Journal articles: 'User tasks'

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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.

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Cordes, 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.

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Harej, 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.

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Zhang, 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.

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Lv, 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.

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The precise context of user tasks helps to ameliorate personal information management on desktop. This paper introduces a novel approach to discern user tasks using contextual information which is divided into two categories, user behavior based context and text based context. With the contextual information, user tasks are discerned by support vector machine (SVM) method. Experimental results showed the impact of distinct attributes of files on the performance of user task identification.

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Wu, 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.

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Mobile crowdsensing (MCS) is a promising sensing paradigm that leverages diverse embedded sensors in massive mobile devices. One of its main challenges is to effectively select participants to perform multiple sensing tasks, so that sufficient and reliable data is collected to implement various MCS services. Participant selection should consider the limited budget, the different tasks locations, and deadlines. This selection becomes even more challenging when the MCS tries to efficiently accomplish tasks under different heat regions and collect high-credibility data. In this paper, we propose a user characteristics aware participant selection (UCPS) mechanism to improve the credibility of task data in the sparse user region acquired by the platform and to reduce the task failure rate. First, we estimate the regional heat according to the number of active users, average residence time of users and history of regional sensing tasks, and then we divide urban space into high-heat and low-heat regions. Second, the user state information and sensing task records are combined to calculate the willingness, reputation and activity of users. Finally, the above four factors are comprehensively considered to reasonably select the task participants for different heat regions. We also propose task queuing strategies and community assistance strategies to ensure task allocation rates and task completion rates. The evaluation results show that our mechanism can significantly improve the overall data quality and complete sensing tasks of low-heat regions in a timely and reliable manner.

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Cuomo, 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.

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Despite the widespread use of graphical forms-based interfaces, there are no widely accepted and proven interaction methods for supporting even the most common data entry tasks. We present three common data entry tasks (task flow, domain-related data entry, hierarchical list selection) and a variety of commonly-used designs to support them, and some pros and cons of each. We recommend that good designs to commonly performed data entry tasks be identified and catalogued

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Su, 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.

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Mobile crowdsensing (MCS) network means completing large-scale and complex sensing tasks in virtue of the mobile devices of ordinary users. Therefore, sufficient user participation plays a basic role in MCS. On the basis of studying and analyzing the strategy of user participation incentive mechanism, this paper proposes the user threshold-based cognition incentive strategy against the shortcomings of existing incentive strategies, such as task processing efficiency and budget control. The user threshold and the budget of processing subtasks are set at the very beginning. The platform selects the user set with the lowest threshold, and the best user for processing tasks according to users’ budget. The incentive cost of the corresponding users is calculated based on the user threshold at last. In conclusion, through the experiment validation and comparison with the existing user participation incentive mechanism, it was found that the user threshold-based incentive strategy is advantageous in improving the proportion of task completion and reducing the platform’s budget cost.

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Chen, 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.

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Mobile crowdsensing is a special data collection manner which collects data by smart phones taken by people every day. It is essential to pick suitable workers for different outdoor tasks. Constrained by participants’ locations and their daily travel rules, they are likely to accomplish light outdoor tasks by their way without extra detours. Previous researchers found that people prefer to accomplish a certain number of tasks at a time; thus, we focus on assigning light outdoor tasks to workers by considering two optimization objectives, including (1) maximizing the ratio of light tasks for different workers and (2) maximizing the worker’s satisfaction on assigned tasks. This task allocation problem is a non-deterministic polynomial-time-hard due to two reasons, that is, tasks and workers are many-to-many relationships and workers move from different places to different places. Considering both optimization objectives, we design the global-optimizing task allocation algorithm, which greedily selects the most appropriate participant until either no participant can be chosen or no tasks can be assigned. For the purpose of emulating real scenarios, different scales of maps, tasks, and workers are simulated to evaluate algorithms. Experimental results verify that the proposed global-optimizing method outperforms baselines on both maximization objectives.

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Rind, 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.

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User tasks play a pivotal role in visualization design and evaluation. However, the term ‘task’ is used ambiguously within the visualization community. In this article, we critically analyze the relevant literature and systematically compare definitions of ‘task’ and the usage of related terminology. In doing so, we identify a three-dimensional conceptual space of user tasks in visualization, referred to as the task cube, and the more precise concepts ‘objective’ and ‘action’ for tasks. We illustrate the usage of the task cube’s dimensions in an objective-driven visualization process, in different scenarios of visualization design and evaluation, and for comparing categorizations of abstract tasks. Thus, visualization researchers can better formulate their contributions which helps advance visualization as a whole.

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Johnsgard, Todd J., Stanley R. Page, Robert D. Wilson, and Ronald J. Zeno. "A Comparison of Graphical User Interface Widgets for Various Tasks." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 39, no. 4 (October 1995): 287–91. http://dx.doi.org/10.1177/154193129503900414.

