Academic literature on the topic 'User tasks'
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Journal articles on the topic "User tasks"
Mehrotra, Rishabh. "Inferring User Needs & Tasks from User Interactions." ACM SIGIR Forum 52, no. 2 (January 17, 2019): 176–77. http://dx.doi.org/10.1145/3308774.3308806.
Full textCordes, Richard E. "Task-Selection Bias: A Case for User-Defined Tasks." International Journal of Human-Computer Interaction 13, no. 4 (December 2001): 411–19. http://dx.doi.org/10.1207/s15327590ijhc1304_04.
Full textHarej, Viktor, and Maja Žumer. "Analysis of FRBR User Tasks." Cataloging & Classification Quarterly 51, no. 7 (October 2013): 741–59. http://dx.doi.org/10.1080/01639374.2013.785461.
Full textZhang, Yin, and Athena Salaba. "User interface for FRBR user tasks in online catalogs." Proceedings of the American Society for Information Science and Technology 46, no. 1 (2009): 1–4. http://dx.doi.org/10.1002/meet.2009.1450460371.
Full textLv, Ning, Jing Li Zhou, and Lei Hua Qin. "Using Context to Discern User Tasks on Desktop." Applied Mechanics and Materials 519-520 (February 2014): 318–21. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.318.
Full textWu, Dapeng, Haopeng Li, and Ruyan Wang. "User Characteristic Aware Participant Selection for Mobile Crowdsensing." Sensors 18, no. 11 (November 15, 2018): 3959. http://dx.doi.org/10.3390/s18113959.
Full textCuomo, Donna L., Eliot Jablonka, and Jane N. Mosier. "Data Entry Interaction Techniques for Graphical User Interfaces." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 6 (October 1996): 370–74. http://dx.doi.org/10.1177/154193129604000611.
Full textSu, Hua, Qianqian Wu, Xuemei Sun, and Ning Zhang. "The User Participation Incentive Mechanism of Mobile Crowdsensing Network Based on User Threshold." Discrete Dynamics in Nature and Society 2020 (June 20, 2020): 1–8. http://dx.doi.org/10.1155/2020/2683981.
Full textChen, Huihui, Bin Guo, Zhiwen Yu, and Liming Chen. "A location-constrained crowdsensing task allocation method for improving user satisfaction." International Journal of Distributed Sensor Networks 15, no. 10 (October 2019): 155014771988398. http://dx.doi.org/10.1177/1550147719883987.
Full textRind, Alexander, Wolfgang Aigner, Markus Wagner, Silvia Miksch, and Tim Lammarsch. "Task Cube: A three-dimensional conceptual space of user tasks in visualization design and evaluation." Information Visualization 15, no. 4 (July 25, 2016): 288–300. http://dx.doi.org/10.1177/1473871615621602.
Full textDissertations / Theses on the topic "User tasks"
Mehrotra, R. "Inferring user needs and tasks from user interactions." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10047203/.
Full textBen, Lahmar Imen. "Continuity of user tasks execution in pervasive environments." Phd thesis, Institut National des Télécommunications, 2012. http://tel.archives-ouvertes.fr/tel-00789725.
Full textSayyaparaju, Vedha. "User-designed background tasks in App inventor." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100626.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (page 70).
In this thesis, I describe how I designed and built multiple components and extensions to App Inventor 2 that will allow application builders to create custom services and background tasks and to build applications that can interact with these services and tasks. Previously, the App Inventor platform only supported the creation of applications which had a screen in the foreground at all times. As such, the main abstraction of App Inventor was this notion of a "Screen". These screens could launch certain tasks to run in the background, but they were limited to the few tasks that were exposed by the App Inventor interface. Application builders could not design and customize their own background tasks. This restricted App Inventor users from building certain types of applications, for example, a music player application or an application that has heavy network communication. To enable users to build such applications, I extended the App Inventor platform to expose a "Task" object in addition to the existing "Screen" object. I created a messaging system which would allow Screens and Tasks to communicate with each other. I also developed additional task components that could be contained in these new Task objects. Users can customize the functionality of Tasks by putting together multiple task components. In this way, App Inventor users can now build more functional applications and explore a part of the Android SDK that was previously out of reach.
by Vedha Sayyaparaju.
M. Eng.
Tobon, Carolina. "Evaluating geovisualisation and user interaction : an experimental design approach based upon user tasks." Thesis, University College London (University of London), 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.405460.
Full textCasallas, suarez Juan Sebastian. "Prediction of user action in moving-target selection tasks." Thesis, Paris, ENSAM, 2015. http://www.theses.fr/2015ENAM0018/document.
