Thi Ngoc Trang Tran, A. Felfernig, Viet-Man Le, Müslüm Atas, Martin Stettinger, Ralph Samer
In group recommender systems,decision manipulation refers to an attack in which a group member makes attempts to push his/her favorite options. In this paper, we propose user interfaces to counteract decision manipulation in group recommender systems. The proposed user interfaces visualize information dimensions regarding rating adaptations of group members at different transparency levels. The results show that the user interface at the highest transparency level best helps to discourage users from decision manipulation. Besides, the ability of the user interfaces to counteract decision manipulation differs depending on the dimensions represented in the user interfaces. The information dimensions regarding "textititem ratings " and "textitgroup recommendations " have the strongest impacts on preventing users from decision manipulation.
{"title":"User Interfaces for Counteracting Decision Manipulation in Group Recommender Systems","authors":"Thi Ngoc Trang Tran, A. Felfernig, Viet-Man Le, Müslüm Atas, Martin Stettinger, Ralph Samer","doi":"10.1145/3314183.3324977","DOIUrl":"https://doi.org/10.1145/3314183.3324977","url":null,"abstract":"In group recommender systems,decision manipulation refers to an attack in which a group member makes attempts to push his/her favorite options. In this paper, we propose user interfaces to counteract decision manipulation in group recommender systems. The proposed user interfaces visualize information dimensions regarding rating adaptations of group members at different transparency levels. The results show that the user interface at the highest transparency level best helps to discourage users from decision manipulation. Besides, the ability of the user interfaces to counteract decision manipulation differs depending on the dimensions represented in the user interfaces. The information dimensions regarding \"textititem ratings \" and \"textitgroup recommendations \" have the strongest impacts on preventing users from decision manipulation.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115473260","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}
Other than private broadcasters, publicly financed broadcasters have to fulfil a public service remit. Individual playouts in public radio, therefore, consist not only of recommender content but also of 'anti-recommender content" that matches public interests. Such anti-recommender content in individual playouts may be unexpected for users and may need explanation. To find out what explanations might look like in public radio, we elicit the requirements of the public service remit for an example country. Based on these requirements, we propose an approach for designing explanations of recommendations that align with the public service remit.
{"title":"Towards Explanations of Anti-Recommender Content in Public Radio","authors":"Stefan Hirschmeier","doi":"10.1145/3314183.3323454","DOIUrl":"https://doi.org/10.1145/3314183.3323454","url":null,"abstract":"Other than private broadcasters, publicly financed broadcasters have to fulfil a public service remit. Individual playouts in public radio, therefore, consist not only of recommender content but also of 'anti-recommender content\" that matches public interests. Such anti-recommender content in individual playouts may be unexpected for users and may need explanation. To find out what explanations might look like in public radio, we elicit the requirements of the public service remit for an example country. Based on these requirements, we propose an approach for designing explanations of recommendations that align with the public service remit.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"383 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124765080","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}
Attention plays an important role in the daily lives of people and especially in learning. It may be influenced by different factors since childhood or during the aging process because of deficits such as Attention Deficit Hyperactivity Disorder (ADHD), which is responsible of learning difficulties. Serious games for attention training may be helpful to develop self-regulation skills in attention training through a personalized game experience. It can provide children with appropriate guidance to develop their self-regulation skills while enhancing their cognitive functions such as attention. The transparency of the user model may help users (both children and tutors) to follow their progression, and to develop their learning strategy. In this paper, a pilot study was conducted to evaluate the assessment step of a developed attention training serious game. The objective was to study whether the transparency of the learner model influences the users' perception of their attention and self-regulate their learning. The primary results of the pilot experiment show that open learner model influences the decision of users on difficulty level preference that may be promising in self-regulated attention training.
