William M. Webberley

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As the demand for quick, live and relevant information increases, more people look to microblogging sites, such as Twitter, as a source of content. Retweeting acts as a filter of useful information for users with more interesting information likely to be disseminated further through the network. "Interestingness" denotes the level of interest in a(More)
Social networks foster the development of social sensing to gather data about situations in the environment. Making sense of this information is, however, a challenge because the process is not linear and additional sensed information may be needed to better understand a situation. In this paper we explore how two complementary technologies, Moira and(More)
Effective coalition operations require support for dynamic information gathering, processing, and sharing at the network edge for Collective Situation Understanding (CSU). To enhance CSU and leverage the combined strengths of humans and machines, we propose a conversational interface using Controlled Natural Language (CNL), which is both human readable and(More)
Controlled natural language (CNL) has great potential to support human–machine interaction (HMI) because it provides an information representation that is both human readable and machine processable. We investigated the effectiveness of a CNL-based conversational interface for HMI in a behavioral experiment called simple human experiment regarding locally(More)
Online social networks such as Twitter have emerged as an important mechanism for individuals to share information and post user generated content. However, filtering interesting content from the large volume of messages received through Twitter places a significant cognitive burden on users. Motivated by this problem, we develop a new automated mechanism(More)
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