Full textSelection of moving targets is a common, yet complex task in human–computer interaction (HCI), and more specifically in virtual reality (VR). Action prediction has proven to be the most comprehensive enhancement to address moving-target selection challenges. Current predictive techniques, however, heavily rely on continuous tracking of user actions, without considering the possibility that target-reaching actions may have a dominant pre-programmed component—this theory is known as the pre-programmed control theory.Thus, based on the pre-programmed control theory, this research explores the possibility of predicting moving-target selection prior to action execution. Specifically, three levels of action prediction are investigated: 1) action performance measured as the movement time (MT) required to reach a target, 2) prospective difficulty (PD), i.e., subjective assessments made prior to action execution; and 3) intention, i.e., the target that the user plans to reach.In this dissertation, intention prediction models are developed using decision trees and scoring functions—these models are evaluated in two VR studies. PD models for 1-D, and 2-D moving- target selection tasks are developed based on Fitts' Law, and evaluated in an online experiment. Finally, MT models with the same structural form of the aforementioned PD models are evaluated in a 3-D moving-target selection experiment deployed in VR
Estes, T. Scott. "From the use of performance tasks to the user of performance tasks| Authentic learning and assessment experiences in middle schools." Thesis, Aurora University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10131732.
Full textThe purpose of this qualitative, multi-case study is to identify the traits three middle school classroom teachers share, which seemingly enable them to successfully engage their students in performance-based activities and assessments. This study investigates the research behind the use of performance tasks, authentic learning and assessment and connects the data gleaned from observations and interviews with participants and administrators to the literature review. Data analysis and summations connect performance tasks to authentic learning but also identify more subjective traits such as relationship building, riskiness in instructional methodology, and the innate skills of a teacher, which appear to enhance students’ learning experiences. Students observed in the classrooms are asked not only to know content and cultivate an appropriate skill base, but also asked to use that knowledge and those skills to solve real-world problems. Data from the three participants not only illustrates the findings of other relevant research, but characterizes the types of teachers who inspire students to perform on a more complex level in order to solve complex problems.
Gwizdka, Jacek, and Mark Chignell. "Individual Differences and Task-based User Interface Evaluation: A Case Study of Pending Tasks in Email." Elsevier, 2004. http://hdl.handle.net/10150/105556.
Full textThis paper addresses issues raised by the ever-expanding role of email as a multi-faceted application that combines communication, collaboration, and task management. Individual differences analysis was used to contrast two email user interfaces in terms of their demands on users. The results of this analysis were then interpreted in terms of their implications for designing more inclusive interfaces that meet the needs of users with widely ranging abilities. The specific target of this research is the development of a new type of email message representation that makes pending tasks more visible. We describe a study that compared a new way of representing tasks in an email inbox, with a more standard representation (the Microsoft Outlook inbox). The study consisted of an experiment that examined how people with different levels of three specific cognitive capabilities (flexibility of closure, visual memory, and working memory) perform when using these representations. We then identified combinations of representation and task that are disadvantageous for people with low levels of the measured capabilities.
Ingmarsson, Magnus. "Modelling User Tasks and Intentions for Service Discovery in Ubiquitous Computing." Licentiate thesis, Linköping University, Linköping University, MDA - Human Computer Interfaces, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8319.
Full textUbiquitous computing (Ubicomp) increases in proliferation. Multiple and ever growing in numbers, computational devices are now at the users' disposal throughout the physical environment, while simultaneously being effectively invisible. Consequently, a significant challenge is service discovery. Services may for instance be physical, such as printing a document, or virtual, such as communicating information. The existing solutions, such as Bluetooth and UPnP, address part of the issue, specifically low-level physical interconnectivity. Still absent are solutions for high-level challenges, such as connecting users with appropriate services. In order to provide appropriate service offerings, service discovery in Ubicomp must take the users' context, tasks, goals, intentions, and available resources into consideration. It is possible to divide the high-level service-discovery issue into two parts; inadequate service models, and insufficient common-sense models of human activities.
This thesis contributes to service discovery in Ubicomp, by arguing that in order to meet these high-level challenges, a new layer is required. Furthermore, the thesis presents a prototype implementation of this new service-discovery architecture and model. The architecture consists of hardware, ontology-layer, and common-sense-layer. This work addresses the ontology and common-sense layers. Subsequently, implementation is divided into two parts; Oden and Magubi. Oden addresses the issue of inadequate service models through a combination of service-ontologies in concert with logical reasoning engines, and Magubi addresses the issue of insufficient common-sense models of human activities, by using common sense models in combination with rule engines. The synthesis of these two stages enables the system to reason about services, devices, and user expectations, as well as to make suitable connections to satisfy the users' overall goal.
Designing common-sense models and service ontologies for a Ubicomp environment is a non-trivial task. Despite this, we believe that if correctly done, it might be possible to reuse at least part of the knowledge in different situations. With the ability to reason about services and human activities it is possible to decide if, how, and where to present the services to the users. The solution is intended to off-load users in diverse Ubicomp environments as well as provide a more relevant service discovery.