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The purpose of the present study was to compare user performance, accuracy and preference while using standard user interface controls or “widgets” to complete specific types of tasks. Radio buttons were significantly faster, accurate, and preferred than any outer widget for the mutually exclusive selection tasks. For the non-mutually exclusive selection tasks, check boxes were significantly faster and preferred. These widgets were superior due to the fact that all possible options were initially visible. As the number of options increased, the time to complete each task also increased. A practitioner's table for selecting effective widgets for specific types of tasks is provided. Further implications for user interface design and research are discussed.

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Taniguchi, Shoichi. "User Tasks in the RDA-Based Model." Cataloging & Classification Quarterly 51, no. 7 (October 2013): 788–815. http://dx.doi.org/10.1080/01639374.2013.800623.

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Zubrycki, Igor, and Grzegorz Granosik. "Intuitive User Interfaces for Mobile Manipulation Tasks." Journal of Automation, Mobile Robotics and Intelligent Systems 9, no. 1 (February 10, 2015): 41–52. http://dx.doi.org/10.14313/jamris_1-2015/6.

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Yen, Gary G., and Daghan Acay. "Adaptive user interfaces in complex supervisory tasks." ISA Transactions 48, no. 2 (April 2009): 196–205. http://dx.doi.org/10.1016/j.isatra.2008.11.002.

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Zachos, Konstantinos, Angela Kounkou, and Neil A. M. Maiden. "Exploiting Codified User Task Knowledge to Discover Services at Design-Time." International Journal of Systems and Service-Oriented Engineering 3, no. 2 (April 2012): 30–66. http://dx.doi.org/10.4018/jssoe.2012040103.

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Most techniques for engineering service-based applications do not explicitly exploit knowledge about users and their tasks. In this paper the authors hypothesize that codified knowledge about user tasks can improve service discovery at design-time. It reports the extension of an existing service discovery algorithm to match service queries to user task models then reformulate the service queries with task-specific knowledge in order to improve discovery precision and recall scores. An empirical investigation of the extended algorithm revealed that, in order to deliver significant benefits, user task models need to describe more context-specific knowledge with which to extend service queries.

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WANG, DAZHI, and KISHOR S. TRIVEDI. "MODELING USER-PERCEIVED RELIABILITY BASED ON USER BEHAVIOR GRAPHS." International Journal of Reliability, Quality and Safety Engineering 16, no. 04 (August 2009): 303–29. http://dx.doi.org/10.1142/s0218539309003411.

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Service Reliability is an important consideration for new service deployment. Traditional system-oriented measures are no longer adequate to describe the reliability perceived by the user. In this paper we propose a general service reliability analysis approach based on user behavior, and derive formulas to compute service reliability from the user model and service models. The derived user-perceived service reliability incorporates the user task reliabilities, the dependencies of different user tasks, and various types of user behavior besides failure and recovery of system hardware and software components. This approach is applied to the service reliability computation for an example fault tolerant cluster hosing two services. Factors from both the system side and the user side are analyzed for the user-perceived service reliability of the cluster, and the results are compared with the system availability and service reliability lower bound.

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Kortum, Philip, and Claudia Ziegler Acemyan. "The Relationship Between User Mouse-based Performance And Subjective Usability Assessments." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 1174–78. http://dx.doi.org/10.1177/1541931213601275.

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Objective metrics, such as effectiveness and efficiency, are often considered to be the best website usability measurements. User performance metrics that can be collected remotely, such as mouse clicks and the distance the mouse has traveled show particular promise. However, no studies have demonstrated a direct relationship between subjective usability measures and these two objective user performance metrics. In this paper, thirty participants completed five different tasks of varying difficulty on a commercial website. Mouse clicks, the distance the mouse moved, success rates, and System Usability Scale (SUS) scores were collected for each task. Results showed that participants made fewer mouse clicks on tasks at which they were successful than on tasks they failed. Participants moved the mouse over twice as far on failed tasks as compared to successful tasks. The correlations between SUS scores and the two mouse-based measurements were remarkably strong.

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Canal, Gerard, Carme Torras, and Guillem Alenyà. "Are Preferences Useful for Better Assistance?" ACM Transactions on Human-Robot Interaction 10, no. 4 (December 31, 2021): 1–19. http://dx.doi.org/10.1145/3472208.

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Assistive Robots have an inherent need of adapting to the user they are assisting. This is crucial for the correct development of the task, user safety, and comfort. However, adaptation can be performed in several manners. We believe user preferences are key to this adaptation. In this article, we evaluate the use of preferences for Physically Assistive Robotics tasks in a Human-Robot Interaction user evaluation. Three assistive tasks have been implemented consisting of assisted feeding, shoe-fitting, and jacket dressing, where the robot performs each task in a different manner based on user preferences. We assess the ability of the users to determine which execution of the task used their chosen preferences (if any). The obtained results show that most of the users were able to successfully guess the cases where their preferences were used even when they had not seen the task before. We also observe that their satisfaction with the task increases when the chosen preferences are employed. Finally, we also analyze the user’s opinions regarding assistive tasks and preferences, showing promising expectations as to the benefits of adapting the robot behavior to the user through preferences.

