Panagiotis Germanakos, S. Kleanthous, G. Samaras, V. Dimitrova, B. Steichen
It is our great pleasure to welcome you to the 2nd International workshop on Human Aspects in Adaptive and Personalized Interactive Environments (HAAPIE 2017). HAAPIE 2017 (http://haapie.cs.ucy.ac.cy) is a full-day workshop held on 09 July 2017 in conjunction with the 25th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2017), 09-12 July 2017 in Bratislava, Slovakia. Nowadays, the profound digital transformation has upgraded the role of the computational system into an intelligent multidimensional communication medium that creates new opportunities, competencies, models and processes. HAAPIE embraces the essence of the human-machine co-existence and aims to bring more inclusively the "human-in-the-loop", adequately supporting the rising multi-purpose goals, needs, requirements, activities and interactions of users through new human-centered adaptive and personalized interactive environments, algorithms and systems. It brings together experts, researchers, students and practitioners from different disciplines for sharing ideas and experiences, lessons learned, approaches and results that could substantially contribute to the broader UMAP community. This year we received 14 submissions from all around the world covering a broad range of topics on the workshop's research themes areas. Each paper has been reviewed by up to 3 members of the IPC with expertise in the respective area to ensure the necessary relevance, quality and novelty.
{"title":"UMAP 2017 HAAPIE (Human Aspects in Adaptive and Personalized Interactive Environments) Workshop Chairs' Preface & Organization","authors":"Panagiotis Germanakos, S. Kleanthous, G. Samaras, V. Dimitrova, B. Steichen","doi":"10.1145/3099023.3099050","DOIUrl":"https://doi.org/10.1145/3099023.3099050","url":null,"abstract":"It is our great pleasure to welcome you to the 2nd International workshop on Human Aspects in Adaptive and Personalized Interactive Environments (HAAPIE 2017). HAAPIE 2017 (http://haapie.cs.ucy.ac.cy) is a full-day workshop held on 09 July 2017 in conjunction with the 25th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2017), 09-12 July 2017 in Bratislava, Slovakia. Nowadays, the profound digital transformation has upgraded the role of the computational system into an intelligent multidimensional communication medium that creates new opportunities, competencies, models and processes. HAAPIE embraces the essence of the human-machine co-existence and aims to bring more inclusively the \"human-in-the-loop\", adequately supporting the rising multi-purpose goals, needs, requirements, activities and interactions of users through new human-centered adaptive and personalized interactive environments, algorithms and systems. It brings together experts, researchers, students and practitioners from different disciplines for sharing ideas and experiences, lessons learned, approaches and results that could substantially contribute to the broader UMAP community. This year we received 14 submissions from all around the world covering a broad range of topics on the workshop's research themes areas. Each paper has been reviewed by up to 3 members of the IPC with expertise in the respective area to ensure the necessary relevance, quality and novelty.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117183524","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}
This demo paper presents a Web application for recommending travel regions for independent travelers. Users can specify preferences such as budget and preferred activities and receive suggested trips consisting of multiple regions. We explain the main ideas behind the data model and algorithm of our solution, and give an overview on the implementation
{"title":"A Web-based Application for Recommending Travel Regions","authors":"W. Wörndl","doi":"10.1145/3099023.3099031","DOIUrl":"https://doi.org/10.1145/3099023.3099031","url":null,"abstract":"This demo paper presents a Web application for recommending travel regions for independent travelers. Users can specify preferences such as budget and preferred activities and receive suggested trips consisting of multiple regions. We explain the main ideas behind the data model and algorithm of our solution, and give an overview on the implementation","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125010216","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}
Effective exercise selection based on learner characteristics is important for Intelligent Tutoring Systems to improve learning. Based on a literature review, we categorize learner characteristics used for adaptation in an ITS. We then present a preliminary framework of the relationship between some of these learner characteristics, with an emphasis on personality, and how they can be used by an ITS to adapt exercise selection.
{"title":"Conceptualizing a Framework for Adaptive Exercise Selection with Personality as a Major Learner Characteristic","authors":"J. Okpo, J. Masthoff, Matt Dennis, N. Beacham","doi":"10.1145/3099023.3099078","DOIUrl":"https://doi.org/10.1145/3099023.3099078","url":null,"abstract":"Effective exercise selection based on learner characteristics is important for Intelligent Tutoring Systems to improve learning. Based on a literature review, we categorize learner characteristics used for adaptation in an ITS. We then present a preliminary framework of the relationship between some of these learner characteristics, with an emphasis on personality, and how they can be used by an ITS to adapt exercise selection.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"300 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123392425","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}
This paper presents principles of designing Educational Assessment Technology (EdAT) that is culturally-appropriate. These principles are based on a study on international large-scale assessments (ILSA) and the relations of their findings with culture. In order to achieve this, we correlate ILSA data with Cultural Dimension data for 81 countries and examine the implications for designing student-centred systems based on cultural dimensions. Cultural dimensions such as long-term orientation are good predictors for achievement and can guide design decisions around adaptation.
