579 research outputs found

    The man/machine interface in information retrieval: Providing access to the casual user

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    This study is concerned with the difficulties encountered by casual users wishing to employ Information Storage and Retrieval Systems. A casual user is defined as a professional who has neither time nor desire to pursue in depth the study of the numerous and varied retrieval systems. His needs for on-line search are only occasional, and not limited to any particular system. The paper takes a close look at the state of the art of research concerned with aiding casual users of Information Storage and Retrieval Systems. Current experiments such as LEXIS, CONIT, IIDA, CITE, and CCL are presented and discussed. Comments and proposals are offered, specifically in the areas of training, learning and cost as experienced by the casual user. An extensive bibliography of recent works on the subject follows the text

    Dialogue Design for a Robot-Based Face-Mirroring Game to Engage Autistic Children with Emotional Expressions

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    We present design strategies for Human Robot Interaction for school-aged autistic children with limited receptive language. Applying these strategies to the DE-ENIGMA project (large EU project addressing emotion recognition in autistic children) supported development of a new activity for in facial expression imitation whereby the robot imitates the child’s face to encourage the child to notice facial expressions in a play-based game. A usability case study with 15 typically-developing children aged 4–6 at an English-language school in the Netherlands was performed to observe the feasibility of the setup and make design revisions before exposing the robot to autistic children

    StoryDroid: Automated Generation of Storyboard for Android Apps

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    Mobile apps are now ubiquitous. Before developing a new app, the development team usually endeavors painstaking efforts to review many existing apps with similar purposes. The review process is crucial in the sense that it reduces market risks and provides inspiration for app development. However, manual exploration of hundreds of existing apps by different roles (e.g., product manager, UI/UX designer, developer) in a development team can be ineffective. For example, it is difficult to completely explore all the functionalities of the app in a short period of time. Inspired by the conception of storyboard in movie production, we propose a system, StoryDroid, to automatically generate the storyboard for Android apps, and assist different roles to review apps efficiently. Specifically, StoryDroid extracts the activity transition graph and leverages static analysis techniques to render UI pages to visualize the storyboard with the rendered pages. The mapping relations between UI pages and the corresponding implementation code (e.g., layout code, activity code, and method hierarchy) are also provided to users. Our comprehensive experiments unveil that StoryDroid is effective and indeed useful to assist app development. The outputs of StoryDroid enable several potential applications, such as the recommendation of UI design and layout code

    An analytical inspection framework for evaluating the search tactics and user profiles supported by information seeking interfaces

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    Searching is something we do everyday both in digital and physical environments. Whether we are searching for books in a library or information on the web, search is becoming increasingly important. For many years, however, the standard for search in software has been to provide a keyword search box that has, over time, been embellished with query suggestions, Boolean operators, and interactive feedback. More recent research has focused on designing search interfaces that better support exploration and learning. Consequently, the aim of this research has been to develop a framework that can reveal to designers how well their search interfaces support different styles of searching behaviour.The primary contribution of this research has been to develop a usability evaluation method, in the form of a lightweight analytical inspection framework, that can assess both search designs and fully implemented systems. The framework, called Sii, provides three types of analyses: 1) an analysis of the amount of support the different features of a design provide; 2) an analysis of the amount of support provided for 32 known search tactics; and 3) an analysis of the amount of support provided for 16 different searcher profiles, such as those who are finding, browsing, exploring, and learning. The design of the framework was validated by six independent judges, and the results were positively correlated against the results of empirical user studies. Further, early investigations showed that Sii has a learning curve that begins at around one and a half hours, and, when using identical analysis results, different evaluators produce similar design revisions.For Search experts, building interfaces for their systems, Sii provides a Human-Computer Interaction evaluation method that addresses searcher needs rather than system optimisation. For Human-Computer Interaction experts, designing novel interfaces that provide search functions, Sii provides the opportunity to assess designs using the knowledge and theories generated by the Information Seeking community. While the research reported here is under controlled environments, future work is planned that will investigate the use of Sii by independent practitioners on their own projects

    Special Libraries, December 1964

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    Volume 55, Issue 10https://scholarworks.sjsu.edu/sla_sl_1964/1009/thumbnail.jp

    Special Libraries, December 1964

    Get PDF
    Volume 55, Issue 10https://scholarworks.sjsu.edu/sla_sl_1964/1009/thumbnail.jp

    Supporting Voice-Based Natural Language Interactions for Information Seeking Tasks of Various Complexity

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    Natural language interfaces have seen a steady increase in their popularity over the past decade leading to the ubiquity of digital assistants. Such digital assistants include voice activated assistants, such as Amazon's Alexa, as well as text-based chat bots that can substitute for a human assistant in business settings (e.g., call centers, retail / banking websites) and at home. The main advantages of such systems are their ease of use and - in the case of voice-activated systems - hands-free interaction. The majority of tasks undertaken by users of these commercially available voice-based digital assistants are simple in nature, where the responses of the agent are often determined using a rules-based approach. However, such systems have the potential to support users in completing more complex and involved tasks. In this dissertation, I describe experiments investigating user behaviours when interacting with natural language systems and how improvements in design of such systems can benefit the user experience. Currently available commercial systems tend to be designed in a way to mimic superficial characteristics of a human-to-human conversation. However, the interaction with a digital assistant differs significantly from the interaction between two people, partly due to limitations of the underlying technology such as automatic speech recognition and natural language understanding. As computing technology evolves, it may make interactions with digital assistants resemble those between humans. The first part of this thesis explores how users will perceive the systems that are capable of human-level interaction, how users will behave while communicating with such systems, and new opportunities that may be opened by that behaviour. Even in the absence of the technology that allows digital assistants to perform on a human level, the digital assistants that are widely adopted by people around the world are found to be beneficial for a number of use-cases. The second part of this thesis describes user studies aiming at enhancing the functionality of digital assistants using the existing level of technology. In particular, chapter 6 focuses on expanding the amount of information a digital assistant is able to deliver using a voice-only channel, and chapter 7 explores how expanded capabilities of voice-based digital assistants would benefit people with visual impairments. The experiments presented throughout this dissertation produce a set of design guidelines for existing as well as potential future digital assistants. Experiments described in chapters 4, 6, and 7 focus on supporting the task of finding information online, while chapter 5 considers a case of guiding a user through a culinary recipe. The design recommendations provided by this thesis can be generalised in four categories: how naturally a user can communicate their thoughts to the system, how understandable the system's responses are to the user, how flexible the system's parameters are, and how diverse the information delivered by the system is
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