Intelligent generative locative hyperstructure

Authors: Hargood, C., Charles, F. and Millard, D.E.

http://eprints.bournemouth.ac.uk/30536/

Start date: 9 July 2018

Locative Hypertext Narrative has seen a resurgence in the Hypertext and Interactive Narrative research communities over the last five years. However, while locative hypertext provides significant opportunities for rich locative applications for both education and entertainment many applications in this space are tied to very specific locations, restricting their utility to local users. While this is necessary for some locative applications (such as tour guides) others make use of location as a thematic or contextual backdrop and as such could be effectively read in similar locations elsewhere. However, many locative systems are restricted to use specific prescribed locations, and systems that do generate locations do so in a simplistic manner, and often with mixed results. In this paper we propose a more intelligent generative approach to locative hypertext that will generate a locative structure for the user's local area that both respects the thematic location demands of the piece and the effective patterns and structures of locative narrative.

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Authors: Hargood, C., Charles, F. and Millard, D.E.

http://eprints.bournemouth.ac.uk/30536/

Journal: HT 2018 - Proceedings of the 29th ACM Conference on Hypertext and Social Media

Pages: 238-241

ISBN: 9781450354271

DOI: 10.1145/3209542.3210574

© 2018 Association for Computing Machinery. Locative Hypertext Narrative has seen a resurgence in the Hypertext and Interactive Narrative research communities over the last five years. However, while locative hypertext provides significant opportunities for rich locative applications for both education and entertainment, many applications in this space are tied to very specific locations, restricting their utility to local users. While this is necessary for some locative applications (such as tour guides), others make use of location as a thematic or contextual backdrop and as such could be effectively read in similar locations elsewhere. However, many locative systems are restricted to use specific prescribed locations, and systems that do generate locations do so in a simplistic manner, and often with mixed results. In this paper we propose a more intelligent generative approach to locative hypertext that will generate a locative structure for the user's local area that both respects the thematic location demands of the piece and the effective patterns and structures of locative narrative.

The data on this page was last updated at 04:56 on May 20, 2019.