Report code: LiU-Tek-Lic-2007:14.
Huynh, David François 1978. "A user interface framework for supporting information management tasks in Haystack." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/87355.
Full textIncludes bibliographical references (p. 153-155).
by David François Huynh.
S.M.
Cox, Kevin Ross, and n/a. "Searching by browsing." University of Canberra. Information Sciences & Engineering, 1994. http://erl.canberra.edu.au./public/adt-AUC20060630.102136.
Full textBooks on the topic "User tasks"
Information tasks: Toward a user-centered approach to information systems. San Diego: Academic Press, 1996.
Find full textScär, Sissel Guttormsen. Implicit and explicit learning of computerised tasks: The role of the user-interface and task saliency. Zürich: ADAG Copy, 1998.
Find full textZacharias, Franziska. Knowledge Representations for Planning Manipulation Tasks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Find full textJ, Gold E., Perry Lee, and Bray Faustin, eds. Tanks for the memories: Floatation tank talks. [Nevada City, CA]: Gateways/IDHHB, 1995.
Find full textJanice, Redish, ed. User and task analysis for interface design. New York: Wiley, 1998.
Find full textLogunova, Oksana, Petr Romanov, and Elena Il'ina. Processing of experimental data on a computer. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1064882.
Full textHormann, Hans-Jurgen. TOM - Test of multiple task performance. User manual. Koln, Germany: DLR, 1989.
Find full textEngland, David, Philippe Palanque, Jean Vanderdonckt, and Peter J. Wild, eds. Task Models and Diagrams for User Interface Design. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11797-8.
Full textWinckler, Marco, Hilary Johnson, and Philippe Palanque, eds. Task Models and Diagrams for User Interface Design. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-77222-4.
Full textKorneev, Viktor, Larisa Gagarina, and Mariya Korneeva. Visualization in scientific research. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1029660.
Full textBook chapters on the topic "User tasks"
Kraft, Christian. "Identifying Core Tasks." In User Experience Innovation, 43–56. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4150-8_5.
Full textKraft, Christian. "Innovating Around Core Tasks." In User Experience Innovation, 57–64. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4150-8_6.
Full textTreu, Siegfried. "Computer Applications and Tasks." In User Interface Design, 61–83. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2429-8_4.
Full textSutcliffe, Alistair. "RE Tasks and Processes." In User-Centred Requirements Engineering, 45–77. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0217-5_3.
Full textJohnson, Peter, Stephanie Wilson, and Hilary Johnson. "Designing User Interfaces from Analyses of Users’ Tasks." In Human-Computer Interaction INTERACT ’97, 655–56. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-0-387-35175-9_118.
Full textNavalpakkam, Vidhya, Ravi Kumar, Lihong Li, and D. Sivakumar. "Attention and Selection in Online Choice Tasks." In User Modeling, Adaptation, and Personalization, 200–211. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31454-4_17.
Full textDíaz Esteban, Alberto. "Integrating Multilingual Text Classification Tasks and User Modeling in Personalized Newspaper Services." In User Modeling 2001, 268–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44566-8_41.
Full textKunert, Tibor. "User Tasks and Requirements for iTV Applications." In User-Centered Interaction Design Patterns for Interactive Digital Television Applications, 85–98. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-275-7_4.
Full textFoerster, Cora. "Controlling Distributed User Tasks in Heterogeneous Networks." In Hector Heterogeneous Computers Together A Joint Project of IBM and the University of Karlsruhe, 183–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73574-5_11.
Full textTorre, Ilaria. "Goals, Tasks and Application Domains as the Guidelines for Defining a Framework for User Modelling." In User Modeling 2001, 260–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44566-8_39.
Full textConference papers on the topic "User tasks"
Rind, Alexander, Wolfgang Aigner, Markus Wagner, Silvia Miksch, and Tim Lammarsch. "User tasks for evaluation." In the Fifth Workshop. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2669557.2669568.
Full textJohnson, Peter, Stephanie Wilson, and Hilary Johnson. "Designing user interfaces from analyses of users' tasks." In CHI '97 extended abstracts. New York, New York, USA: ACM Press, 1997. http://dx.doi.org/10.1145/1120212.1120322.
Full textSow, D., M. Ebling, R. P. Lehmann, J. Davis, and L. Bergman. "SCOUT contextually organizes user tasks." In IEEE International Conference on e-Business Engineering (ICEBE'05). IEEE, 2005. http://dx.doi.org/10.1109/icebe.2005.109.
Full textPalacios, Alfons, Roberto García, Marta Oliva, and Toni Granollers. "Semantic Web End-User Tasks." In the XV International Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2662253.2662299.