{"title":"International Large-Scale Assessments and Culture: Implications for Designing Educational Technology","authors":"E. Kapros","doi":"10.1145/3099023.3099054","DOIUrl":"https://doi.org/10.1145/3099023.3099054","url":null,"abstract":"This paper presents principles of designing Educational Assessment Technology (EdAT) that is culturally-appropriate. These principles are based on a study on international large-scale assessments (ILSA) and the relations of their findings with culture. In order to achieve this, we correlate ILSA data with Cultural Dimension data for 81 countries and examine the implications for designing student-centred systems based on cultural dimensions. Cultural dimensions such as long-term orientation are good predictors for achievement and can guide design decisions around adaptation.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128830609","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}
Our wider research project investigates the design of a persuasive game for preventing mental health problems and improving subjective wellbeing in a student population. In this paper, we explore how persuasive game elements and interactions can be adapted to different student personalities, active stressors and attitudes. In six focus groups we investigated (1) which key stressors are experienced by students, (2) what characteristics of students need to be considered for adapting game interactions and challenges, and (3) which approaches to personalisation could be applied. Participants were shown stories about a fictional student, conveying high and low levels of three personality traits (Conscientiousness, Emotional Stability and Extraversion), levels of active stressors, and varying attitudes towards change. Participants discussed how to tailor game interactions, activities and challenges to the characteristics of the fictional student. In general, participants perceived real-time personalisation using implicit measures as more effective, but recognised explicit profiling as a valuable complementary method. These findings have implications for the personalisation and design of persuasive game based interventions for health.
{"title":"Qualitative Study into Adapting Persuasive Games for Mental Wellbeing to Personality, Stressors and Attitudes","authors":"Ana Ciocarlan, J. Masthoff, N. Oren","doi":"10.1145/3099023.3099111","DOIUrl":"https://doi.org/10.1145/3099023.3099111","url":null,"abstract":"Our wider research project investigates the design of a persuasive game for preventing mental health problems and improving subjective wellbeing in a student population. In this paper, we explore how persuasive game elements and interactions can be adapted to different student personalities, active stressors and attitudes. In six focus groups we investigated (1) which key stressors are experienced by students, (2) what characteristics of students need to be considered for adapting game interactions and challenges, and (3) which approaches to personalisation could be applied. Participants were shown stories about a fictional student, conveying high and low levels of three personality traits (Conscientiousness, Emotional Stability and Extraversion), levels of active stressors, and varying attitudes towards change. Participants discussed how to tailor game interactions, activities and challenges to the characteristics of the fictional student. In general, participants perceived real-time personalisation using implicit measures as more effective, but recognised explicit profiling as a valuable complementary method. These findings have implications for the personalisation and design of persuasive game based interventions for health.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127429211","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}
Mirjam Augstein, Thomas Neumayr, W. Kurschl, Daniel Kern, Thomas Burger, J. Altmann
Personalization has been discussed in a number of domains such as learning, search or information retrieval. In the area of human-computer interaction, personalization also plays a prominent role. For the variety of users, especially for those with impairments, interaction abilities vary drastically and for many it is not possible to use common interaction devices like a mouse or the touch screen of a smart phone (at least not with their predefined configuration). This paper describes a personalized interaction approach based on i) modeling users' interaction abilities, ii) automated selection and configuration of interaction devices for the individual user, and iii) adaptive behavior of selected applications. It is not exclusively focused on the requirements of people with impairments but frequently takes up this target group as it might particularly benefit from interaction personalization concepts.
