Relevant bibliographies by topics / User adaptation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'User adaptation'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "User adaptation"

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Shoham, Snunith. "User Adaptation to Public Services." Journal of Library Administration 6, no. 2 (1985): 101–9. http://dx.doi.org/10.1300/j111v06n02_09.

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Nilsson, Erik G., Jacqueline Floch, Svein Hallsteinsen, and Erlend Stav. "Model-based user interface adaptation." Computers & Graphics 30, no. 5 (2006): 692–701. http://dx.doi.org/10.1016/j.cag.2006.07.003.

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Eid, Mustafa Ismail Mustafa, and Hani I. Abbas. "User adaptation and ERP benefits: moderation analysis of user experience with ERP." Kybernetes 46, no. 3 (2017): 530–49. http://dx.doi.org/10.1108/k-08-2015-0212.

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Purpose The purpose of the study is to measure the impact of user adaptation of enterprise resources planning (ERP) post implementation through an appreciation of the benefits ERP provides to its users in Saudi Arabia (SA). The study will also measure the moderation effect of user experience with ERP on the relationship between user adaptation of ERP and user benefits from ERP. Design/methodology/approach The authors conducted a survey questionnaire study of 253 ERP users and tested the research model through the application of a hierarchical multiple regression analysis. Findings The findings show that user adaptation of ERP has a strong positive impact on ERP user benefits. In addition, it is found that the level of user experience with ERP has no significant moderation effect on the relationship between user adaptation of ERP and ERP user benefits. Practical implications The study findings suggest that functional management should develop appropriate strategies to effectively manage user adaptation of ERP. An equally important implication is for the ERP vendors to consider making their ERP systems as flexible and maintainable as possible by offering effective tools to easily accommodate changes in user requirements with minimum effort and cost. Originality/value This study provides insights into the inter-relationships between the motivation for improving user adaptation of ERP and gaining more benefits from ERP systems. It will also extend our understanding of the moderation effect of user experience with ERP on the relationship between user adaptation of ERP and ERP user benefits in developing countries.
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Benyon, David, Thomas Kühme, Uwe Malinowsi, and Piyawadee Noi Sukaviriya. "Computer-aided adaptation of user interfaces." ACM SIGCHI Bulletin 26, no. 1 (1994): 25–27. http://dx.doi.org/10.1145/181526.181529.

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Di Cagno, Gianluca, Cyril Concolato, and Jean Claude Dufourd. "Multimedia adaptation in end-user terminals." Signal Processing: Image Communication 21, no. 3 (2006): 200–216. http://dx.doi.org/10.1016/j.image.2005.09.005.

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Delic, Vlado, Milan Gnjatovic, Niksa Jakovljevic, Branislav Popovic, Ivan Jokic, and Milana Bojanic. "User-awareness and adaptation in conversational agents." Facta universitatis - series: Electronics and Energetics 27, no. 3 (2014): 375–87. http://dx.doi.org/10.2298/fuee1403375d.

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This paper considers the research question of developing user-aware and adaptive conversational agents. The conversational agent is a system which is user-aware to the extent that it recognizes the user identity and his/her emotional states that are relevant in a given interaction domain. The conversational agent is user-adaptive to the extent that it dynamically adapts its dialogue behavior according to the user and his/her emotional state. The paper summarizes some aspects of our previous work and presents work-in-progress in the field of speech-based human-machine interaction. It focuses particularly on the development of speech recognition modules in cooperation with both modules for emotion recognition and speaker recognition, as well as the dialogue management module. Finally, it proposes an architecture of a conversational agent that integrates those modules and improves each of them based on some kind of synergies among themselves.
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López-Jaquero, Víctor, Vivian Genaro Motti, Francisco Montero, and Pascual González López. "Gisatie: A User Interface Adaptation Life-Cycle." International Joural of User-System Interaction 14, no. 1 (2021): 1–29. http://dx.doi.org/10.37789/ijusi.2021.14.1.1.

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Jokinen, Kristiina. "Adaptation and user expertise modelling in AthosMail." Universal Access in the Information Society 4, no. 4 (2006): 374–92. http://dx.doi.org/10.1007/s10209-005-0002-z.

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Barakonyi, István, and Dieter Schmalstieg. "Augmented reality agents for user interface adaptation." Computer Animation and Virtual Worlds 19, no. 1 (2008): 23–35. http://dx.doi.org/10.1002/cav.220.