{"title":"Personalized Serious Games for Self-regulated Attention Training","authors":"Nadia Hocine","doi":"10.1145/3314183.3323458","DOIUrl":"https://doi.org/10.1145/3314183.3323458","url":null,"abstract":"Attention plays an important role in the daily lives of people and especially in learning. It may be influenced by different factors since childhood or during the aging process because of deficits such as Attention Deficit Hyperactivity Disorder (ADHD), which is responsible of learning difficulties. Serious games for attention training may be helpful to develop self-regulation skills in attention training through a personalized game experience. It can provide children with appropriate guidance to develop their self-regulation skills while enhancing their cognitive functions such as attention. The transparency of the user model may help users (both children and tutors) to follow their progression, and to develop their learning strategy. In this paper, a pilot study was conducted to evaluate the assessment step of a developed attention training serious game. The objective was to study whether the transparency of the learner model influences the users' perception of their attention and self-regulate their learning. The primary results of the pilot experiment show that open learner model influences the decision of users on difficulty level preference that may be promising in self-regulated attention training.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125393080","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 widely agreed that museums and other cultural heritage venues should provide visitors with personalised interaction and services such as personalised mobile guides, although currently most do not. Since museum visitors are typically first-time visitors and since their visit is for a relatively short session, personalisation should use initial interaction data to associate the user with a particular persona and thereby infer other facts about the user's preferences and needs. In this paper we report a questionnaire-based study carried out with 105 visitors of a Science and Technology Centre to examine the minimal features needed to identify visitor personas. We find that museum visitors can be clustered by their visit motivation and perceived success factors; these clusters are found to correspond both with Falk's visitor categorisation and a prior classification of exploration styles. Consequently, these two features can be used to reliably identify the visitor persona, and therefore, can be used for user modeling.
{"title":"Using Personas to Model Museum Visitors","authors":"Moneerah Almeshari, J. Dowell, J. Nyhan","doi":"10.1145/3314183.3323867","DOIUrl":"https://doi.org/10.1145/3314183.3323867","url":null,"abstract":"It is widely agreed that museums and other cultural heritage venues should provide visitors with personalised interaction and services such as personalised mobile guides, although currently most do not. Since museum visitors are typically first-time visitors and since their visit is for a relatively short session, personalisation should use initial interaction data to associate the user with a particular persona and thereby infer other facts about the user's preferences and needs. In this paper we report a questionnaire-based study carried out with 105 visitors of a Science and Technology Centre to examine the minimal features needed to identify visitor personas. We find that museum visitors can be clustered by their visit motivation and perceived success factors; these clusters are found to correspond both with Falk's visitor categorisation and a prior classification of exploration styles. Consequently, these two features can be used to reliably identify the visitor persona, and therefore, can be used for user modeling.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121327617","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}
Pooja P. Bovard, Harry T. Gao, Jason B. Goodman, Zahar Prasov
While software tools can be very powerful, a one-size-fits-all approach does not work because individual needs vary over time. Co-Adapt is a software framework that learns from user activity and adjusts the interface in real time to suit changing needs. Prior research has shown that the best in class user interfaces (UI) are not as effective across multiple groups of people. We performed three experiments by integrating with three distinct UI prototypes that tested iteratively tailored software to show the effectiveness of different UI presentations. Co-Adapt demonstrates that a multitude of UIs improve usability, which in some instances lead to greater tool adoption. Our success across three domains suggests generalizability of the framework and is promising for further experimentation across other application areas.
{"title":"Co-Adapt: Continuously Tailored Software","authors":"Pooja P. Bovard, Harry T. Gao, Jason B. Goodman, Zahar Prasov","doi":"10.1145/3314183.3324971","DOIUrl":"https://doi.org/10.1145/3314183.3324971","url":null,"abstract":"While software tools can be very powerful, a one-size-fits-all approach does not work because individual needs vary over time. Co-Adapt is a software framework that learns from user activity and adjusts the interface in real time to suit changing needs. Prior research has shown that the best in class user interfaces (UI) are not as effective across multiple groups of people. We performed three experiments by integrating with three distinct UI prototypes that tested iteratively tailored software to show the effectiveness of different UI presentations. Co-Adapt demonstrates that a multitude of UIs improve usability, which in some instances lead to greater tool adoption. Our success across three domains suggests generalizability of the framework and is promising for further experimentation across other application areas.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126096458","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}
A. Origlia, Renata Savy, Violetta Cataldo, Loredana Schettino, Alessandro Ansani, I. Sessa, A. Chiera, I. Poggi
Investigating the multimodal communication of Tourist Guides to implement a Virtual Tourist Guide leading tourists in three Italian Charterhouses, the paper focuses on an aspect of the human guide's speech that would be useful to create a very realistic Virtual Guide: linguistic disfluencies. On a corpus of three guided tours in S. Martino Charterhouse (Naples) an analysis is presented of the guides' pauses and their concomitant gestures.
