| 1. |
- Liu, Yuanhua, 1971, et al.
(författare)
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Considering the importance of user profiles in interface design
- 2009
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Ingår i: User Interfaces. ; , s. 23-
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- User profile is a popular term widely employed during product design processes by industrial companies. Such a profile is normally intended to represent real users of a product. The ultimate purpose of a user profile is actually to help designers to recognize or learn about the real user by presenting them with a description of a real user’s attributes, for instance; the user’s gender, age, educational level, attitude, technical needs and skill level. The aim of this chapter is to provide information on the current knowledge and research about user profile issues, as well as to emphasize the importance of considering these issues in interface design. In this chapter, we mainly focus on how users’ difference in expertise affects their performance or activity in various interaction contexts. Considering the complex interaction situations in practice, novice and expert users’ interactions with medical user interfaces of different technical complexity will be analyzed as examples: one focuses on novice and expert users’ difference when interacting with simple medical interfaces, and the other focuses on differences when interacting with complex medical interfaces. Four issues will be analyzed and discussed: (1) how novice and expert users differ in terms of performance during the interaction; (2) how novice and expert users differ in the perspective of cognitive mental models during the interaction; (3) how novice and expert users should be defined in practice; and (4) what are the main differences between novice and expert users’ implications for interface design. Besides describing the effect of users’ expertise difference during the interface design process, we will also pinpoint some potential problems for the research on interface design, as well as some future challenges that academic researchers and industrial engineers should face in practice.
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| 2. |
- Wilhelmsson, Kenneth, 1976
(författare)
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Om förutsättningarna för språkligt datorstöd på ordnivån och uppåt
- 2017
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Ingår i: Text och kontext - perspektiv på textanalys / Karin Helgesson, Hans Lundqvist, Anna Lyngfelt, Andreas Nord & Åsa Wengelin (red.). - Malmö : Gleerups. - 9789140693648 ; , s. 207-228
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 3. |
- Dodig-Crnkovic, Gordana, 1955
(författare)
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Cognitive Architectures Based on Natural Info-Computation
- 2022
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Ingår i: Studies in Applied Philosophy, Epistemology and Rational Ethics. - Cham : Springer. - 2192-6255 .- 2192-6263. ; , s. 3-13, s. 3-13
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Bokkapitel (refereegranskat)abstract
- At the time when the first models of cognitive architectures have been proposed, some forty years ago, understanding of cognition, embodiment and evolution was substantially different from today’s. So was the state of the art of information physics, information chemistry, bioinformatics, neuroinformatics, computational neuroscience, complexity theory, self-organization, theory of evolution, as well as the basic concepts of information and computation. Novel developments support a constructive interdisciplinary framework for cognitive architectures based on natural morphological computing, where interactions between constituents at different levels of organization of matter-energy and their corresponding time-dependent dynamics, lead to complexification of agency and increased cognitive capacities of living organisms that unfold through evolution. Proposed info-computational framework for naturalizing cognition considers present updates (generalizations) of the concepts of information, computation, cognition, and evolution in order to attain an alignment with the current state of the art in corresponding research fields. Some important open questions are suggested for future research with implications for further development of cognitive and intelligent technologies.
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| 4. |
- Laaber, C., et al.
(författare)
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An Evaluation of Open-Source Software Microbenchmark Suites for Continuous Performance Assessment
- 2018
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Ingår i: MSR '18 Proceedings of the 15th International Conference on Mining Software Repositories. - New York, NY, USA : ACM Digital Library. - 9781450357166 ; , s. 119-130, s. 119-130
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Continuous integration (CI) emphasizes quick feedback to developers. This is at odds with current practice of performance testing, which predominantely focuses on long-running tests against entire systems in production-like environments. Alternatively, software microbenchmarking attempts to establish a performance baseline for small code fragments in short time. This paper investigates the quality of microbenchmark suites with a focus on suitability to deliver quick performance feedback and CI integration. We study ten open-source libraries written in Java and Go with benchmark suite sizes ranging from 16 to 983 tests, and runtimes between 11 minutes and 8.75 hours. We show that our study subjects include benchmarks with result variability of 50% or higher, indicating that not all benchmarks are useful for reliable discovery of slow-downs. We further artificially inject actual slowdowns into public API methods of the study subjects and test whether test suites are able to discover them. We introduce a performance-test quality metric called the API benchmarking score (ABS). ABS represents a benchmark suite's ability to find slowdowns among a set of defined core API methods. Resulting benchmarking scores (i.e., fraction of discovered slowdowns) vary between 10% and 100% for the study subjects. This paper's methodology and results can be used to (1) assess the quality of existing microbenchmark suites, (2) select a set of tests to be run as part of CI, and (3) suggest or generate benchmarks for currently untested parts of an API.
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| 5. |
- Rafiq, Y., et al.