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Bartling, Mona, Anthony C. Robinson, Harold Achicanoy Estrella, and Anton Eitzinger. "The impact of user characteristics of smallholder farmers on user experiences with collaborative map applications." PLOS ONE 17, no. 3 (2022): e0264426. http://dx.doi.org/10.1371/journal.pone.0264426.

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In the future, farmers will have increasing opportunities to use collaborative smartphone applications for agricultural management. Geospatial information in combination with agricultural-relevant information is a great source of knowledge for farmers. Including maps in collaborative mobile agriculture applications benefits communication processes related to agricultural-relevant questions. Ensuring a positive user experience with map interfaces depends on their design. To develop design guidelines for map-oriented mobile agricultural applications, this study evaluates 24 different map design variations (varying in their elements and degrees of complexity) and characterizes their user experience with 72 coffee farmers as study participants. Our findings show that the most crucial factors for a positive user experience were restricted interactivity, simple tasks to conduct (selecting single point features), and a simplified base map style, highlighting relevant landmarks. Since our farmers consisted primarily of less-experienced smartphone and map users, our findings may also be helpful for users in general, sharing similar user characteristics. While empirical, in-situ studies pose many challenges, they provide relevant insights into the real use situation and user behavior of mobile map applications. Our findings help establish some basic principles for designing map adaptations, serving as a guideline for creating effective mapping applications, which adapt to the farmers’ contextual factors. Based on our study results, we suggest future research for continuing conceptualizing principles of map design adaptation and support this effort through empirical, in-situ studies for relating contextual user factors to the adaptation behavior of map applications.
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Dissertations / Theses on the topic "User adaptation"

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Myrlund, Jonas. "User Adaptation in Anonymous Web Applications." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-27333.

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The goal of the project in this thesis is to explore the viability of an approach to user adaptation where the application context is significantly more constraining than in most cases seen in previous academic work.The project describes and implements a system for rolling out product features incrementally in an optimal way, based on feature adoption statistics within user segments. In other words, the described system should allow for simple personalization of the product.When analyzing the adoption rate of new features, we find that there are indeed clear differences between the identified user segments. However, limitations due to the lack of stable user identity make adaptation approaches based on these data unfeasable in practice.
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Cocea, Mihaela. "User modelling and adaptation in exploratory learning." Thesis, Birkbeck (University of London), 2011. http://eprints.port.ac.uk/12174/.

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User modelling in Exploratory Learning Environments (ELEs) is an emerging field with several challenges to be addressed. Due to the freedom given to learners, the amount of information generated is very large, making the modelling process very challenging. Consequently, only relevant information should be used in the user modelling process. This, however, leads to other challenges such as identification of relevant information, finding an optimal knowledge representation and defining an inference mechanism by which this knowledge is used in diagnosing the learner. This thesis addresses the challenges of user modelling in ELEs by monitoring learners' behaviour and taking into account only relevant actions in the context of an ELE for the domain of mathematical generalisation. An iterative approach was used, in line with the iterative design of the ELE. The modelling mechanism employed a modified version of Case-based Reasoning (CBR) and was evaluated using pedagogical scenarios and data from simulated and real students. This approach has the advantage of storing only relevant information and allows learner diagnosis during as well as at the end of a task. The user model was further exploited to support learning related activities, such as prioritising feedback and grouping for collaboration. For feedback prioritisation, a mechanism based on Multi-criteria Decision Making was developed and tested with the help of educational experts. The grouping for collaboration approach was inspired from Group Technology, a method from cellular manufacturing systems, and its testing showed it produces meaningful groups. Both the feedback prioritisation and the grouping for collaboration mechanisms propose solutions that are particularly relevant for ELEs by considering pertinent criteria for this type of learning. To ensure optimal coverage of the knowledge base, the user modelling approach was enhanced with adaptive mechanisms for expanding the knowledge base, which was tested on real and simulated data. This approach ensures that learner diagnostic is possible when the initial knowledge base is small and/or new behaviours are encountered over time.
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Marín, Isern Lucas. "Dynamic adaptation of user profiles in recommender systems." Doctoral thesis, Universitat Rovira i Virgili, 2013. http://hdl.handle.net/10803/123905.

