Intelligent Content was proposed by Ann Rockley as content that is structurally rich and semantically aware and therefore automatically discoverable, reusable, reconfigurable, and adaptable. Currently, the majority of approaches to achieving Intelligent Content are service-side, where cloud services discover and transform content before delivering it to a client or user. An alternative approach to achieving Intelligent Content, embeds the intelligence within the content itself, imbuing the content with the ability to call services and enact discovery, reusability, reconfiguration and adaption on the client-side.Thus, the Intelligent Content can be proactive in calling cloud services and perform contextually relevant transformations or behaviours. This work explores this client-side approach to Intelligent Content and aims to examine the content-service interactions in such a system. The research follows a case-study based approach, examining the development of a client-side user model utilised to personalise and cache content on the client-side. Specifically, the research examines a propensity model, monitoring implicit user actions such as mouse movement and scrolling to create content that knows the propensity of a user to click on various page elements. Evaluation of the proposed architecture will examine the impact of content-service interaction frequency on system accuracy and response time.
Ann Rockley提出的智能内容是指结构丰富且具有语义感知的内容，因此可以自动发现、可重用、可重构和可适应。目前，实现智能内容的大多数方法都是在服务端，云服务在将内容交付给客户端或用户之前发现并转换内容。实现智能内容的另一种方法是将智能嵌入到内容本身，使内容具有调用服务和在客户端执行发现、可重用性、重新配置和自适应的能力。因此，智能内容可以主动调用云服务并执行与上下文相关的转换或行为。这项工作探索了智能内容的客户端方法，旨在检查这样一个系统中的内容-服务交互。该研究遵循基于案例研究的方法，检查用于个性化和缓存客户端内容的客户端用户模型的开发。具体来说，该研究检验了一个倾向模型，监测隐含的用户行为，如鼠标移动和滚动，以创建了解用户点击各种页面元素倾向的内容。对提议的体系结构的评估将检查内容-服务交互频率对系统准确性和响应时间的影响。
{"title":"Propensity Modelling for Intelligent Content","authors":"Rebekah Storan Clarke","doi":"10.1145/3099023.3099029","DOIUrl":"https://doi.org/10.1145/3099023.3099029","url":null,"abstract":"Intelligent Content was proposed by Ann Rockley as content that is structurally rich and semantically aware and therefore automatically discoverable, reusable, reconfigurable, and adaptable. Currently, the majority of approaches to achieving Intelligent Content are service-side, where cloud services discover and transform content before delivering it to a client or user. An alternative approach to achieving Intelligent Content, embeds the intelligence within the content itself, imbuing the content with the ability to call services and enact discovery, reusability, reconfiguration and adaption on the client-side.Thus, the Intelligent Content can be proactive in calling cloud services and perform contextually relevant transformations or behaviours. This work explores this client-side approach to Intelligent Content and aims to examine the content-service interactions in such a system. The research follows a case-study based approach, examining the development of a client-side user model utilised to personalise and cache content on the client-side. Specifically, the research examines a propensity model, monitoring implicit user actions such as mouse movement and scrolling to create content that knows the propensity of a user to click on various page elements. Evaluation of the proposed architecture will examine the impact of content-service interaction frequency on system accuracy and response time.","PeriodicalId":93391,"journal":{"name":"UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)","volume":"21 1","pages":"119-120"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78886832","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}
1. RESEARCH OVERVIEW Social networks (like Facebook and MySpace), collaborative bookmarking systems (like Bibsonomy, Delicious, and CiteULike) and Microblog systems like twitter, offer services such as sharing, commenting, tagging, publishing, rating, retweeting and discussing, that make users increasingly active. Hence, users are more and more connected. Given the tremendous amount of information, witch is generated by these platforms, there is a need to an Information Retrieval (IR) system to automatically answer user’s queries. However, IR system, in this case should take into account additional criteria, such as user’s social networks, user’s interests, user’s preferences, etc. In other words, the classical IR systems should be personalized. In personalized information retrieval, the search process considers a user’s model that covers user’s interest, behavior and history. Commonly, users models are build trough user’s query logs [10], user’s posts (such as tweets, blogs and comments) [15], user’s tags and bookmarking [1, 12, 16]. Consequently, a user is represented by a profile. The user profile is then used in IR system in two main scenarios, “query expansion” [3, 4, 7], or document “re-ranking”[6, 8, 9,
{"title":"Enhancing Personalized Document Ranking using Social Information","authors":"Nawal Ould Amer","doi":"10.1145/2930238.2930374","DOIUrl":"https://doi.org/10.1145/2930238.2930374","url":null,"abstract":"1. RESEARCH OVERVIEW Social networks (like Facebook and MySpace), collaborative bookmarking systems (like Bibsonomy, Delicious, and CiteULike) and Microblog systems like twitter, offer services such as sharing, commenting, tagging, publishing, rating, retweeting and discussing, that make users increasingly active. Hence, users are more and more connected. Given the tremendous amount of information, witch is generated by these platforms, there is a need to an Information Retrieval (IR) system to automatically answer user’s queries. However, IR system, in this case should take into account additional criteria, such as user’s social networks, user’s interests, user’s preferences, etc. In other words, the classical IR systems should be personalized. In personalized information retrieval, the search process considers a user’s model that covers user’s interest, behavior and history. Commonly, users models are build trough user’s query logs [10], user’s posts (such as tweets, blogs and comments) [15], user’s tags and bookmarking [1, 12, 16]. Consequently, a user is represented by a profile. The user profile is then used in IR system in two main scenarios, “query expansion” [3, 4, 7], or document “re-ranking”[6, 8, 9,","PeriodicalId":93391,"journal":{"name":"UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)","volume":"121 1","pages":"345-348"},"PeriodicalIF":0.0,"publicationDate":"2016-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83160871","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}