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Hollands, J. G., and Philip M. Merikle. "Menu Organization and User Expertise in Information Search Tasks." Human Factors: The Journal of the Human Factors and Ergonomics Society 29, no. 5 (October 1987): 577–86. http://dx.doi.org/10.1177/001872088702900507.

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A categorical menu structure based on experts' semantic memory organization was developed, and search efficiency using this menu organization, relative to search efficiency using alphabetic and random menu organizations, was evaluated for users with different levels of expertise. In Experiment 1 experts in psychology sorted 120 psychological terms and the data were submitted to a multidimensional scaling procedure to identify the clusters of terms used to develop the categorical menu organization. In Experiment 2 search efficiency with the three different menu organizations was evaluated for users with different levels of expertise in the subject domain on two different search tasks: (1) definition matching, wherein given a definition, it was necessary to find the correct term with its definition; and (2) term matching, wherein given a term, it was necessary to find the identical term with its definition. Performance on both search tasks improved directly with expertise in the subject area when the categorical menu organization was used, and experts completed the definition-matching task faster than novices with all three types of menu organization. However, performance on the term-matching task was not influenced by expertise when alphabetic and random menu organizations were used.

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Brunete, Alberto, Carlos Mateo, Ernesto Gambao, Miguel Hernando, Jukka Koskinen, Jari M. Ahola, Tuomas Seppälä, and Tapio Heikkila. "User-friendly task level programming based on an online walk-through teaching approach." Industrial Robot: An International Journal 43, no. 2 (March 21, 2016): 153–63. http://dx.doi.org/10.1108/ir-05-2015-0103.

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Purpose – This paper aims to propose a new technique for programming robotized machining tasks based on intuitive human–machine interaction. This will enable operators to create robot programs for small-batch production in a fast and easy way, reducing the required time to accomplish the programming tasks. Design/methodology/approach – This technique makes use of online walk-through path guidance using an external force/torque sensor, and simple and intuitive visual programming, by a demonstration method and symbolic task-level programming. Findings – Thanks to this technique, the operator can easily program robots without learning every robot-specific language and can design new tasks for industrial robots based on manual guidance. Originality/value – The main contribution of the paper is a new procedure to program machining tasks based on manual guidance (walk-through teaching method) and user-friendly visual programming. Up to now, the acquisition of paths and the task programming were done in separate steps and in separate machines. The authors propose a procedure for using a tablet as the only user interface to acquire paths and to make a program to use this path for machining tasks.

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Intille, S. S., K. Larson, and P. Kaushik. "User-adaptive Reminders for Home-based Medical Tasks." Methods of Information in Medicine 47, no. 03 (2008): 203–7. http://dx.doi.org/10.3414/me9111.

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Summary Objectives: We present a prototype adaptive reminder system for home-based medical tasks. The system consists of a mobile device for reminder presentation and ambient sensors to determine opportune moments for reminder delivery. Our objective was to study interaction with the prototype under naturalistic living conditions and gain insight into factors affecting the longterm acceptability of context-sensitive reminder systems for the home setting. Methods: A volunteer participant used the prototype in a residential research facility while adhering to a regimen of simulated medical tasks for ten days. Some reminders were scheduled at fixed times during the day and some were automatically time-shifted based on sensor data. We made a complete video and sensor record of the stay. Finally, the participant commented about his experiences with the system in a debriefing interview. Results: Based on this case study, including direct observation of individual alert-action sequences, we make four recommendations for designers of context-sensitive adaptive reminder systems. Captured metrics suggest that adaptive reminders led to faster reaction times and were perceived by the participant as being more useful. Conclusions: The evaluation of context-sensitive systems that overlap into domestic lives is challenging. We believe that the ideal experiment is to deploy such systems in real homes and assess performance longitudinally. This case study in an instrumented live-in facility is a step toward that long-term goal.

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NONAKA, Hidetoshi, Takayuki KOMATSU, and Tsutomu DA-TE. "User model of pointing tasks with lifting motion." Japanese journal of ergonomics 33, no. 5 (1997): 297–304. http://dx.doi.org/10.5100/jje.33.297.

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Markopoulos, Panos. "Modelling User Tasks with the Unified Modelling Language." IFAC Proceedings Volumes 34, no. 16 (September 2001): 29–34. http://dx.doi.org/10.1016/s1474-6670(17)41497-2.

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Cruz, Ricardo, and Luis A. Pineda. "Promoting Optimal User Experience through Composite Challenge Tasks." Applied Sciences 9, no. 19 (October 1, 2019): 4106. http://dx.doi.org/10.3390/app9194106.