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In a period of time in which the content available through the Internet increases exponentially and is more easily accessible every day, techniques for aiding the selection and extraction of important and personalised information are of vital importance. Recommender Systems (RS) appear as a tool to help the user in a decision making process by evaluating a set of objects or alternatives and aiding the user at choosing which one/s of them suits better his/her interests or preferences. Those preferences need to be accurate enough to produce adequate recommendations and should be updated if the user changes his/her likes or if they are incorrect or incomplete. In this work an adequate model for managing user preferences in a multi-attribute (numerical and categorical) environment is presented to aid at providing recommendations in those kinds of contexts. The evaluation process of the recommender system designed is supported by a new aggregation operator (Unbalanced LOWA) that enables the combination of the information that defines an alternative into a single value, which then is used to rank the whole set of alternatives. After the recommendation has been made, learning processes have been designed to evaluate the user interaction with the system to find out, in a dynamic and unsupervised way, if the user profile in which the recommendation process relies on needs to be updated with new preferences. The work detailed in this document also includes extensive evaluation and testing of all the elements that take part in the recommendation and learning processes.
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Karagiannidis, Charalampos. "Supporting run-time adaptation in intelligent user interfaces." Thesis, University of Kent, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242908.

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Antona, Margherita Giovanna. "Process-oriented tool support for user interface adaptation design." Thesis, University of Kent, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409164.

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Carrara, Nicolas. "Reinforcement learning for dialogue systems optimization with user adaptation." Thesis, Lille 1, 2019. http://www.theses.fr/2019LIL1I071/document.

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Les systèmes d’intelligence artificielle les plus puissants utilisent désormais des modèles statistiques. Afin de construire des modèles efficaces, ces systèmes doivent collecter une quantité substantielle de données issues de l’environnement. Les assistants personnels, maisons connectées, serveurs vocaux et autres systèmes de dialogue ne font pas exception. Ces systèmes ont pour vocation d’interagir avec des humains, et pour cela, leurs données d’apprentissage se doivent d’être collectées avec ces mêmes humains. Parce que le nombre d’interactions avec une seule personne est assez faible, l’approche usuelle pour augmenter le jeu de données consiste à agréger les données de tous les utilisateurs.Une des limitations de cette approche vient du fait que, par construction, les modèles entraînés ainsi ne sont efficaces qu’avec un humain "moyen" et n’incluent pas de système d’adaptation ; cette faiblesse entraîne la restriction du service à certains groupes de personnes; Par conséquent, cela réduit l’ensemble des utilisateurs et provoque des problèmes d’inclusion. La présente thèse propose des solutions impliquant la construction de systèmes de dialogue combinant l’apprentissage par transfert et l’apprentissage parrenforcement. La thèse explore deux pistes de recherche : La première consiste à inclure un mécanisme d’adaptation dès les premières interactions avec un nouvel utilisateur. Pour ce faire, nous utilisons la connaissance accumulée avec des utilisateurs déjà connus du système. La question sous-jacente est la suivante : comment gérer l’évolution du système suite à une croissance interrompue d’utilisateurs et donc de connaissance? La première approche implique le clustering des systèmes de dialogue (chacun étant spécialisé pour un utilisateur) en fonction de leurs stratégies. Nous démontrons que la méthode améliore la qualité des dialogues en interagissant avec des modèles à base de règles et des modèles d’humains. La seconde approche propose d’inclure un mécanisme d’apprentissage par transfert dans l’exécution d’un algorithme d’apprentissage profond par renforcement, Deep Q-learning. La seconde piste avance l’idée selon laquelle les premières interactions avec un nouvel utilisateur devraient être gérées par un système de dialogue sécurisé et précautionneux avant d’utiliser un système de dialogue spécialisé. L’approche se divise en deux étapes. La première étape consiste à apprendre une stratégie sécurisée avec de l’apprentissage par renforcement. À cet effet, nous proposons un nouveau framework d’apprentissage par renforcement sous contrainte en états continus ainsi que des algorithmes les solutionnant. En particulier, nous validons, en termes de sécurité et d’efficacité, une extension de Fitted-Q pour les deux applications sous contraintes : les systèmes de dialogue et la conduite autonome. La deuxième étape implique l’utilisation de ces stratégies sécurisées lors des premières interactions avec un nouvel utilisateur ; cette méthode est une extension de l’algorithme classique d’exploration, ε-greedy<br>The most powerful artificial intelligence systems are now based on learned statistical models. In order to build efficient models, these systems must collect a huge amount of data on their environment. Personal assistants, smart-homes, voice-servers and other dialogue applications are no exceptions to this statement. A specificity of those systems is that they are designed to interact with humans, and as a consequence, their training data has to be collected from interactions with these humans. As the number of interactions with a single person is often too scarce to train a proper model, the usual approach to maximise the amount of data consists in mixing data collected with different users into a single corpus. However, one limitation of this approach is that, by construction, the trained models are only efficient with an "average" human and do not include any sort of adaptation; this lack of adaptation makes the service unusable for some specific group of persons and leads to a restricted customers base and inclusiveness problems. This thesis proposes solutions to construct Dialogue Systems that are robust to this problem by combining Transfer Learning and Reinforcement Learning. It explores two main ideas: The first idea of this thesis consists in incorporating adaptation in the very first dialogues with a new user. To that extend, we use the knowledge gathered with previous users. But how to scale such systems with a growing database of user interactions? The first proposed approach involves clustering of Dialogue Systems (tailored for their respective user) based on their behaviours. We demonstrated through handcrafted and real user-models experiments how this method improves the dialogue quality for new and unknown users. The second approach extends the Deep Q-learning algorithm with a continuous transfer process.The second idea states that before using a dedicated Dialogue System, the first interactions with a user should be handled carefully by a safe Dialogue System common to all users. The underlying approach is divided in two steps. The first step consists in learning a safe strategy through Reinforcement Learning. To that extent, we introduced a budgeted Reinforcement Learning framework for continuous state space and the underlying extensions of classic Reinforcement Learning algorithms. In particular, the safe version of the Fitted-Q algorithm has been validated, in term of safety and efficiency, on a dialogue system tasks and an autonomous driving problem. The second step consists in using those safe strategies when facing new users; this method is an extension of the classic ε-greedy algorithm
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Xia, Qian, and n/a. "Leveraging Single-User Applications for Multi-User Collaboration." Griffith University. School of Information and Communication Technology, 2006. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20070216.093300.

