436 research outputs found

    Recommendations based on social links

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    The goal of this chapter is to give an overview of recent works on the development of social link-based recommender systems and to offer insights on related issues, as well as future directions for research. Among several kinds of social recommendations, this chapter focuses on recommendations, which are based on users’ self-defined (i.e., explicit) social links and suggest items, rather than people of interest. The chapter starts by reviewing the needs for social link-based recommendations and studies that explain the viability of social networks as useful information sources. Following that, the core part of the chapter dissects and examines modern research on social link-based recommendations along several dimensions. It concludes with a discussion of several important issues and future directions for social link-based recommendation research

    Information Systems Research Themes: A Seventeen-year Data-driven Temporal Analysis

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    Extending the research on our discipline’s identity, we examine how the major research themes have evolved in four top IS journals: Management Information Systems Quarterly (MISQ), Information Systems Research (ISR), Journal of the Association for Information Systems (JAIS), and Journal of Management Information Systems (JMIS). By doing so, we answer Palvia, Daneshvar Kakhki, Ghoshal, Uppala, and Wang’s (2015) call to provide continuous updates to the research trends in IS due to the discipline’s dynamism. Second, building on Sidorov, Evangelopoulos, Valacich, and Ramakrishnan (2008) we examine temporal trends in prominent research streams over the last 17 years. We show that, as IS research evolves over time, certain themes appear to endure the test of time, while others peak and trough. More importantly, our analysis identifies new emergent themes that have begun to gain prominence in IS research community. Further, we break down our findings by journal and show the type of content that they may desire most. Our findings also allow the IS research community to discern the specific contributions and roles of our premier journals in the evolution of research themes over time

    A Self-Regulated Learning Approach to Educational Recommender Design

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    Recommender systems, or recommenders, are information filtering systems prevalent today in many fields. One type of recommender found in the field of education, the educational recommender, is a key component of adaptive learning solutions as these systems avoid “one-size-fits-all” approaches by tailoring the learning process to the needs of individual learners. To function, these systems utilize learning analytics in a student-facing manner. While existing research has shown promise and explores a variety of types of educational recommenders, there is currently a lack of research that ties educational theory to the design and implementation of these systems. The theory considered here, self-regulated learning, is underexplored in educational recommender research. Self-regulated learning advocates a cyclical feedback loop that focuses on putting students in control of their learning with consideration for activities such as goal setting, selection of learning strategies, and monitoring of one’s performance. The goal of this research is to explore how best to build a self-regulated learning guided educational recommender and discover its influence on academic success. This research applies a design science methodology in the creation of a novel educational recommender framework with a theoretical base in self-regulated learning. Guided by existing research, it advocates for a hybrid recommender approach consisting of knowledge-based and collaborative filtering, made possible by supporting ontologies that represent the learner, learning objects, and learner actions. This research also incorporates existing Information Systems (IS) theory in the evaluation, drawing further connections between these systems and the field of IS. The self-regulated learning-based recommender framework is evaluated in a higher education environment via a web-based demonstration in several case study instances using mixed-method analysis to determine this approach’s fit and perceived impact on academic success. Results indicate that the self-regulated learning-based approach demonstrated a technology fit that was positively related to student academic performance while student comments illuminated many advantages to this approach, such as its ability to focus and support various studying efforts. In addition to contributing to the field of IS research by delivering an innovative framework and demonstration, this research also results in self-regulated learning-based educational recommender design principles that serve to guide both future researchers and practitioners in IS and education

    iSchool Student Research Journal, Vol.11, Iss.1

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    Foundational Models in Medical Imaging: A Comprehensive Survey and Future Vision

