Full Paper: Ontology-Based Dialogue System for Domain-Specific Knowledge Acquisition

Building task-oriented dialogue systems for solving specific tasks within companies represents a challenging research objective especially when the specific expertise of the company is not yet machine-readable formalized. Aiming to collect the specific knowledge in a company-scope knowledge graph, we design the architecture of a dialog system integrating the natural language processing modules with the specific concepts described in the domain ontology and the com- pany’s graph of instances. The described system helps growing the knowledge graph with the specific company data, while also providing the NLP building blocks for a future dialog system specifically tuned for the requirements of the target company processes

Should I stay or should I go?: how healthcare professionals close encounters with people with dementia in the acute hospital setting

Around a quarter of hospital beds in the UK are occupied by patients living with dementia (PWD), and communication impairments are common across all types of dementia, often exacerbated by the hospital environment. Unsurprisingly, healthcare professionals (HCPs) report particular challenges in caring for this patient group, whilst trying to recognise and value their personhood as per the underpinning ethos of person-centred care. However, whilst there is a growing body of research that underlines the importance of communication in dementia care, there is far less that actually examines this communication in real time interaction. Suggestions and pointers for good communication do exist, but these do not tend to be empirically derived, and sometimes conflict with empirical findings. This paper focuses on a specific area of interaction which has previously received very little attention: the way in which healthcare encounters are ended or closed. There is potentially a conflict between a pressure to manage a patient as efficiently as possible, and endeavouring to ensure person -centred care and deal with communication difficulties arising from dementia. Using conversation analysis, we examined forty-one video recordings of HCP/PWD interactions collected from an acute inpatient ward. We identify three phenomena around which there were recurring troubles in our dataset: ‘open-ended pre-closings’, ‘mixed messages’ and ‘non specifics and indeterminate terms’. We conclude that moves towards closing an encounter that appear intuitive to HCPs as competent interactants, and that may represent best practice in other healthcare settings, may in fact serve to confuse a PWD and create difficulties with closings. Our findings underline the importance of examining best practice guidance as it is actually talked into being, using approaches which can unpack the interactional detail involved. They also emphasise the importance of context in the analysis of healthcare delivery, to avoid a ‘one size fits all’ approach

TV News Story Segmentation Based on Semantic Coherence and Content Similarity

In this paper, we introduce and evaluate two novel approaches, one using video stream and the other using close-caption text stream, for segmenting TV news into stories. The segmentation of the video stream into stories is achieved by detecting anchor person shots and the text stream is segmented into stories using a Latent Dirichlet Allocation (LDA) based approach. The benefit of the proposed LDA based approach is that along with the story segmentation it also provides the topic distribution associated with each segment. We evaluated our techniques on the TRECVid 2003 benchmark database and found that though the individual systems give comparable results, a combination of the outputs of the two systems gives a significant improvement over the performance of the individual systems

New Square Dance Vol. 26, No. 3 (Mar. 1971)

Monthly square dance magazine that began publication in 1945

Suffolk Journal, Vol. 60, No. 23, 4/25/2001

https://dc.suffolk.edu/journal/1377/thumbnail.jp