{"title":"A Personalized Interaction Approach: Motivation and Use Case","authors":"Mirjam Augstein, Thomas Neumayr, W. Kurschl, Daniel Kern, Thomas Burger, J. Altmann","doi":"10.1145/3099023.3099051","DOIUrl":"https://doi.org/10.1145/3099023.3099051","url":null,"abstract":"Personalization has been discussed in a number of domains such as learning, search or information retrieval. In the area of human-computer interaction, personalization also plays a prominent role. For the variety of users, especially for those with impairments, interaction abilities vary drastically and for many it is not possible to use common interaction devices like a mouse or the touch screen of a smart phone (at least not with their predefined configuration). This paper describes a personalized interaction approach based on i) modeling users' interaction abilities, ii) automated selection and configuration of interaction devices for the individual user, and iii) adaptive behavior of selected applications. It is not exclusively focused on the requirements of people with impairments but frequently takes up this target group as it might particularly benefit from interaction personalization concepts.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134352606","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}
Valentina Maccatrozzo, E. V. Everdingen, Lora Aroyo, G. Schreiber
In the digital era, personalisation systems are the typical way to deal with the massive amount of information on the Web. ese systems decide in our place what we like, possibly hiding us away from a complete world of potentially interesting content. ese systems do not challenge us to open our horizons of interest, trap- ping us more and more in our lter bubble. Introducing diversity and serendipity in the recommendation results has been widely recognised as the solution to this issue in the information retrieval eld. However, serendipity cannot be addressed and measured with traditional accuracy metrics, because it introduces much more complexity in terms of subjectivity and personality. Inspired by the curiosity theory of Berlyne, further developed by Silvia, we introduce in user pro les a so-called coping potential estimation as a measure of the users' ability to cope with new items (e.g., ability to appreciate serendipitous recommendations). Our assumption is that curiosity leads to serendipity and high coping potential users accept more serendipitous results, and thus we need to model it in the recommendation algorithm. We performed an online ex- periment where we asked users a number of questions about TV programmes recommendations. Our results show that users with a high coping potential are more inclined to accept serendipitous recommendations than their counterparts.
{"title":"Everybody, More or Less, likes Serendipity","authors":"Valentina Maccatrozzo, E. V. Everdingen, Lora Aroyo, G. Schreiber","doi":"10.1145/3099023.3099064","DOIUrl":"https://doi.org/10.1145/3099023.3099064","url":null,"abstract":"In the digital era, personalisation systems are the typical way to deal with the massive amount of information on the Web. ese systems decide in our place what we like, possibly hiding us away from a complete world of potentially interesting content. ese systems do not challenge us to open our horizons of interest, trap- ping us more and more in our lter bubble. Introducing diversity and serendipity in the recommendation results has been widely recognised as the solution to this issue in the information retrieval eld. However, serendipity cannot be addressed and measured with traditional accuracy metrics, because it introduces much more complexity in terms of subjectivity and personality. Inspired by the curiosity theory of Berlyne, further developed by Silvia, we introduce in user pro les a so-called coping potential estimation as a measure of the users' ability to cope with new items (e.g., ability to appreciate serendipitous recommendations). Our assumption is that curiosity leads to serendipity and high coping potential users accept more serendipitous results, and thus we need to model it in the recommendation algorithm. We performed an online ex- periment where we asked users a number of questions about TV programmes recommendations. Our results show that users with a high coping potential are more inclined to accept serendipitous recommendations than their counterparts.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133880885","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}
Personalized educational systems are able to provide learners questions of specified difficulty. Since learners differ, the appropriate level of difficulty may vary and it may be impossible to find an universal setting. We implemented a version of an adaptive educational system for geography practice that allows learners to adjust difficulty of questions. We evaluated this feature using a randomized control experiment. The overall results show only a small effect of the adjustment. A more detailed analysis, however, shows that for some groups of learners the effect can be important, although not necessarily advantageous. The collected data from the experiment provide insight into how to tune question difficulty automatically.
{"title":"Should We Give Learners Control Over Item Difficulty?","authors":"Jan Papousek, Radek Pelánek","doi":"10.1145/3099023.3099080","DOIUrl":"https://doi.org/10.1145/3099023.3099080","url":null,"abstract":"Personalized educational systems are able to provide learners questions of specified difficulty. Since learners differ, the appropriate level of difficulty may vary and it may be impossible to find an universal setting. We implemented a version of an adaptive educational system for geography practice that allows learners to adjust difficulty of questions. We evaluated this feature using a randomized control experiment. The overall results show only a small effect of the adjustment. A more detailed analysis, however, shows that for some groups of learners the effect can be important, although not necessarily advantageous. The collected data from the experiment provide insight into how to tune question difficulty automatically.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133896917","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}
It is our great pleasure to welcome you to the UMAP 2017 LBR, Demo, and TOR Track, the 25th User Modelling, Adaptation and Personalization, held in Bratislava, Slovakia organized between the July 9-12th, 2017. This track of UMAP wraps three categories: (i) Demos, which showcase research prototypes and commercially available products of UMAP-based systems, (ii) Late-breaking Results, which contain original and unpublished accounts of innovative research ideas, preliminary results, industry showcases, and system prototypes, addressing both the theory and practice of UMAP and (iii) Theory, Opinion and Reflection (TOR). TOR is an additional category introduced in this edition of UMAP. Papers in this category critically look at ongoing research topics, reflect on persistent or fleeting trends in the field and offer blue sky future agendas for UMAP research. A novelty related to the TOR category is the presentation format. TOR papers will be presented in the form of an interactive campfire session in a discussion corner during the poster session. In total, we received 13 LBR, 6 TOR, and 4 Demo submissions out of which 8, 3 and 3 were deemed of high quality by the reviewers. Further 6 LBR papers were accepted from the main conference.
