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Observation of new excited ${B} ^0_{s} $ states
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In: Eur.Phys.J.C ; https://hal.archives-ouvertes.fr/hal-03010999 ; Eur.Phys.J.C, 2021, 81 (7), pp.601. ⟨10.1140/epjc/s10052-021-09305-3⟩ (2021)
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Detecting Geospatial Location Descriptions in Natural Language Text ...
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Detecting Geospatial Location Descriptions in Natural Language Text ...
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Reinforcement learning for query-based multi-document extractive summarisation
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Outcomes and experiences of dialectical behaviour therapy for individuals with intellectual disabilities
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Mapping Wildlife Species Distribution With Social Media: Augmenting Text Classification With Species Names (Short Paper)
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Screening of cognitive functions: analysis and development of neuropsychological test instruments
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Observation of $B^0_s\to\bar{D}^0 K^0_S$ and evidence for $B^0_s\to\bar{D}^{*0} K^0_S$ decays
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KneeTex: An ontology-driven system for information extraction from MRI reports
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KneeTex: An ontology-driven system for information extraction from MRI reports
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Evaluating hearing aid handling skills: a systematic and descriptive review
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Impact of citing papers for summarisation of clinical documents
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Semantic and geometric enrichment of 3D geo-spatial models with captioned photos and labelled illustrations
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Semantic and geometric enrichment of 3D geo-spatial models with captioned photos and labelled illustrations
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Auditory-verbal therapy for promoting spoken language development in children with permanent hearing impairments
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Refocusing Intelligence: Keeping Intelligence Relevant Beyond the Global War on Terrorism
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Interpreting Spatial Language in Image Captions
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Abstract:
The map as a tool for accessing data has become very popular in recent years, but a lot of data do not have the necessary spatial meta-data to allow for that. Some data such as photographs however have spatial information in their captions and if this could be extracted, then they could be made available via map-based interfaces. Towards this goal, we introduce a model and spatio-linguistic reasoner for interpreting the spatial information in image captions that is based upon quantitative data about spatial language use acquired directly from people. Spatial language is inherently vague, and both the model and reasoner have been designed to incorporate this vagueness at the quantitative level and not only qualitatively.
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URL: http://oro.open.ac.uk/68765/1/halletal2011.pdf http://oro.open.ac.uk/68765/ https://doi.org/10.1007/s10339-010-0385-5
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