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People rely on off-the-shelf commercial single-user software systems in their daily lives and work to perform single-user tasks. People also need groupware systems to perform collaborative or group tasks. The goal of this thesis work is to develop innovative techniques for building computer applications that combine conventional single-user functionalities with advanced collaboration capabilities to effectively support people's individual and group work. This thesis work contributes an innovative Transparent Adaptation (TA) approach and associated supporting techniques that can be used to convert existing or new single-user applications into real-time multi-user collaborative versions without changing their source code. The transparently adapted collaborative systems not only support unconstrained collaboration and other collaboration features that were previously seen only in advanced groupware research prototypes, but also maintain the conventional functionalities and interface features that were previously seen only in commercial off-the-shelf single-user applications. Major technical contributions of the TA approach include techniques for adapting the single-user application programming interface to the data and operation models of the underlying generic collaboration technique and a generic system architecture for collaborative systems. The Operation Transformation (OT) technique has been chosen as the underlying collaboration technique for the TA approach due to its capability of supporting unconstrained collaboration and application independence. This thesis work has also made important contributions to OT by extending OT from supporting only collaborative plain text editing to supporting collaboration on complex data structures and comprehensive functionalities. To support the adaptation of complex data and operation models in a range of applications, this thesis work has contributed a package of advanced adaptation techniques for collaborative table editing and graphic object grouping. These techniques have not only increased the capability of TA, but have also advanced the state-of-the-art of collaborative editing techniques. To facilitate natural and smooth collaboration, this thesis work has contributed a multi-functional workspace awareness framework which is able to reduce the effort for developing workspace awareness features, and to be extended to support new workspace awareness features. Most importantly, this framework is able to deliver correct and precise workspace awareness information in the face of dynamic content and view changes in TA-based systems, which is an innovative feature unavailable in existing techniques. The TA approach and supporting techniques were developed and tested in the process of transparently converting two commercial off-the-shelf single-user applications - Microsoft Word and PowerPoint - into real-time collaborative applications, called CoWord and CoPowerPoint, respectively. CoWord and CoPowerPoint not only retain the functionalities and the 'look-and-feel' of their single-user counterparts, but also provide advanced multi-user collaboration capabilities for supporting multiple interaction paradigms, ranging from concurrent and free interaction to sequential and synchronized interaction, and for supporting detailed workspace awareness, including multi-user tele-pointers and radar views. The TA-based collaborative system architecture and the generic collaboration engine software component developed from this work can be reused in adapting a wide range of single-user applications.
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Xia, Qian. "Leveraging Single-User Applications for Multi-User Collaboration." Thesis, Griffith University, 2006. http://hdl.handle.net/10072/366194.

