Incremental Update Summarization: Adaptive Sentence Selection based on Prevalence and Novelty

The automatic summarization of long-running events from news steams is a challenging problem. A long-running event can contain hundreds of unique ‘nuggets’ of information to summarize, spread-out over its lifetime. Meanwhile, informatio reported about it can rapidly become outdated and is often highly redundant. Incremental update summarization (IUS) aims to select sentences from news streams to issue as updates to the user, summarising that event over time. The updates issued should cover all of the key nuggets concisely and before...

A Study of Personalised Medical Literature Search

Medical search engines are used everyday by both medical practitioners and the public to find the latest medical literature and guidance regarding conditions and treatments. Importantly, the information needs that drive medical search can vary between users for the same query, as clinicians search for content specific to their own area of expertise, while the public search about topics of interest to them. However, prior research into personalised search has so far focused on the Web search domain, and it is not clear whether personalised...

Comparing Algorithms for Microblog Summarisation

Event detection and tracking using social media and user-generated content has received a lot of attention from the research community in recent years, since such sources can purportedly provide up-to-date information about events as they evolve, e.g. earthquakes. Concisely reporting (summarising) events for users/emergency services using information obtained from social media sources like Twitter is not a solved problem. Current systems either directly apply, or build upon, classical summarisation approaches previously shown to be...