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    Foundation models, large-scale, pre-trained deep-learning models adapted to a wide range of downstream tasks have gained significant interest lately in various deep-learning problems undergoing a paradigm shift with the rise of these models. Trained on large-scale dataset to bridge the gap between different modalities, foundation models facilitate contextual reasoning, generalization, and prompt capabilities at test time. The predictions of these models can be adjusted for new tasks by augmenting the model input with task-specific hints called prompts without requiring extensive labeled data and retraining. Capitalizing on the advances in computer vision, medical imaging has also marked a growing interest in these models. To assist researchers in navigating this direction, this survey intends to provide a comprehensive overview of foundation models in the domain of medical imaging. Specifically, we initiate our exploration by providing an exposition of the fundamental concepts forming the basis of foundation models. Subsequently, we offer a methodical taxonomy of foundation models within the medical domain, proposing a classification system primarily structured around training strategies, while also incorporating additional facets such as application domains, imaging modalities, specific organs of interest, and the algorithms integral to these models. Furthermore, we emphasize the practical use case of some selected approaches and then discuss the opportunities, applications, and future directions of these large-scale pre-trained models, for analyzing medical images. In the same vein, we address the prevailing challenges and research pathways associated with foundational models in medical imaging. These encompass the areas of interpretability, data management, computational requirements, and the nuanced issue of contextual comprehension.Comment: The paper is currently in the process of being prepared for submission to MI

    Telling stories with personas

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    Even though the persona method is a well-known tool in the Human-Technology Interaction field for knowing users and their goals, tasks and environments, there are varying opinions about how personas should be developed and used. Many agree that combining personas with scenarios and user stories is useful, but scenarios and user stories can also be defined and used in various ways. The purpose of my master's thesis is to examine with a literature review different ways to develop and use personas together with scenarios and user stories. My thesis aims to gain a broad picture of the topic rather than confirm one, single perspective. I will search for sources in multiple places since quantitative research alone cannot provide complete enough answers to my research questions. I have divided personas into four types based on my literature review. Manual, semi-automatic and automatic personas are based on mostly user research, but they vary on how many steps in their development are done manually. Expert personas are based on knowledge gathered from stakeholders, literature and other experts. Designers should decide the type of persona based on the purpose of the project and available data and resources. The most important elements in persona description are a photo, name, background information, goals, pain points and story. All personas in the project should be comparable by using the same elements in persona descriptions and same layout in persona documents. Deciding what sources are included in a literature review and how extensively new sources are searched for are always subjective decisions. Another limitation of my thesis is that it does not cover visual design methods, such as storyboards or user journeys. There is some academic research about personas, scenarios and user stories, but knowledge about this topic could be broadened and deepened by conducting more research on the effectiveness, popularity and usage of these methods. Comparisons of practices between countries and companies would also be interesting

    Social marketing:brand equity enhancement through social initiative co-creation

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    Abstract. In 1951, Wiebe, in an attempt to stimulate marketing scholars and practitioners to seek ways of adapting commercial marketing principles and techniques to influencing social behaviour for the good of target audiences and the society, asked: “Why should the devil always have the best tunes?” While this simple but profound question gave birth to the concept of social marketing, it also laid the ground for the persisting narrow evaluation of social behavioural change organisations only through the lens of the benefits they offer to the society, without much consideration given to how supporting social change organisations could help them make more dents on social problems and serve the society better. To overcome this limitation, social marketing scholars and practitioners have devoted resources researching and infusing concepts such as co-creation and branding, amongst others, into social marketing. To add zest to ongoing efforts geared towards improving the effectiveness of social behavioural change organisations, this study sought to examine how social behavioural change organisations can leverage social change initiatives co-creation for brand equity enhancement by integrating the concepts of social marketing, co-creation and brand equity enhancement into a holistic conceptual framework, which no existing literature has done. This qualitative study employed the observation and semi-structured interview methods to investigate a case company and arrived at two empirically validated conclusions. 1. By co-creating social change initiatives with stakeholders, behavioural change instigating organisations will gain improved brand awareness, enhanced brand perception, higher brand loyalty, positive brand association and favourable podium to extend their brands to new initiatives and commercial investments. 2. To reap these benefits, firstly, social change organisations need to be adept at identifying, segmenting and managing their ecosystem of social change co-creators. Secondly, be more purposeful and strategic in their brand and social change initiatives positioning. Thirdly, become the orchestrators of their brand and change initiatives narratives on various social media platforms used by their target audiences, co-creators and followers
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