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People rely on off-the-shelf commercial single-user software systems in their daily lives and work to perform single-user tasks. People also need groupware systems to perform collaborative or group tasks. The goal of this thesis work is to develop innovative techniques for building computer applications that combine conventional single-user functionalities with advanced collaboration capabilities to effectively support people's individual and group work. This thesis work contributes an innovative Transparent Adaptation (TA) approach and associated supporting techniques that can be used to convert existing or new single-user applications into real-time multi-user collaborative versions without changing their source code. The transparently adapted collaborative systems not only support unconstrained collaboration and other collaboration features that were previously seen only in advanced groupware research prototypes, but also maintain the conventional functionalities and interface features that were previously seen only in commercial off-the-shelf single-user applications. Major technical contributions of the TA approach include techniques for adapting the single-user application programming interface to the data and operation models of the underlying generic collaboration technique and a generic system architecture for collaborative systems. The Operation Transformation (OT) technique has been chosen as the underlying collaboration technique for the TA approach due to its capability of supporting unconstrained collaboration and application independence. This thesis work has also made important contributions to OT by extending OT from supporting only collaborative plain text editing to supporting collaboration on complex data structures and comprehensive functionalities. To support the adaptation of complex data and operation models in a range of applications, this thesis work has contributed a package of advanced adaptation techniques for collaborative table editing and graphic object grouping. These techniques have not only increased the capability of TA, but have also advanced the state-of-the-art of collaborative editing techniques. To facilitate natural and smooth collaboration, this thesis work has contributed a multi-functional workspace awareness framework which is able to reduce the effort for developing workspace awareness features, and to be extended to support new workspace awareness features. Most importantly, this framework is able to deliver correct and precise workspace awareness information in the face of dynamic content and view changes in TA-based systems, which is an innovative feature unavailable in existing techniques. The TA approach and supporting techniques were developed and tested in the process of transparently converting two commercial off-the-shelf single-user applications - Microsoft Word and PowerPoint - into real-time collaborative applications, called CoWord and CoPowerPoint, respectively. CoWord and CoPowerPoint not only retain the functionalities and the 'look-and-feel' of their single-user counterparts, but also provide advanced multi-user collaboration capabilities for supporting multiple interaction paradigms, ranging from concurrent and free interaction to sequential and synchronized interaction, and for supporting detailed workspace awareness, including multi-user tele-pointers and radar views. The TA-based collaborative system architecture and the generic collaboration engine software component developed from this work can be reused in adapting a wide range of single-user applications.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Information and Communication Technology<br>Full Text
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Kämpfe, Tanja Katharina. "Content-based image retrieval and the use of neural networks for user adaptation." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=98305066X.

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Rashidi, Parisa. "Smart home adaptation based on explicit and implicit user feedback." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Thesis/Fall2007/p_rashidi_120707.pdf.

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Books on the topic "User adaptation"

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Carberry, Sandra, Stephan Weibelzahl, Alessandro Micarelli, and Giovanni Semeraro, eds. User Modeling, Adaptation, and Personalization. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38844-6.

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Houben, Geert-Jan, Gord McCalla, Fabio Pianesi, and Massimo Zancanaro, eds. User Modeling, Adaptation, and Personalization. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02247-0.

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Masthoff, Judith, Bamshad Mobasher, Michel C. Desmarais, and Roger Nkambou, eds. User Modeling, Adaptation, and Personalization. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31454-4.

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De Bra, Paul, Alfred Kobsa, and David Chin, eds. User Modeling, Adaptation, and Personalization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13470-8.

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Ricci, Francesco, Kalina Bontcheva, Owen Conlan, and Séamus Lawless, eds. User Modeling, Adaptation and Personalization. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20267-9.

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Dimitrova, Vania, Tsvi Kuflik, David Chin, Francesco Ricci, Peter Dolog, and Geert-Jan Houben, eds. User Modeling, Adaptation, and Personalization. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08786-3.