{"title":"Human, All Too Human: Towards a Disfluent Virtual Tourist Guide","authors":"A. Origlia, Renata Savy, Violetta Cataldo, Loredana Schettino, Alessandro Ansani, I. Sessa, A. Chiera, I. Poggi","doi":"10.1145/3314183.3323866","DOIUrl":"https://doi.org/10.1145/3314183.3323866","url":null,"abstract":"Investigating the multimodal communication of Tourist Guides to implement a Virtual Tourist Guide leading tourists in three Italian Charterhouses, the paper focuses on an aspect of the human guide's speech that would be useful to create a very realistic Virtual Guide: linguistic disfluencies. On a corpus of three guided tours in S. Martino Charterhouse (Naples) an analysis is presented of the guides' pauses and their concomitant gestures.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132626271","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 an approach and methodology for user-centred evaluation of adaptive systems. In contrast to layered evaluation approaches that decompose adaptation into its constituents, our approach conceptualises the quality and benefit for the user into separate evaluation qualities for a comprehensive and multifaceted evaluation. Instruments of different modalities are used to measure these qualities from the user perspective. A service is presented that takes up this approach and enables time- and cost-efficient evaluation by defining and re-using evaluation qualities and instruments, as well as collecting and analysing data based on these definitions. This approach allows to compare different adaptive systems by using the same qualities and adapting the instruments to the specific characteristics of the particular adaptive system.
{"title":"Towards a Multi-Modal Methodology for User-Centred Evaluation of Adaptive Systems","authors":"A. Nussbaumer, Christina M. Steiner, Owen Conlan","doi":"10.1145/3314183.3323681","DOIUrl":"https://doi.org/10.1145/3314183.3323681","url":null,"abstract":"This paper presents an approach and methodology for user-centred evaluation of adaptive systems. In contrast to layered evaluation approaches that decompose adaptation into its constituents, our approach conceptualises the quality and benefit for the user into separate evaluation qualities for a comprehensive and multifaceted evaluation. Instruments of different modalities are used to measure these qualities from the user perspective. A service is presented that takes up this approach and enables time- and cost-efficient evaluation by defining and re-using evaluation qualities and instruments, as well as collecting and analysing data based on these definitions. This approach allows to compare different adaptive systems by using the same qualities and adapting the instruments to the specific characteristics of the particular adaptive system.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116692184","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}
Emily Sullivan, D. Bountouridis, Jaron Harambam, Shabnam Najafian, Felicia Loecherbach, M. Makhortykh, Domokos M. Kelen, Daricia Wilkinson, David Graus, N. Tintarev
Personalized content provided by recommender systems is an integral part of the current online news reading experience. However, news recommender systems are criticized for their 'black-box' approach to data collection and processing, and for their lack of explainability and transparency. This paper focuses on explaining user profiles constructed from aggregated reading behavior data, used to provide content-based recommendations. The paper makes a first step toward consolidating epistemic values of news providers and news readers. We present an evaluation of an explanation interface reflecting these values, and find that providing users with different goals for self-actualization (i.e., Broaden Horizons vs. Discover the Unexplored) influences their reading intentions for news recommendations.