Full textKim, Heejin, Seungjae Oh, Sung H. Han, and Min K. Chung. "Natural pointing posture in distal pointing tasks." In SUI '14: Symposium on Spatial User Interaction. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2659766.2661213.
Full textDev, Himel, and Zhicheng Liu. "Identifying Frequent User Tasks from Application Logs." In IUI'17: 22nd International Conference on Intelligent User Interfaces. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3025171.3025184.
Full textLi, Xin, Lei Zhang, Ping Luo, Enhong Chen, Guandong Xu, Yu Zong, and Chu Guan. "Mining user tasks from print logs." In 2014 International Joint Conference on Neural Networks (IJCNN). IEEE, 2014. http://dx.doi.org/10.1109/ijcnn.2014.6889721.
Full textBalbo, Sandrine, Dirk Draheim, Christof Lutteroth, and Gerald Weber. "Appropriateness of user interfaces to tasks." In the 4th international workshop. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1122935.1122957.
Full textSmith, Missie, Jillian Streeter, Gary Burnett, and Joseph L. Gabbard. "Visual search tasks." In AutomotiveUI '15: The 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2799250.2799291.
Full textBjerre, Per, Allan Christensen, Simon André Pedersen, Andreas Køllund Pedersen, and Wolfgang Stuerzlinger. "Transition Times for Manipulation Tasks in Hybrid Interfaces." In SUI '15: Symposium on Spatial User Interaction. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2788940.2794358.
Full textReports on the topic "User tasks"
Redden, Elizabeth S., Daniel D. Turner, and Christian B. Carstens. The Effect of Future Forces Warrior Planned Sensor Offset on Performance of Infantry Tasks: Limited User Evaluation. Fort Belvoir, VA: Defense Technical Information Center, April 2006. http://dx.doi.org/10.21236/ada448487.
Full textCamenzind, Lauren, Molly Kafader, Rachel Schwam, Mikayla Taylor, Zoie Wilkes, and Madison Williams. Space Retrieval Training for Memory Enhancement in Adults with Dementia. University of Tennessee Health Science Center, May 2021. http://dx.doi.org/10.21007/chp.mot2.2021.0013.
Full textNaves, Claudia, David Amorim, David Geisler-Moroder, Thorbjörn Laike, Justyna Martyniuk-Peczek, Barbara Szybinska Matusiak, Wilfried Pohl, and Natalia Sokol. Literature review of user needs, toward user requirements. Edited by Barbara Szybinska Matusiak. IEA SHC Task 61, September 2020. http://dx.doi.org/10.18777/ieashc-task61-2020-0001.
Full textAshton, Zoe Charon Maria, Joanne Roth Wendelberger, Lawrence O. Ticknor, Terece Turton, and Francesca Samsel. Analyzing Task-Based User Study Data to Determine Colormap Efficiency. Office of Scientific and Technical Information (OSTI), July 2015. http://dx.doi.org/10.2172/1210205.
Full textAshton, Zoe Charon Maria, Joanne Roth Wendelberger, Lawrence O. Ticknor, Terece Turton, and Francesca Samsel. Analyzing task-based user study data to determine colormap efficiency. Office of Scientific and Technical Information (OSTI), July 2015. http://dx.doi.org/10.2172/1210206.
Full textPetersen, Rodney, Danielle Santos, Matthew C. Smith, Karen A. Wetzel, and Greg Witte. Workforce Framework for Cybersecurity (NICE Framework). National Institute of Standards and Technology, November 2020. http://dx.doi.org/10.6028/nist.sp.800-181r1.
Full textNashman, Marilyn. The use of vision and touch sensors for dimensional inspection tasks. Gaithersburg, MD: National Institute of Standards and Technology, 1992. http://dx.doi.org/10.6028/nist.ir.4839.
Full textMcGee, Steven, Everett Smith, Andrew Rasmussen, and Jeremy Gubman. Using Rasch analysis for determining the cut score of a computer science placement exam. The Learning Partnership, April 2021. http://dx.doi.org/10.51420/conf.2021.4.
Full textCurtis, Christopher K., Christian E. Randall, Brian Tidball, Scott Bachmann, Darryl Stimson, David E. Kancler, Megan E. Gorman, and Mary McWesler. Application of Cognitive Task Analysis in User Requirements and Prototype Design Presentation/Briefing. Fort Belvoir, VA: Defense Technical Information Center, October 2005. http://dx.doi.org/10.21236/ada441401.
Full textFernandes, Kathleen. A Scenario-Based Methodology for Evaluating User Interface Functionality on a Database Retrieval Task. Fort Belvoir, VA: Defense Technical Information Center, May 1991. http://dx.doi.org/10.21236/ada236967.
Full text