10,207 research outputs found

    Natural language processing

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    Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

    Structuring visual exploratory analysis of skill demand

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    The analysis of increasingly large and diverse data for meaningful interpretation and question answering is handicapped by human cognitive limitations. Consequently, semi-automatic abstraction of complex data within structured information spaces becomes increasingly important, if its knowledge content is to support intuitive, exploratory discovery. Exploration of skill demand is an area where regularly updated, multi-dimensional data may be exploited to assess capability within the workforce to manage the demands of the modern, technology- and data-driven economy. The knowledge derived may be employed by skilled practitioners in defining career pathways, to identify where, when and how to update their skillsets in line with advancing technology and changing work demands. This same knowledge may also be used to identify the combination of skills essential in recruiting for new roles. To address the challenges inherent in exploring the complex, heterogeneous, dynamic data that feeds into such applications, we investigate the use of an ontology to guide structuring of the information space, to allow individuals and institutions to interactively explore and interpret the dynamic skill demand landscape for their specific needs. As a test case we consider the relatively new and highly dynamic field of Data Science, where insightful, exploratory data analysis and knowledge discovery are critical. We employ context-driven and task-centred scenarios to explore our research questions and guide iterative design, development and formative evaluation of our ontology-driven, visual exploratory discovery and analysis approach, to measure where it adds value to users’ analytical activity. Our findings reinforce the potential in our approach, and point us to future paths to build on

    Flight deck automation: Promises and realities

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    Issues of flight deck automation are multifaceted and complex. The rapid introduction of advanced computer-based technology onto the flight deck of transport category aircraft has had considerable impact both on aircraft operations and on the flight crew. As part of NASA's responsibility to facilitate an active exchange of ideas and information among members of the aviation community, a NASA/FAA/Industry workshop devoted to flight deck automation, organized by the Aerospace Human Factors Research Division of NASA Ames Research Center. Participants were invited from industry and from government organizations responsible for design, certification, operation, and accident investigation of transport category, automated aircraft. The goal of the workshop was to clarify the implications of automation, both positive and negative. Workshop panels and working groups identified issues regarding the design, training, and procedural aspects of flight deck automation, as well as the crew's ability to interact and perform effectively with the new technology. The proceedings include the invited papers and the panel and working group reports, as well as the summary and conclusions of the conference

    Information Outlook, October 2004

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    Volume 8, Issue 10https://scholarworks.sjsu.edu/sla_io_2004/1009/thumbnail.jp

    Cyber Threat Observatory: Design and Evaluation of an Interactive Dashboard for Computer Emergency Response Teams

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    Computer emergency response teams (CERTs) of the public sector provide preventive and reactive cybersecurity services for authorities, citizens, and enterprises. However, their tasks of monitoring, analyzing, and communicating threats to establish cyber situational awareness are getting more complex due to the increasing information volume disseminated through public channels. Besides the time-consuming data collection for incident handling and daily reporting, CERTs are often confronted with irrelevant, redundant, or incredible information, exacerbating the time-critical prevention of and response to cyber threats. Thus, this design science research paper presents the user-centered design and evaluation of the Cyber Threat Observatory, which is an automatic, cross-platform and real-time cybersecurity dashboard. Based on expert scenario-based walkthroughs and semi-structured interviews (N=12), it discusses six design implications, including customizability and filtering, data source modularity, cross-platform interrelations, content assessment algorithms, integration with existing software, as well as export and communication capabilities

    Cognitive BPM as an Equalizer: Improving Access and Efficiency for Employees with (and without) Cognitive Disabilities

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    We examine ProcessGPT, an AI model designed to automate, augment, and improve business processes, to study the challenges of managing business processes within the cognitive limitations of the human workforce, particularly individuals with cognitive disabilities. ProcessGPT provides a blueprint for designing efficient business processes that take into account human cognitive limitations. By viewing this through the lens of cognitive disabilities, we show that ProcessGPT improves process usability for individuals with and without cognitive disabilities. We also demonstrate that organizations implementing ProcessGPT-like capabilities will realize increased productivity, morale, and inclusion.Comment: 7 pages, 2 figure

    Social Media for Cities, Counties and Communities

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    Social media (i.e., Twitter, Facebook, Flickr, YouTube) and other tools and services with user- generated content have made a staggering amount of information (and misinformation) available. Some government officials seek to leverage these resources to improve services and communication with citizens, especially during crises and emergencies. Yet, the sheer volume of social data streams generates substantial noise that must be filtered. Potential exists to rapidly identify issues of concern for emergency management by detecting meaningful patterns or trends in the stream of messages and information flow. Similarly, monitoring these patterns and themes over time could provide officials with insights into the perceptions and mood of the community that cannot be collected through traditional methods (e.g., phone or mail surveys) due to their substantive costs, especially in light of reduced and shrinking budgets of governments at all levels. We conducted a pilot study in 2010 with government officials in Arlington, Virginia (and to a lesser extent representatives of groups from Alexandria and Fairfax, Virginia) with a view to contributing to a general understanding of the use of social media by government officials as well as community organizations, businesses and the public. We were especially interested in gaining greater insight into social media use in crisis situations (whether severe or fairly routine crises, such as traffic or weather disruptions)
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