{"title":"Reading News with a Purpose: Explaining User Profiles for Self-Actualization","authors":"Emily Sullivan, D. Bountouridis, Jaron Harambam, Shabnam Najafian, Felicia Loecherbach, M. Makhortykh, Domokos M. Kelen, Daricia Wilkinson, David Graus, N. Tintarev","doi":"10.1145/3314183.3323456","DOIUrl":"https://doi.org/10.1145/3314183.3323456","url":null,"abstract":"Personalized content provided by recommender systems is an integral part of the current online news reading experience. However, news recommender systems are criticized for their 'black-box' approach to data collection and processing, and for their lack of explainability and transparency. This paper focuses on explaining user profiles constructed from aggregated reading behavior data, used to provide content-based recommendations. The paper makes a first step toward consolidating epistemic values of news providers and news readers. We present an evaluation of an explanation interface reflecting these values, and find that providing users with different goals for self-actualization (i.e., Broaden Horizons vs. Discover the Unexplored) influences their reading intentions for news recommendations.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117250936","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}
Panagiotis Germanakos, V. Dimitrova, B. Steichen, A. Piotrkowicz
It is our great pleasure to welcome you to the 4th International Workshop on Human Aspects in Adaptive and Personalized Interactive Environments (HAAPIE 2019). HAAPIE 2019 (http://haapie.cs.ucy.ac.cy) is a full-day workshop held on 09 June 2019 in conjunction with the 27th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2019), 09-12 June 2019 in Larnaca, Cyprus. 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" approach/idea, 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 in order to share ideas and experiences, lessons learned, approaches and results that could substantially contribute to the broader UMAP community. This year we received 10 submissions from all around the world covering a broad range of topics on the workshop's research themes. 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 2019 HAAPIE (Human Aspects in Adaptive and Personalized Interactive Environments) Workshop Chairs' Welcome","authors":"Panagiotis Germanakos, V. Dimitrova, B. Steichen, A. Piotrkowicz","doi":"10.1145/3314183.3323856","DOIUrl":"https://doi.org/10.1145/3314183.3323856","url":null,"abstract":"It is our great pleasure to welcome you to the 4th International Workshop on Human Aspects in Adaptive and Personalized Interactive Environments (HAAPIE 2019). HAAPIE 2019 (http://haapie.cs.ucy.ac.cy) is a full-day workshop held on 09 June 2019 in conjunction with the 27th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2019), 09-12 June 2019 in Larnaca, Cyprus. 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\" approach/idea, 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 in order to share ideas and experiences, lessons learned, approaches and results that could substantially contribute to the broader UMAP community. This year we received 10 submissions from all around the world covering a broad range of topics on the workshop's research themes. 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":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132237341","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}
The incidence of physical inactivity, obesity and non-communicable diseases is on the rise globally due to the sedentary lifestyles occasioned by modernity and technology. As a means of tackling the inactivity problem, which is almost becoming a global epidemic, research has shown that persuasive technology holds bright prospects. However, in the physical activity domain, there is limited research on users' persuasion profiles and the differences between users who are currently exercising (acting users) and those who have the intentions to exercise in the future (non-acting users). To bridge this gap, we conducted a study among 190 participants resident in two individualist countries to determine the susceptibility profile of both user types and their differences. We based our study on storyboards, illustrating six commonly employed persuasive features in fitness apps. The results of our analysis showed that both user types are most likely to be susceptible to Goal-Setting/Self-Monitoring, followed by Reward and Competition, and least likely to be susceptible to Cooperation, Social Comparison and Social Learning. In particular, acting users are more likely to be susceptible to Social Learning than non-acting us-ers. Overall, our findings suggest that, irrespective of user type, personal features will be more likely effective than social features among users from individualist cultures. We discuss the implications of our findings in the context of fitness apps design.
{"title":"Susceptibility to Fitness App's Persuasive Features: Differences Between Acting and Non-Acting Users","authors":"Kiemute Oyibo, I. Adaji, Julita Vassileva","doi":"10.1145/3314183.3323851","DOIUrl":"https://doi.org/10.1145/3314183.3323851","url":null,"abstract":"The incidence of physical inactivity, obesity and non-communicable diseases is on the rise globally due to the sedentary lifestyles occasioned by modernity and technology. As a means of tackling the inactivity problem, which is almost becoming a global epidemic, research has shown that persuasive technology holds bright prospects. However, in the physical activity domain, there is limited research on users' persuasion profiles and the differences between users who are currently exercising (acting users) and those who have the intentions to exercise in the future (non-acting users). To bridge this gap, we conducted a study among 190 participants resident in two individualist countries to determine the susceptibility profile of both user types and their differences. We based our study on storyboards, illustrating six commonly employed persuasive features in fitness apps. The results of our analysis showed that both user types are most likely to be susceptible to Goal-Setting/Self-Monitoring, followed by Reward and Competition, and least likely to be susceptible to Cooperation, Social Comparison and Social Learning. In particular, acting users are more likely to be susceptible to Social Learning than non-acting us-ers. Overall, our findings suggest that, irrespective of user type, personal features will be more likely effective than social features among users from individualist cultures. We discuss the implications of our findings in the context of fitness apps design.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134272000","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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