{"title":"UMAP'17 Late-Breaking Results, Demonstration and Theory, Opinion & Reflection Papers Chairs' Preface & Organization","authors":"M. Tkalcic, D. Thakker","doi":"10.1145/3099023.3099062","DOIUrl":"https://doi.org/10.1145/3099023.3099062","url":null,"abstract":"It is our great pleasure to welcome you to the UMAP 2017 LBR, Demo, and TOR Track, the 25th User Modelling, Adaptation and Personalization, held in Bratislava, Slovakia organized between the July 9-12th, 2017. This track of UMAP wraps three categories: (i) Demos, which showcase research prototypes and commercially available products of UMAP-based systems, (ii) Late-breaking Results, which contain original and unpublished accounts of innovative research ideas, preliminary results, industry showcases, and system prototypes, addressing both the theory and practice of UMAP and (iii) Theory, Opinion and Reflection (TOR). TOR is an additional category introduced in this edition of UMAP. Papers in this category critically look at ongoing research topics, reflect on persistent or fleeting trends in the field and offer blue sky future agendas for UMAP research. A novelty related to the TOR category is the presentation format. TOR papers will be presented in the form of an interactive campfire session in a discussion corner during the poster session. In total, we received 13 LBR, 6 TOR, and 4 Demo submissions out of which 8, 3 and 3 were deemed of high quality by the reviewers. Further 6 LBR papers were accepted from the main conference.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115011183","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}
Research has shown that persuasive technologies are more effective when they are personalized. Persuasive strategies work differently for various people; hence a one size fits all approach may not bring about the desired change in behavior or attitude. This paper contributes to personalization in question and answer (Q&A) social networks by exploring the possibility of personalizing social influence strategies based on the computer programming skill level and the highest level of education of users. In particular, this paper explores the susceptibility of users in Stack Overflow, a Q&A social network, to social support influence strategies for novice and expert computer programmers. In addition, we explore if first degree holders respond to the social support influence strategies the same way graduate degree holders do. Using a sample size of 282 Stack Overflow users, we constructed four models using Partial Least Squares Structural Equation Modelling (PLS-SEM) and carried out multi-group analysis between these models. The results of our analysis show that social facilitation significantly influences cooperation for novice programmers, but not for expert programmers. In addition, social learning does not significantly influence the persuasiveness of the system for expert programmers compared to users who are novice in computer programming. For the users grouped according to their highest level of education, social learning influenced cooperation among the graduate degree holders and competition influenced the graduate degree holders to continue using the system. The result of this study can provide useful guidelines to social network developers that can be used in implementing personalized influence strategies in Q&A social communities.
{"title":"Personalizing Social Influence Strategies in a Q&A Social Network","authors":"I. Adaji, Julita Vassileva","doi":"10.1145/3099023.3099057","DOIUrl":"https://doi.org/10.1145/3099023.3099057","url":null,"abstract":"Research has shown that persuasive technologies are more effective when they are personalized. Persuasive strategies work differently for various people; hence a one size fits all approach may not bring about the desired change in behavior or attitude. This paper contributes to personalization in question and answer (Q&A) social networks by exploring the possibility of personalizing social influence strategies based on the computer programming skill level and the highest level of education of users. In particular, this paper explores the susceptibility of users in Stack Overflow, a Q&A social network, to social support influence strategies for novice and expert computer programmers. In addition, we explore if first degree holders respond to the social support influence strategies the same way graduate degree holders do. Using a sample size of 282 Stack Overflow users, we constructed four models using Partial Least Squares Structural Equation Modelling (PLS-SEM) and carried out multi-group analysis between these models. The results of our analysis show that social facilitation significantly influences cooperation for novice programmers, but not for expert programmers. In addition, social learning does not significantly influence the persuasiveness of the system for expert programmers compared to users who are novice in computer programming. For the users grouped according to their highest level of education, social learning influenced cooperation among the graduate degree holders and competition influenced the graduate degree holders to continue using the system. The result of this study can provide useful guidelines to social network developers that can be used in implementing personalized influence strategies in Q&A social communities.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114054336","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}
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