer flow past a vertical porous flat plate with Dufour and Soret effects Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Liberal Studies Publisher An entity responsible for making the resource available School of Liberal Studies, Pandit Deendayal Energy University, India Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Misra, Surya Narayan Date A point or period of time associated with an event in the lifecycle of the resource 2019-12-31 Description An account of the resource Mahatma Gandhi has left his heritage of spiritual force; the influence which emanated from his personality was ineffable, like music, like beauty its claim upon others was great because of its revelation of a spontaneous self-giving. Suffice to say, he never belonged to his age. He was rather a link between the past and future, and the philosopher for the 21st century. In fact, in 2007 the United Nations has rightly decided to observe October 2nd (Gandhi's Birthday) as the Day of Non-violence. As a tribute, especially in 2019 as his birth centennial year, we must recall the saintly man, who preached non-violence, and his ideals that are the potential to address many of our contemporary concerns. DOI: 10.5281/zenodo.3874025 Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://ojs.indrastra.com/index.php/liberalstudies/article/view/43 Language A language of the resource eng Publisher An entity responsible for making the resource available Pandit Deendayal Energy University Relation A related resource https://ojs.indrastra.com/index.php/liberalstudies/article/view/43/43 Rights Information about rights held in and over the resource Copyright (c) 2019 Pandit Deendayal Petroleum University, India https://creativecommons.org/licenses/by-nc-nd/4.0/ Source A related resource from which the described resource is derived Liberal Studies; Vol. 4 No. 2 (2019): July-December 2019; 203-208 2688-9374 2455-9857 Subject The topic of the resource Mahatma Gandhi Title A name given to the resource Mahatma Gandhi: A Sesquicentennial Birthday Tribute Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource AEGIS : Journal of International Relations Source A related resource from which the described resource is derived School of International Relations, President University, Indonesia Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Aryodiguno, Harryanto Cornelia, Tiara Date A point or period of time associated with an event in the lifecycle of the resource 2022-06-18 Description An account of the resource Since opened in 2011, the number of Chinese students goes to Taiwan for 6 months exchange grew more and more every year. What things that motivate the Chinese student to come to Taiwan? Is it related to the current both country’s political condition? What they been thinking about Taiwan, before and after they came? Will they obtain a new perspective about cross-strait disputes? Will they be the agent of democratic political reform in China in the future? Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context http://e-journal.president.ac.id/presunivojs/index.php/AEGIS/article/view/3530 10.33021/aegis.v6i1.3530 Language A language of the resource eng Publisher An entity responsible for making the resource available President University Relation A related resource http://e-journal.president.ac.id/presunivojs/index.php/AEGIS/article/view/3530/1157 Rights Information about rights held in and over the resource Copyright (c) 2022 AEGIS : Journal of International Relations http://creativecommons.org/licenses/by-nc/4.0 Source A related resource from which the described resource is derived AEGIS : Journal of International Relations; Vol 6, No 1 (2022) 2548-4532 2541-1373 Title A name given to the resource Mainland China Student Study in Taiwan: Motivation, Impression, Potential Political Reform Agent Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Kouroupetroglou, Christos Tektonidis, Dimitris Koumpis, Adamantios Ignatiadis, Ioannis Date A point or period of time associated with an event in the lifecycle of the resource 2012-01-17 Description An account of the resource This paper presents the outcomes from the interviews with experts and stakeholders that took part under the study on e-Accessibility2020[1] (â??Study on Implications from Future ICT Trends on Assistive Technology and Accessibility Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/1791 10.3991/ijim.v6i1.1791 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/1791/2038 Rights Information about rights held in and over the resource Copyright (c) 2017 Christos Kouroupetroglou, Dimitris Tektonidis, Adamantios Koumpis, Ioannis Ignatiadis Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 6 No. 1 (2012); pp. 43-47 1865-7923 Subject The topic of the resource eAccessibility mobile accessibility assistive technology e-Accessibility standards Design for all Title A name given to the resource Mainstreaming of Mobile Assistive Technology: Expertsâ?? Thoughts and Opinions Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Non-refereed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Sarif, Siti Mahfuzah Hanafi, Zurina Packeer Mohamed, Shafinah Farvin Bahrin Zaibon, Syamsul Mohamad Mohsin, Mohamad Farhan Date A point or period of time associated with an event in the lifecycle of the resource 2020-04-07 Description An account of the resource This paper discusses a unique business model of eatery recommender system based on local knowledge using mobile platform. The business model is developed to define the business concept of the innovation which is a rural innovation involving multiple entities (locals, eatery owners and users who are searching for eatery). The innovation highlights on local knowledge crowdsourced from the participation of locals through gamification activities included in the mobile app. In achieving the aim, the design science methodology was adapted in this study which consists of 4 phases: (i) Awareness of Problem, (ii) Suggestion, (iii) Evaluation, and (iv) Conclusion. The proposed business model was developed through a few activities including literature review, comparative study dan preliminary study. Then, the study continued with developing a prototype known as Makan@Local Chatok (M@LC) app and evaluated the app in terms of its usability aspects. Results from the usability testing concludes that the app is perceived as easy to use. It was also found that the proposed business model has been well-accepted by users. In conclusion, it is hoped that this study will not only demonstrate the potential and impact of mobile eatery recommendation system using local knowledge, but also provide a capstone on business research in the field of tourism industry. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/13357 10.3991/ijim.v14i05.13357 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/13357/6781 Rights Information about rights held in and over the resource Copyright (c) 2020 Siti Mahfuzah Sarif, Zurina Hanafi, Shafinah Farvin Packeer Mohamed, Syamsul Bahrin Zaibon, Mohamad Farhan Mohamad Mohsin Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 05 (2020); pp. 129-149 1865-7923 Subject The topic of the resource Mobile recommender system local knowledge gamification Title A name given to the resource Makan@Local Chatok: Mobile Eatery Recommendation System Based on Local Knowledge Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article