Pub Date : 2015-06-29DOI: 10.1007/978-3-319-20267-9_6
Victor Codina, Jose Mena, Luis Oliva
{"title":"Context-Aware User Modeling Strategies for Journey Plan Recommendation","authors":"Victor Codina, Jose Mena, Luis Oliva","doi":"10.1007/978-3-319-20267-9_6","DOIUrl":"https://doi.org/10.1007/978-3-319-20267-9_6","url":null,"abstract":"","PeriodicalId":93391,"journal":{"name":"UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)","volume":"66 1","pages":"68-79"},"PeriodicalIF":0.0,"publicationDate":"2015-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75881133","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}
Pub Date : 2015-06-29DOI: 10.1007/978-3-319-20267-9_28
D. Doychev, Rachael Rafter, A. Lawlor, Barry Smyth
{"title":"News Recommenders: Real-Time, Real-Life Experiences","authors":"D. Doychev, Rachael Rafter, A. Lawlor, Barry Smyth","doi":"10.1007/978-3-319-20267-9_28","DOIUrl":"https://doi.org/10.1007/978-3-319-20267-9_28","url":null,"abstract":"","PeriodicalId":93391,"journal":{"name":"UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)","volume":"6 1","pages":"337-342"},"PeriodicalIF":0.0,"publicationDate":"2015-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77636014","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}
Pub Date : 2015-06-29DOI: 10.1007/978-3-319-20267-9_24
C. Wongchokprasitti, J. Peltonen, Tuukka Ruotsalo, P. Bandyopadhyay, Giulio Jacucci, Peter Brusilovsky
{"title":"User Model in a Box: Cross-System User Model Transfer for Resolving Cold Start Problems","authors":"C. Wongchokprasitti, J. Peltonen, Tuukka Ruotsalo, P. Bandyopadhyay, Giulio Jacucci, Peter Brusilovsky","doi":"10.1007/978-3-319-20267-9_24","DOIUrl":"https://doi.org/10.1007/978-3-319-20267-9_24","url":null,"abstract":"","PeriodicalId":93391,"journal":{"name":"UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)","volume":"2 1","pages":"289-301"},"PeriodicalIF":0.0,"publicationDate":"2015-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86835433","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}
Pub Date : 2015-06-29DOI: 10.1007/978-3-319-20267-9_14
Belgin Mutlu, Eduardo Veas, C. Trattner, V. Sabol
{"title":"Towards a Recommender Engine for Personalized Visualizations","authors":"Belgin Mutlu, Eduardo Veas, C. Trattner, V. Sabol","doi":"10.1007/978-3-319-20267-9_14","DOIUrl":"https://doi.org/10.1007/978-3-319-20267-9_14","url":null,"abstract":"","PeriodicalId":93391,"journal":{"name":"UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)","volume":"25 1","pages":"169-182"},"PeriodicalIF":0.0,"publicationDate":"2015-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82771779","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}
Pub Date : 2015-06-29DOI: 10.1007/978-3-319-20267-9_32
M. Tkalcic, B. Ferwerda, D. Hauger, M. Schedl
{"title":"Personality Correlates for Digital Concert Program Notes","authors":"M. Tkalcic, B. Ferwerda, D. Hauger, M. Schedl","doi":"10.1007/978-3-319-20267-9_32","DOIUrl":"https://doi.org/10.1007/978-3-319-20267-9_32","url":null,"abstract":"","PeriodicalId":93391,"journal":{"name":"UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)","volume":"1 1","pages":"364-369"},"PeriodicalIF":0.0,"publicationDate":"2015-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83091863","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}
Pub Date : 2015-06-29DOI: 10.1007/978-3-319-20267-9_16
José San Pedro, Davide Proserpio, Nuria Oliver
{"title":"MobiScore: Towards Universal Credit Scoring from Mobile Phone Data","authors":"José San Pedro, Davide Proserpio, Nuria Oliver","doi":"10.1007/978-3-319-20267-9_16","DOIUrl":"https://doi.org/10.1007/978-3-319-20267-9_16","url":null,"abstract":"","PeriodicalId":93391,"journal":{"name":"UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)","volume":"21 1","pages":"195-207"},"PeriodicalIF":0.0,"publicationDate":"2015-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89255828","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}
Pub Date : 2015-06-29DOI: 10.1007/978-3-319-20267-9_31
Dario De Nart, Dante Degl'Innocenti, Andrea Pavan, Marco Basaldella, C. Tasso
{"title":"Modelling the User Modelling Community (and Other Communities as Well)","authors":"Dario De Nart, Dante Degl'Innocenti, Andrea Pavan, Marco Basaldella, C. Tasso","doi":"10.1007/978-3-319-20267-9_31","DOIUrl":"https://doi.org/10.1007/978-3-319-20267-9_31","url":null,"abstract":"","PeriodicalId":93391,"journal":{"name":"UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)","volume":"14 1","pages":"357-363"},"PeriodicalIF":0.0,"publicationDate":"2015-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73947552","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}
Pub Date : 2015-06-29DOI: 10.1007/978-3-319-20267-9_7
Ronny Cook, J. Kay, B. Kummerfeld
{"title":"MOOClm: User Modelling for MOOCs","authors":"Ronny Cook, J. Kay, B. Kummerfeld","doi":"10.1007/978-3-319-20267-9_7","DOIUrl":"https://doi.org/10.1007/978-3-319-20267-9_7","url":null,"abstract":"","PeriodicalId":93391,"journal":{"name":"UMAP ... proceedings of the ... Conference on User Modeling, Adaptation and Personalization. UMAP (Conference)","volume":"108 1","pages":"80-91"},"PeriodicalIF":0.0,"publicationDate":"2015-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80820429","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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