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Optimal user experience or flow is a theory with great impact on user experience. Promoting flow has become a competitive advantage for interactive systems, including rehabilitation. This can be achieved through an engaging interface that provides a rewarding experience and motivates the user to use the system again. This theory sustains that promoting a state of flow and improving task performance depends heavily on the balance between the challenges posed by the system and the skills deployed by the user. We further claim that balanced mental and motor skills demanded by the task improve flow and task performance. This paper presents an experiment supporting these claims. For this, we built two movement-interaction rehabilitation systems called SIBMER and Macoli (arm in Náhuatl). Both systems have two versions, one with a balanced load of mental and motor skills, and the other with an unbalanced one. Both versions are compared in terms of their potential to promote the state of flow and to improve task performance. Results show that a balance demand of mental and motor skills promotes flow, independently of the task complexity. Likewise, the experiment shows a correlation between flow and performance.

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Vuong, Tung, Miamaria Saastamoinen, Giulio Jacucci, and Tuukka Ruotsalo. "Understanding user behavior in naturalistic information search tasks." Journal of the Association for Information Science and Technology 70, no. 11 (March 18, 2019): 1248–61. http://dx.doi.org/10.1002/asi.24201.

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Ruotsalo, Tuukka, Kumaripaba Athukorala, Dorota Głowacka, Ksenia Konyushkova, Antti Oulasvirta, Samuli Kaipiainen, Samuel Kaski, and Giulio Jacucci. "Supporting exploratory search tasks with interactive user modeling." Proceedings of the American Society for Information Science and Technology 50, no. 1 (2013): 1–10. http://dx.doi.org/10.1002/meet.14505001040.

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Bailey, Brian P., Piotr D. Adamczyk, Tony Y. Chang, and Neil A. Chilson. "A framework for specifying and monitoring user tasks." Computers in Human Behavior 22, no. 4 (July 2006): 709–32. http://dx.doi.org/10.1016/j.chb.2005.12.011.

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Hendahewa, Chathra, and Chirag Shah. "Evaluating user search trails in exploratory search tasks." Information Processing & Management 53, no. 4 (July 2017): 905–22. http://dx.doi.org/10.1016/j.ipm.2017.04.001.

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Zhang, Limin, Sabah Currim, and Faiz Currim. "Competitive Intelligence Task Analysis And Retrieval: An End-User Approach." Review of Business Information Systems (RBIS) 15, no. 2 (April 11, 2011): 15–24. http://dx.doi.org/10.19030/rbis.v15i2.4200.

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The Internet, as one of the major resources for competitive intelligence (CI), not only provides a large amount of public data but also exposes a variety of business relations that may not otherwise be well-known. However, finding such information can be tedious and time-consuming for end-users without proper tools or expertise. In this paper, we examine the nature of CI tasks, classify and decompose them based on a task complexity theory, and propose norms for a context-based approach to retrieve CI data. We developed a meta-search engine called Competitive Intelligence Task Analysis and Retrieval (CITAR) to demonstrate the feasibility of the proposed approach. The present study provides a framework to further explore the relationships among CI tasks, interactive search, and context-based search systems design.

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Ozcan, Eda, Damla Topalli, Gul Tokdemir, and Nergiz Ercil Cagiltay. "A user task design notation for improved software design." PeerJ Computer Science 7 (May 24, 2021): e503. http://dx.doi.org/10.7717/peerj-cs.503.

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System design is recognized as one of the most critical components of a software system that bridges system requirements and coding. System design also has a significant impact on testing and maintenance activities, and on further improvements during the lifespan of the software system. Software design should reflect all necessary components of the requirements in a clear and understandable manner by all stakeholders of the software system. To distinguish system elements, separation of concerns in software design is suggested. In this respect, identification of the user tasks, i.e., the tasks that need to be performed by the user, is not currently reflected explicitly in system design documents. Our main assumption in this study is that software quality can be improved significantly by clearly identifying the user tasks from those that need to be performed by the computer system itself. Additionally, what we propose has the potential to better reflect the user requirements and main objectives of the system on the software design and thereby to improve software quality. The main aim of this study is to introduce a novel notation for software developers in the frame of UML Activity Diagram (UML-AD) that enables designers to identify the user tasks and define them separately from the system tasks. For this purpose, an extension of UML-AD, named UML-ADE (UML-Activity Diagram Extended) was proposed. Afterwards, it was implemented in a serious game case for which the specification of user tasks is extremely important. Finally, its effectiveness was analyzed and compared to UML-AD experimentally with 72 participants. The defect detection performance of the participants on both diagrams with two real-life serious game scenarios was evaluated. Results show a higher level of understandability for those using UML-ADE, which in turn may indicate a better design and higher software quality. The results encourage researchers to develop specific design representations dedicated to task design to improve system quality and to conduct further evaluations of the impact of these design on each of the above mentioned potential benefits for the software systems.

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Xing, Guoliang, Hao Gao, Qi Cao, Xinyu Yue, Bingbing Xu, Keting Cen, and Huawei Shen. "User Profiling for CSDN: Keyphrase Extraction, User Tagging and User Growth Value Prediction: First-place Entry for User Profiling Technology Evaluation Campaign in SMP Cup 2017." Data Intelligence 1, no. 2 (May 2019): 137–59. http://dx.doi.org/10.1162/dint_a_00015.

