9,608 research outputs found

    An embodied conversational agent for intelligent web interaction on pandemic crisis communication

    Get PDF
    In times of crisis, an effective communication mechanism is paramount in providing accurate and timely information to the community. In this paper we study the use of an intelligent embodied conversational agent (EGA) as the front end interface with the public for a Crisis Communication Network Portal (CCNet). The proposed system, CCNet, is an integration of the intelligent conversation agent, AINI, and an Automated Knowledge Extraction Agent (AKEA). AKEA retrieves first hand information from relevant sources such as government departments and news channels. In this paper, we compare the interaction of AINI against two popular search engines, two question answering systems and two conversational systems

    Research Reports: 1984 NASA/ASEE Summer Faculty Fellowship Program

    Get PDF
    A NASA/ASEE Summer Faulty Fellowship Program was conducted at the Marshall Space Flight Center (MSFC). The basic objectives of the programs are: (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate an exchange of ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of the participants' institutions; and (4) to contribute to the research objectives of the NASA Centers. The Faculty Fellows spent ten weeks at MSFC engaged in a research project compatible with their interests and background and worked in collaboration with a NASA/MSFC colleague. This document is a compilation of Fellows' reports on their research during the summer of 1984. Topics covered include: (1) data base management; (2) computational fluid dynamics; (3) space debris; (4) X-ray gratings; (5) atomic oxygen exposure; (6) protective coatings for SSME; (7) cryogenics; (8) thermal analysis measurements; (9) solar wind modelling; and (10) binary systems

    Learning a Policy for Opportunistic Active Learning

    Full text link
    Active learning identifies data points to label that are expected to be the most useful in improving a supervised model. Opportunistic active learning incorporates active learning into interactive tasks that constrain possible queries during interactions. Prior work has shown that opportunistic active learning can be used to improve grounding of natural language descriptions in an interactive object retrieval task. In this work, we use reinforcement learning for such an object retrieval task, to learn a policy that effectively trades off task completion with model improvement that would benefit future tasks.Comment: EMNLP 2018 Camera Read

    A natural language interface to databases

    Get PDF
    The development of a Natural Language Interface which is semantic-based and uses Conceptual Dependency representation is presented. The system was developed using Lisp and currently runs on a Symbolics Lisp machine. A key point is that the parser handles morphological analysis, which expands its capabilities of understanding more words
    • …
    corecore