(författare)
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Learning to Share: Engineering Adaptive Decision-Support for Online Social Networks
- 2017
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Ingår i: PROCEEDINGS OF THE 2017 32ND IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE'17). - 1527-1366. - 9781538626849 ; , s. 280-285
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Some online social networks (OSNs) allow users to define friendship-groups as reusable shortcuts for sharing information with multiple contacts. Posting exclusively to a friendship-group gives some privacy control, while supporting communication with (and within) this group. However, recipients of such posts may want to reuse content for their own social advantage, and can bypass existing controls by copy-pasting into a new post; this cross-posting poses privacy risks. This paper presents a learning to share approach that enables the incorporation of more nuanced privacy controls into OSNs. Specifically, we propose a reusable, adaptive software architecture that uses rigorous runtime analysis to help OSN users to make informed decisions about suitable audiences for their posts. This is achieved by supporting dynamic formation of recipient-groups that benefit social interactions while reducing privacy risks. We exemplify the use of our approach in the context of Facebook.
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| 6. |
- Palmquist, Adam, 1983, et al.
(författare)
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AUTOMATON : A Gamification Machine Learning Project
- 2023
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Ingår i: Encyclopedia of Data Science and Machine Learning. - : IGI Global. - 9781799892205 - 1799892204 - 9781799892212 ; , s. 3090-3101
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Bokkapitel (refereegranskat)abstract
- This article displays a design ethnographic case study on an ongoing machine learning project at a Scandinavian gamification start-up company. From late 2020 until early 2021, the project produced a machine learning proof of concept, later implemented in the gamification start-up´s application programming interface to offer smart gamification. The initial results show promise in using prediction models to automate the cluster model selection affording more functional, autonomous, and scalable user segments that are faster to implement. The finding provides opportunities for gamification (e.g., in learning analytics and health informatics). An identified challenge was performance; the neural networks required hyperparameter fine-tuning, which is time-consuming and limits scalability. Interesting further investigations should consider the neural network fine-tuning process, but also attempt to verify the effectiveness of the cluster models selection compared with a control group.
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| 7. |
- Bae, Juhee, et al.
(författare)
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Complex Data Analysis
- 2019
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Ingår i: Data science in Practice. - Cham : Springer. - 9783319975566 - 9783319975559 ; , s. 157-169
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Bokkapitel (refereegranskat)abstract
- Data science applications often need to deal with data that does not fit into the standard entity-attribute-value model. In this chapter we discuss three of these other types of data. We discuss texts, images and graphs. The importance of social media is one of the reason for the interest on graphs as they are a way to represent social networks and, in general, any type of interaction between people. In this chapter we present examples of tools that can be used to extract information and, thus, analyze these three types of data. In particular, we discuss topic modeling using a hierarchical statistical model as a way to extract relevant topics from texts, image analysis using convolutional neural networks, and measures and visual methods to summarize information from graphs.
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| 8. |
- Bae, Juhee, et al.
(författare)
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Visual Data Analysis
- 2019
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Ingår i: Data science in Practice. - Cham : Springer. - 9783319975566 - 9783319975559 ; , s. 133-155
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Bokkapitel (refereegranskat)abstract
- Data Science offers a set of powerful approaches for making new discoveries from large and complex data sets. It combines aspects of mathematics, statistics, machine learning, etc. to turn vast amounts of data into new insights and knowledge. However, the sole use of automatic data science techniques for large amounts of complex data limits the human user’s possibilities in the discovery process, since the user is estranged from the process of data exploration. This chapter describes the importance of Information Visualization (InfoVis) and visual analytics (VA) within data science and how interactive visualization can be used to support analysis and decision-making, empowering and complementing data science methods. Moreover, we review perceptual and cognitive aspects, together with design and evaluation methodologies for InfoVis and VA.
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| 9. |
- Boulund, Fredrik, et al.
(författare)
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Computational and Statistical Considerations in the Analysis of Metagenomic Data
- 2018
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Ingår i: Metagenomics: Perspectives, Methods, and Applications. - 9780081022689 ; , s. 81-102
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- In shotgun metagenomics, microbial communities are studied by random DNA fragments sequenced directly from environmental and clinical samples. The resulting data is massive, potentially consisting of billions of sequence reads describing millions of microbial genes. The data interpretation is therefore nontrivial and dependent on dedicated computational and statistical methods. In this chapter we discuss the many challenges associated with the analysis of shotgun metagenomic data. First, we address computational issues related to the quantification of genes in metagenomes. We describe algorithms for efficient sequence comparisons, recommended practices for setting up data workflows and modern high-performance computer resources that can be used to perform the analysis. Next, we outline the statistical aspects, including removal of systematic errors and how to identify differences between microbial communities from different experimental conditions. We conclude by underlining the increasing importance of efficient and reliable computational and statistical solutions in the analysis of large metagenomic datasets.
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| 10. |
- Torra, Vicenç, et al.
(författare)
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Data privacy
- 2019
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Ingår i: Data science in Practice. - Cham : Springer. - 9783319975566 - 9783319975559 ; , s. 121-132
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Bokkapitel (refereegranskat)abstract
- In this chapter we present an overview of the topic data privacy. We review privacy models and measures of disclosure risk. These models and measures provide computational definitions of what privacy means, and of how to evaluate the privacy level of a data set. Then, we give a summary of data protection mechanisms. We provide a classification of these methods according to three dimensions: whose privacy is being sought, the computations to be done, and the number of data sources. Finally, we describe masking methods. Such methods are the data protection mechanisms used for databases when the data use is undefined and the protected database is required to be useful for several data uses. We also provide a definition of information loss (or data utility) for this type of data protection mechanism. The chapter finishes with a summary.
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