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The Chinese Software Developer Network (CSDN) is one of the largest information technology communities and service platforms in China. This paper describes the user profiling for CSDN, an evaluation track of SMP Cup 2017. It contains three tasks: (1) user document keyphrase extraction, (2) user tagging and (3) user growth value prediction. In the first task, we treat keyphrase extraction as a classification problem and train a Gradient-Boosting-Decision-Tree model with comprehensive features. In the second task, to deal with class imbalance and capture the interdependency between classes, we propose a two-stage framework: (1) for each class, we train a binary classifier to model each class against all of the other classes independently; (2) we feed the output of the trained classifiers into a softmax classifier, tagging each user with multiple labels. In the third task, we propose a comprehensive architecture to predict user growth value. Our contributions in this paper are summarized as follows: (1) we extract various types of features to identify the key factors in user value growth; (2) we use the semi-supervised method and the stacking technique to extend labeled data sets and increase the generality of the trained model, resulting in an impressive performance in our experiments. In the competition, we achieved the first place out of 329 teams.

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Christ, Richard E., Joseph A. Conroy, and Robert E. Robertson. "Crew Requirements Definition System Demonstration." Proceedings of the Human Factors Society Annual Meeting 33, no. 17 (October 1989): 1139. http://dx.doi.org/10.1518/107118189786757987.

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The crew requirements definition system (CRDS) is a computer-based methodology designed to minimize the time required to accomplishment any set of tasks while using the fewest resources. It enables analysts and researchers to study in a timely and cost effective manner the effects of varying crew size, task start times (and hence task sequencing), and task allocation to crewmembers or equipment items during the performance of designated missions without the need to observe crews actually performing their duties. The CRDS is programmed in C-language and is designed to be used on an “XT” or faster class of personal computer. The basis of the system is several automated PERT, GANTT, and critical path method calculations. In addition, the system produces other automated calculations and summaries to aid the user. The user should have some knowledge of these operations research techniques to use the system effectively. Also needed is an understanding of the tasks to be performed, the personnel and equipment items available to perform the tasks, each task's duration, and any requirements for task sequencing. The U.S. Army Research Institute for the Behavioral and Social Sciences (ARI) developed the CRDS for the Force Design Directorate at the U.S. Army Combined Arms Combat Development Activity. However, the system is useful in any military or civilian situations in which there is a need to design and evaluate alternative small unit organizational structures. The system can be used whenever the user has some knowledge, or is willing to venture some guesstimates, of the tasks that need to be performed and the capabilities of various assets to perform those tasks.

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Coury, Bruce G., and Richard A. Strauss. "Cognitive Models in User Interface Design." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 3 (October 1998): 325–29. http://dx.doi.org/10.1177/154193129804200330.

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Modeling user decision making and problem solving tasks has become a basic requirement for identifying user needs and task requirements and the prerequisite step to developing user interface technologies. In our work in developing new user interface concepts for naval command centers, we have been using cognitive modeling techniques to capture the goals and actions of users, represent those goals and actions as cognitive models, and use those models to assess the utility of user interface options. The purpose of this paper is to show how cognitive modeling has becoming a fundamental component of our design process, and is being used to assess user interface options before actual prototype development commences.

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NADKARNI, SUCHETA, and REETIKA GUPTA. "PERCEIVED WEBSITE COMPLEXITY, TELEPRESENCE AND USER ATTITUDES: THE MODERATING ROLE OF ONLINE USER TASKS." Academy of Management Proceedings 2004, no. 1 (August 2004): A1—A6. http://dx.doi.org/10.5465/ambpp.2004.13862469.

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Moreno, Daniel, Evan Glasheen, Antoinette Domingo, Van Brian Panaligan, Taylor Penaflor, Andrew Rioveros, and Jochen Kressler. "Validity of Caloric Expenditure Measured from a Wheelchair User Smartwatch." International Journal of Sports Medicine 41, no. 08 (March 16, 2020): 505–11. http://dx.doi.org/10.1055/a-1088-5629.

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AbstractThe objective of this study was to investigate the validity of measured caloric expenditure from a fitness smartwatch designed to measured values in wheelchair users against criterion values from a portable metabolic system. 15 wheelchair users and 15 able-bodied participants completed multiple tasks; wheelchair treadmill routine at 30, 45, and 60 strokes per minute, arm cycle ergometry at 45, 60, and 80 revolutions per minute, and arm cycle ergometry VO2Peak test. There were no interactions for device or task and group (wheelchair users vs. able bodied, p=0.375-0.944) therefore results were pooled across groups for all measures. The smartwatch exhibited poor to moderate caloric expenditure association during wheelchair treadmill routine (ICC<0.39) and arm cycle ergometry (ICC<0.541). Smartwatch underestimated caloric expenditure during the wheelchair treadmill task (Mean differences (Limits of Agreement)) (−2.11 (−8.19–3.96), −3.68 (−12.64–5.28), and −4.51 (−15.05–6.02)) and overestimated during the arm cycle ergometry task (0.89 (−3.10–4.88), 3.40 (−0.31–7.12), and 2.81 (−1.71–7.32)). The smartwatch is currently not well suited to calculate caloric expenditure when performing exercise tasks on a wheelchair treadmill and arm cycle ergometry.

