Human-machine conversations to support mission-oriented information provision

Preece, Alun David ORCID: https://orcid.org/0000-0003-0349-9057, Braines, Dave, Pizzocaro, Diego ORCID: https://orcid.org/0000-0003-1976-8805 and Parizas, Christos 2013. Human-machine conversations to support mission-oriented information provision. Presented at: Mobicom 2013: The 19th Annual International Conference on Mobile Computing and Networking, Miami, FL., USA, 30 Sept - 4 Oct 2013. MiSeNet '13: Proceedings of the 2nd ACM Annual International Workshop on Mission-Oriented Wireless Sensor Networking. ACM, pp. 43-50. 10.1145/2509338.2509342

Full text not available from this repository.

Abstract

Mission-oriented sensor networks present challenging problems in terms of human-machine collaboration. Human users need to task the network to help them achieve mission objectives, while humans (sometimes the same individuals) are also sources of mission-critical information. We propose a natural language-based conversational approach to supporting human-machine working in mission-oriented sensor networks. We present a model for human-machine and machine-machine interactions in a realistic mission context, and evaluate the model using an existing surveillance mission scenario. The model supports the flow of conversations from full natural language to a form of Controlled Natural Language (CNL) amenable to machine processing and automated reasoning, including high-level information fusion tasks. We introduce a mechanism for presenting the gist of verbose CNL expressions in a more convenient form for human users. We show how the conversational interactions supported by the model include requests for expansions and explanations of machine-processed information.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Schools > Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher:	ACM
ISBN:	9781450323673
Related URLs:	Organisation
Last Modified:	11 Jun 2023 01:18
URI:	https://orca.cardiff.ac.uk/id/eprint/53514

Citation Data

Cited 2 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item