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Martín, Estefanía, Pablo A. Haya, and Rosa M. Carro, eds. User Modeling and Adaptation for Daily Routines. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4778-7.

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Constantinos, Mourlas, and Germanakos Panagiotis, eds. Intelligent user interfaces: Adaptation and personalization systems and technologies. Information Science Reference, 2008.

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Wu, Xinran. Pricing and user adaptation for smooth and bursty traffic sources. National Library of Canada, 2002.

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Martín, Estefanía. User Modeling and Adaptation for Daily Routines: Providing Assistance to People with Special Needs. Springer London, 2013.

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Book chapters on the topic "User adaptation"

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Wasinger, Rainer, Michael Fry, Judy Kay, and Bob Kummerfeld. "User Modelling Ecosystems: A User-Centred Approach." In User Modeling, Adaptation, and Personalization. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31454-4_31.

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Cristea, Alexandra, and Licia Calvi. "The Three Layers of Adaptation Granularity." In User Modeling 2003. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44963-9_4.

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Bertini, Enrico, Andrea Calì, Tiziana Catarci, Silvia Gabrielli, and Stephen Kimani. "Interaction-Based Adaptation for Small Screen Devices." In User Modeling 2005. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11527886_36.

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Lehmann, Janette, Mounia Lalmas, Elad Yom-Tov, and Georges Dupret. "Models of User Engagement." In User Modeling, Adaptation, and Personalization. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31454-4_14.

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Terzi, Maria, Matthew Rowe, Maria-Angela Ferrario, and Jon Whittle. "Text-Based User-kNN: Measuring User Similarity Based on Text Reviews." In User Modeling, Adaptation, and Personalization. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08786-3_17.

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Peng, Xiaoyan, and Daniel L. Silver. "User Control over User Adaptation: A Case Study." In User Modeling 2005. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11527886_61.

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Bohnert, Fabian, and Ingrid Zukerman. "A User-and Item-Aware Weighting Scheme for Combining Predictive User Models." In User Modeling, Adaptation, and Personalization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13470-8_11.

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Herder, Eelco, Patrick Siehndel, and Ricardo Kawase. "Predicting User Locations and Trajectories." In User Modeling, Adaptation, and Personalization. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08786-3_8.

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Plumbaum, Till. "Semantically-Enhanced Ubiquitous User Modeling." In User Modeling, Adaptation, and Personalization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13470-8_41.

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Peska, Ladislav. "User Feedback and Preferences Mining." In User Modeling, Adaptation, and Personalization. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31454-4_41.

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Conference papers on the topic "User adaptation"

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Smith, Catherine L., and Paul B. Kantor. "User adaptation." In the 31st annual international ACM SIGIR conference. ACM Press, 2008. http://dx.doi.org/10.1145/1390334.1390362.

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Tsandilas, Theophanis, and m. c. schraefel. "User-controlled link adaptation." In the fourteenth ACM conference. ACM Press, 2003. http://dx.doi.org/10.1145/900051.900086.

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Yamamoto, Shuhei, Noriko Kando, and Tetsuji Satoh. "User-User Relationship Migration Observed in Communication Activity." In UMAP '16: User Modeling, Adaptation and Personalization Conference. ACM, 2016. http://dx.doi.org/10.1145/2930238.2930268.

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Zheng, Yong, Bamshad Mobasher, and Robin Burke. "User-Oriented Context Suggestion." In UMAP '16: User Modeling, Adaptation and Personalization Conference. ACM, 2016. http://dx.doi.org/10.1145/2930238.2930252.

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Yamabe, Tetsuo, and Kiyotaka Takahashi. "Experiments in Mobile User Interface Adaptation for Walking Users." In The 2007 International Conference on Intelligent Pervasive Computing (IPC 2007). IEEE, 2007. http://dx.doi.org/10.1109/ipc.2007.94.

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Gurbanov, Tural, Francesco Ricci, and Meinhard Ploner. "Modeling and Predicting User Actions in Recommender Systems." In UMAP '16: User Modeling, Adaptation and Personalization Conference. ACM, 2016. http://dx.doi.org/10.1145/2930238.2930284.

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Gossen, Tatiana, Marcus Nitsche, Jana Vos, and Andreas Nürnberger. "Adaptation of a Search User Interface towards User Needs." In the Symposium. ACM Press, 2013. http://dx.doi.org/10.1145/2528394.2528397.