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Chase, Joseph D., Sherry Perdue Casali, and H. Rex Hartson. "The Predictability of Cursor Control Device Performance Based on a Primitive Set of User Object-Oriented Cursor Actions." Proceedings of the Human Factors Society Annual Meeting 36, no. 4 (October 1992): 306–10. http://dx.doi.org/10.1177/154193129203600410.

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The ability to predict performance with a cursor control device on a complex task by measuring performance on a simple task would be useful in evaluating alternative input devices in many types of novel situations. A user would simply have to perform simple cursor movements with each candidate device, and predictions could be made of his/her performance with the devices on any given software application. Such an approach would reduce tedious trial and error procedures, as well as eliminate the time necessary to first learn various software applications. The current study employed the User Action Notation (UAN), a task-oriented notation that describes the behavior of the user and the interface during their cooperative performance of a task, to decompose complex tasks into primitive components. A set of primitive cursor actions was developed which contains the elementary cursor actions found in complex tasks. A graphics software application was then evaluated, using the UAN, with respect to the frequency of occurrence of each of the primitive user-cursor actions. Individual's ability to perform each primitive user-cursor action with three different input devices was then be measured. These measures were used to form estimates of the individual's ability to perform the graphics task with each input device. Correlations between predicted performance and measured performance on the graphics task were found to exceed 0.9. Results demonstrate the success of the method described herein for predicting complex task performance based on simple task performance, as well as, the usefulness of the UAN for decomposing complex tasks into primitive components.

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Seikel, Michele. "General Notes in Catalog Records versus FRBR User Tasks." Cataloging & Classification Quarterly 51, no. 4 (May 2013): 420–27. http://dx.doi.org/10.1080/01639374.2012.749318.

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Hartson, H. Rex, and Philip D. Gray. "Temporal Aspects of Tasks in the User Action Notation." Human–Computer Interaction 7, no. 1 (March 1992): 1–45. http://dx.doi.org/10.1207/s15327051hci0701_1.

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Atanasova, Margarita, and Anna Malinova. "TRANSFORMING CONCUR TASK TREES MODEL INTO AN ABSTRACT USER INTERFACE." CBU International Conference Proceedings 5 (September 24, 2017): 1036–41. http://dx.doi.org/10.12955/cbup.v5.1067.

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Business applications are difficult to use for the average user. An adaptive user interface improves employeesâ€™ productivity and is presented as a solution to this problem. However, developing user interfaces that are adapted to the needs and culture of the enterprise is time-consuming and expensive. We developed a software prototype for generating adaptive user interfaces that makes this process less time-consuming and more efficient. We propose an extension to the Cameleon Reference Framework project by Information Society Technologies, on the implementation level by adding an additional step for defining the Area of Business Operations. That way the prototype can extract business tasks for the selected industry therefore, presenting to the developer a more intelligent selection of predefined tasks. In this article, we also present a programming approach for transforming a task model, as defined by the ConcurTaskTrees notation, into an abstract user interface.

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Chaudhary, Karan Singh, and Pietro Murano. "The Design and Evaluation of A New Smartwatch User Interface." International Journal of Interactive Mobile Technologies (iJIM) 15, no. 13 (July 13, 2021): 128. http://dx.doi.org/10.3991/ijim.v15i13.22701.

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<p class="0abstract">This paper discusses and presents a new prototype design for a smartwatch user interface. The user interface was designed aiming to adhere to some of the main universal design principles and be a more usable design. The prototype user interface was then compared with a Samsung Gear S3 smartwatch user interface. The comparison was done via an experiment and a series of realistic tasks. The aspects being investigated were task times, errors and subjective user satisfaction. The data collected were statistically analysed. The overall results showed that the prototype user interface fostered faster task times, fewer errors and more user satisfaction.</p>

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Wegner, Stephan, Quentin Lohmeyer, Dimitri Wahlen, Sandra Neumann, Jean-Claude Groebli, and Mirko Meboldt. "Value of Eye-Tracking Data for Classification of Information Processing–Intensive Handling Tasks: Quasi-Experimental Study on Cognition and User Interface Design." JMIR Human Factors 7, no. 2 (June 3, 2020): e15581. http://dx.doi.org/10.2196/15581.

