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A Syndicated Adaptive News-feed: The Energy Hub

Published: 04 February 2020 Publication History

Abstract

Adaptive User Interfaces (AUI) change their presentation and content depending on the individual needs of their client. In our work, we aim to create a AUI that collects articles on “energy-related” issues from various publishers using Google’s Custom Search and NEWS API. We call this AUI news-feed service “The Energy Hub”. We have compared the articles that result from a search from generic search engines with that of “Energy Hub”. The latter shows more promising results with better precision. In future work, we aim to provide all thematically related articles to the reader, customised by user preferences and by their interactions with the AUI. The intention is to improve the reader’s experience using text mining and search-term clustering, including topic modelling. An important aspect of our work is the judgement of the success of the Energy-hub AUI, and we identify a methodology for its evaluation.

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  1. A Syndicated Adaptive News-feed: The Energy Hub

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    cover image ACM Other conferences
    ACSW '20: Proceedings of the Australasian Computer Science Week Multiconference
    February 2020
    367 pages
    ISBN:9781450376976
    DOI:10.1145/3373017
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 04 February 2020

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    Author Tags

    1. Adaptable user interface
    2. news recommender system
    3. text mining.
    4. topic modelling

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    ACSW '20
    ACSW '20: Australasian Computer Science Week 2020
    February 4 - 6, 2020
    VIC, Melbourne, Australia

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    Overall Acceptance Rate 61 of 141 submissions, 43%

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