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Lages, Wallace, and Doug Bowman. "Adjustable Adaptation for Spatial Augmented Reality Workspaces." In SUI '19: Symposium on Spatial User Interaction. ACM, 2019. http://dx.doi.org/10.1145/3357251.3358755.

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Cena, Federica, Cristina Gena, and Claudia Picardi. "An Experimental Study in Cross-Representation Mediation of User Models." In UMAP '16: User Modeling, Adaptation and Personalization Conference. ACM, 2016. http://dx.doi.org/10.1145/2930238.2930263.

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Owen, V. Elizabeth, Gabriella Anton, and Ryan Baker. "Modeling User Exploration and Boundary Testing in Digital Learning Games." In UMAP '16: User Modeling, Adaptation and Personalization Conference. ACM, 2016. http://dx.doi.org/10.1145/2930238.2930271.

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Reports on the topic "User adaptation"

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Weilandt, E., N. Khanchandani, and S. Rao. V5.2-User Adaptation Layer (V5UA). RFC Editor, 2004. http://dx.doi.org/10.17487/rfc3807.

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Morneault, K., S. Rengasami, M. Kalla, and G. Sidebottom. ISDN Q.921-User Adaptation Layer. RFC Editor, 2001. http://dx.doi.org/10.17487/rfc3057.

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Sidebottom, G., L. Coene, G. Verwimp, J. Keller, and B. Bidulock. Signalling Connection Control Part User Adaptation Layer (SUA). Edited by J. Loughney. RFC Editor, 2004. http://dx.doi.org/10.17487/rfc3868.

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Morneault, K., S. Rengasami, M. Kalla, and G. Sidebottom. Integrated Services Digital Network (ISDN) Q.921-User Adaptation Layer. RFC Editor, 2006. http://dx.doi.org/10.17487/rfc4233.

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Morneault, K., R. Dantu, G. Sidebottom, B. Bidulock, and J. Heitz. Signaling System 7 (SS7) Message Transfer Part 2 (MTP2) - User Adaptation Layer. RFC Editor, 2002. http://dx.doi.org/10.17487/rfc3331.

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Sidebottom, G., K. Morneault, and J. Pastor-Balbas, eds. Signaling System 7 (SS7) Message Transfer Part 3 (MTP3) - User Adaptation Layer (M3UA). RFC Editor, 2002. http://dx.doi.org/10.17487/rfc3332.

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Morneault, K., and J. Pastor-Balbas, eds. Signaling System 7 (SS7) Message Transfer Part 3 (MTP3) - User Adaptation Layer (M3UA). RFC Editor, 2006. http://dx.doi.org/10.17487/rfc4666.

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Swartout, William R., and Yolanda Gil. EXPECT: A User-Centered Environment for the Development and Adaptation of Knowledge-Based Planning Aids. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada459766.

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George, T., B. Bidulock, R. Dantu, H. Schwarzbauer, and K. Morneault. Signaling System 7 (SS7) Message Transfer Part 2 (MTP2) - User Peer-to-Peer Adaptation Layer (M2PA). RFC Editor, 2005. http://dx.doi.org/10.17487/rfc4165.

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Hoy, Andreas, Åsa Gerger Swartling, and Elin Leander. Adopting a user-oriented approach to make climate information more accessible across Europe. Stockholm Environment Institute, 2022. http://dx.doi.org/10.51414/sei2022.009.

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Abstract:
Research from the ClimVis Europe project shows that climate information must be presented in more effective ways to reduce climate risks and support adaptation. Users need information that is easy to access, in their own language, and designed to help them make connections between real-time weather events and long-term climate developments. Users of weather and climate data in Europe are aware of only a few (if any) relevant, available tools that provide them with the insights into current, future and long-term meteorological trends that they seek. However, efforts to boost awareness of available tools, while important, will not be enough to meet user demands. Providers of climate information need to consult with stakeholders to co-develop new tools to meet needs and support the uptake of information. Existing European tools have two key shortcomings: limited language and insufficient context. The provision of climate information exclusively in English excludes many users (especially at local and regional levels and in Eastern Europe and Russia). Tools do not link real-time extreme weather with long-term past or future climate trends; such connections are essential to assess climate change-related impacts and adaptation needs. We interpret the results as a call to action, to enhance related communication that is fundamental to the need to reduce climate risks and support adaptation.
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