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Background In order to give a wide range of people the opportunity to ensure and support home care, one approach is to develop medical devices that are as user-friendly as possible. This allows nonexperts to use medical devices that were originally too complicated to use. For a user-centric development of such medical devices, it is essential to understand which user interface design best supports patients, caregivers, and health care professionals. Objective Using the benefits of mobile eye tracking, this work aims to gain a deeper understanding of the challenges of user cognition. As a consequence, its goal is to identify the obstacles to the usability of the features of two different designs of a single medical device user interface. The medical device is a patient assistance device for home use in peritoneal dialysis therapy. Methods A total of 16 participants, with a subset of seniors (8/16, mean age 73.7 years) and young adults (8/16, mean age 25.0 years), were recruited and participated in this study. The handling cycle consisted of seven main tasks. Data analysis started with the analysis of task effectiveness for searching for error-related tasks. Subsequently, the in-depth gaze data analysis focused on these identified critical tasks. In order to understand the challenges of user cognition in critical tasks, gaze data were analyzed with respect to individual user interface features of the medical device system. Therefore, it focused on the two dimensions of dwell time and fixation duration of the gaze. Results In total, 97% of the handling steps for design 1 and 96% for design 2 were performed correctly, with the main challenges being task 1 insert, task 2 connect, and task 6 disconnect for both designs. In order to understand the two analyzed dimensions of the physiological measurements simultaneously, the authors propose a new graphical representation. It distinguishes four different patterns to compare the eye movements associated with the two designs. The patterns identified for the critical tasks are consistent with the results of the task performance. Conclusions This study showed that mobile eye tracking provides insights into information processing in intensive handling tasks related to individual user interface features. The evaluation of each feature of the user interface promises an optimal design by combining the best found features. In this way, manufacturers are able to develop products that can be used by untrained people without prior knowledge. This would allow home care to be provided not only by highly qualified nurses and caregivers, but also by patients themselves, partners, children, or neighbors.

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Herman, L., and Z. Stachoň. "COMPARISON OF USER PERFORMANCE WITH INTERACTIVE AND STATIC 3D VISUALIZATION – PILOT STUDY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 655–61. http://dx.doi.org/10.5194/isprsarchives-xli-b2-655-2016.

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Interactive 3D visualizations of spatial data are currently available and popular through various applications such as Google Earth, ArcScene, etc. Several scientific studies have focused on user performance with 3D visualization, but static perspective views are used as stimuli in most of the studies. The main objective of this paper is to try to identify potential differences in user performance with static perspective views and interactive visualizations. This research is an exploratory study. An experiment was designed as a between-subject study and a customized testing tool based on open web technologies was used for the experiment. The testing set consists of an initial questionnaire, a training task and four experimental tasks. Selection of the highest point and determination of visibility from the top of a mountain were used as the experimental tasks. Speed and accuracy of each task performance of participants were recorded. The movement and actions in the virtual environment were also recorded within the interactive variant. The results show that participants deal with the tasks faster when using static visualization. The average error rate was also higher in the static variant. The findings from this pilot study will be used for further testing, especially for formulating of hypotheses and designing of subsequent experiments.

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Herman, L., and Z. Stachoň. "COMPARISON OF USER PERFORMANCE WITH INTERACTIVE AND STATIC 3D VISUALIZATION – PILOT STUDY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 655–61. http://dx.doi.org/10.5194/isprs-archives-xli-b2-655-2016.

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Interactive 3D visualizations of spatial data are currently available and popular through various applications such as Google Earth, ArcScene, etc. Several scientific studies have focused on user performance with 3D visualization, but static perspective views are used as stimuli in most of the studies. The main objective of this paper is to try to identify potential differences in user performance with static perspective views and interactive visualizations. This research is an exploratory study. An experiment was designed as a between-subject study and a customized testing tool based on open web technologies was used for the experiment. The testing set consists of an initial questionnaire, a training task and four experimental tasks. Selection of the highest point and determination of visibility from the top of a mountain were used as the experimental tasks. Speed and accuracy of each task performance of participants were recorded. The movement and actions in the virtual environment were also recorded within the interactive variant. The results show that participants deal with the tasks faster when using static visualization. The average error rate was also higher in the static variant. The findings from this pilot study will be used for further testing, especially for formulating of hypotheses and designing of subsequent experiments.

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Byrne, Jody. "Evaluating the Effect of Iconic Linkage on the Usability of Software User Guides." Journal of Technical Writing and Communication 35, no. 2 (April 2005): 155–78. http://dx.doi.org/10.2190/uuql-xbrf-ukl6-mrgy.

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This study investigates whether Iconic Linkage—the use of the identical wording to present the same information recurring in a text—can improve the usability of user guides. Iconic Linkage is a writing strategy that potentially allows users to work more quickly and effectively and which promotes better retention of information. The usefulness of Iconic Linkage was tested in a laboratory-based usability study that combined: 1) objective task-based evaluation; and 2) users' subjective evaluations of a software program used in recording parliamentary debates. A post-test survey designed to test subjects' retention of information contained in the user guides was also administered. The study shows that Iconic Linkage significantly improved usability of the user guide: in all tasks, subjects worked more effectively and made fewer mistakes; while in the three timed tasks, subjects completed the tasks much more quickly. Subjects also gave higher ratings for the software and their retention of information was noticeably improved.

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Zhu, Weiping, Wenzhong Guo, and Zhiyong Yu. "Social-Aware Task Allocation in Mobile Crowd Sensing." Wireless Communications and Mobile Computing 2020 (October 14, 2020): 1–15. http://dx.doi.org/10.1155/2020/8822251.

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Task allocation is a significant issue in crowd sensing, which trades off the data quality and sensing cost. Existing task allocation works are based on the assumption that there is plenty of users available in the candidate pool. However, for some specific applications, there may be only a few candidate users, resulting in the poor completion of tasks. To tackle this problem, in this paper, we investigate the task allocation problem with the assistance of social networks. We select a subset of users; if a user can not complete the task, he can propagate the task information to his friends. The object of this problem is to maximize the expected number of completed tasks. We prove that the task allocation problem is an NP-hard and submodular problem and then propose a native greedy selection (NGS) algorithm, which selects the user with maximum margin gain in each round. To improve the efficiency of the NGS algorithm, we further propose a fast greedy selection algorithm (FGS), which selects the user who can actually complete the maximum number of tasks. Experimental results show that although FGS gets slightly worse results in terms of the expected number of completed tasks, it can greatly reduce the running time of seed selection.

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Ashlund, Stacey, and Deborah Hix. "Ideal: A Software Tool to Evaluate Interface Usability." Proceedings of the Human Factors Society Annual Meeting 36, no. 4 (October 1992): 414–17. http://dx.doi.org/10.1177/154193129203600432.

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This paper reports on the design, prototype implementation, and formative evaluation of a software tool—IDEAL (Interface Design Environment and Analysis Lattice). IDEAL integrates usability engineering techniques and behavioral task representations with a graphical hierarchy of user tasks to support formative evaluation of an evolving user interface. Representative users of IDEAL—interface designers and evaluators—participated in two phases of formative evaluation of IDEAL. Empirical evaluation showed IDEAL to be useful as an automated tool for managing the interrelated tasks of user interface development, including interaction design, usability specification, creation of benchmark tasks, and formative evaluation, that are currently performed manually.

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Yaverbaum, Gayle J. "Critical Factors in the User Environment: An Experimental Study of Users, Organizations and Tasks." MIS Quarterly 12, no. 1 (March 1988): 75. http://dx.doi.org/10.2307/248807.

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Muguro, Joseph K., Pringgo Widyo Laksono, Yuta Sasatake, Kojiro Matsushita, and Minoru Sasaki. "User Monitoring in Autonomous Driving System Using Gamified Task: A Case for VR/AR In-Car Gaming." Multimodal Technologies and Interaction 5, no. 8 (July 21, 2021): 40. http://dx.doi.org/10.3390/mti5080040.

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Background: As Automated Driving Systems (ADS) technology gets assimilated into the market, the driver’s obligation will be changed to a supervisory role. A key point to consider is the driver’s engagement in the secondary task to maintain the driver/user in the control loop. This paper aims to monitor driver engagement with a game and identify any impacts the task has on hazard recognition. Methods: We designed a driving simulation using Unity3D and incorporated three tasks: No-task, AR-Video, and AR-Game tasks. The driver engaged in an AR object interception game while monitoring the road for threatening road scenarios. Results: There was a significant difference in the tasks (F(2,33) = 4.34, p = 0.0213), identifying the game-task as significant with respect to reaction time and ideal for the present investigation. Game scoring followed three profiles/phases: learning, saturation, and decline profile. From the profiles, it is possible to quantify/infer drivers’ engagement with the game task. Conclusion: The paper proposes alternative monitoring that has utility, i.e., entertaining the user. Further experiments with AR-Games focusing on the real-world car environment will be performed to confirm the performance following the recommendations derived from the current test.

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Jung, Jieun, Min Jung, Jae-Ho Jeon, Gye-Jeong Jeon, and Seojeong Lee. "Development and User Test of Standard Navigational Tasks to Improve User Interface of Navigational Equipment." Journal of Digital Contents Society 19, no. 10 (October 31, 2018): 1981–88. http://dx.doi.org/10.9728/dcs.2018.19.10.1981.

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Olaverri-Monreal, Cristina, Ahmed Elsherbiny Hasan, and Klaus Bengler. "Intelligent Agent (IA) Systems to Generate User Stories for a Positive User Experience." International Journal of Human Capital and Information Technology Professionals 5, no. 1 (January 2014): 26–40. http://dx.doi.org/10.4018/ijhcitp.2014010103.

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In User Centered Design (UCD) approaches within software development processes, understanding of users, tasks and environments identifying needs and establishing requirements for a positive user experience (UX) is essential to achieve a high usability. The quantitative measurement of UX relies on the fulfillment of psychological needs that can be addressed in storyboards in order to create a context for a certain experience with a particular application. To facilitate the process of capturing software products functionality, we present in this work a framework based on Intelligent Agent (IA) systems to semi-automatically generate user stories. A strong story line is guaranteed by a character-centric approach and additional supportive agents that are defined through characters' properties in form of needs, behaviors skills and goals. Moreover, we allow for the storage of the created characters into a database, so that they can be reused for further stories and we perform a usability evaluation on the user interface to ensure that it meets users' expectations. The system was classified as easy to use and suitable to perform the intended tasks and it also met users' expectation.

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Journal articles on the topic 'User tasks'

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