267 research outputs found

    KARL: A Knowledge-Assisted Retrieval Language

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    Data classification and storage are tasks typically performed by application specialists. In contrast, information users are primarily non-computer specialists who use information in their decision-making and other activities. Interaction efficiency between such users and the computer is often reduced by machine requirements and resulting user reluctance to use the system. This thesis examines the problems associated with information retrieval for non-computer specialist users, and proposes a method for communicating in restricted English that uses knowledge of the entities involved, relationships between entities, and basic English language syntax and semantics to translate the user requests into formal queries. The proposed method includes an intelligent dictionary, syntax and semantic verifiers, and a formal query generator. In addition, the proposed system has a learning capability that can improve portability and performance. With the increasing demand for efficient human-machine communication, the significance of this thesis becomes apparent. As human resources become more valuable, software systems that will assist in improving the human-machine interface will be needed and research addressing new solutions will be of utmost importance. This thesis presents an initial design and implementation as a foundation for further research and development into the emerging field of natural language database query systems

    Improved Coreference Resolution Using Cognitive Insights

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    Coreference resolution is the task of extracting referential expressions, or mentions, in text and clustering these by the entity or concept they refer to. The sustained research interest in the task reflects the richness of reference expression usage in natural language and the difficulty in encoding insights from linguistic and cognitive theories effectively. In this thesis, we design and implement LIMERIC, a state-of-the-art coreference resolution engine. LIMERIC naturally incorporates both non-local decoding and entity-level modelling to achieve the highly competitive benchmark performance of 64.22% and 59.99% on the CoNLL-2012 benchmark with a simple model and a baseline feature set. As well as strong performance, a key contribution of this work is a reconceptualisation of the coreference task. We draw an analogy between shift-reduce parsing and coreference resolution to develop an algorithm which naturally mimics cognitive models of human discourse processing. In our feature development work, we leverage insights from cognitive theories to improve our modelling. Each contribution achieves statistically significant improvements and sum to gains of 1.65% and 1.66% on the CoNLL-2012 benchmark, yielding performance values of 65.76% and 61.27%. For each novel feature we propose, we contribute an accompanying analysis so as to better understand how cognitive theories apply to real language data. LIMERIC is at once a platform for exploring cognitive insights into coreference and a viable alternative to current systems. We are excited by the promise of incorporating our and further cognitive insights into more complex frameworks since this has the potential to both improve the performance of computational models, as well as our understanding of the mechanisms underpinning human reference resolution

    MULTI-MODAL TASK INSTRUCTIONS TO ROBOTS BY NAIVE USERS

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    This thesis presents a theoretical framework for the design of user-programmable robots. The objective of the work is to investigate multi-modal unconstrained natural instructions given to robots in order to design a learning robot. A corpus-centred approach is used to design an agent that can reason, learn and interact with a human in a natural unconstrained way. The corpus-centred design approach is formalised and developed in detail. It requires the developer to record a human during interaction and analyse the recordings to find instruction primitives. These are then implemented into a robot. The focus of this work has been on how to combine speech and gesture using rules extracted from the analysis of a corpus. A multi-modal integration algorithm is presented, that can use timing and semantics to group, match and unify gesture and language. The algorithm always achieves correct pairings on a corpus and initiates questions to the user in ambiguous cases or missing information. The domain of card games has been investigated, because of its variety of games which are rich in rules and contain sequences. A further focus of the work is on the translation of rule-based instructions. Most multi-modal interfaces to date have only considered sequential instructions. The combination of frame-based reasoning, a knowledge base organised as an ontology and a problem solver engine is used to store these rules. The understanding of rule instructions, which contain conditional and imaginary situations require an agent with complex reasoning capabilities. A test system of the agent implementation is also described. Tests to confirm the implementation by playing back the corpus are presented. Furthermore, deployment test results with the implemented agent and human subjects are presented and discussed. The tests showed that the rate of errors that are due to the sentences not being defined in the grammar does not decrease by an acceptable rate when new grammar is introduced. This was particularly the case for complex verbal rule instructions which have a large variety of being expressed

    Ageing Futures: Towards Cognitively Inclusive Digital Media Products

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    This thesis is situated in a moment when the theory and practice of inclusive design appears to be significantly implicated in the social and economic response to demographic changes in Western Europe by addressing the need to reconnect older people with technology. In light of claims that cognitive ageing results in an increasing disconnection from novel digital media in old age, inclusive design is apparently trapped in a discourse in which digital media products and interfaces are designed as a response to a deterministic decline in abilities. The thesis proceeds from this context to ask what intellectual moves are required within the discourses of inclusive design so that its community of theorists and practitioners can both comprehend and afford the enaction of cognitive experience in old age? Whilst influential design scholarship actively disregards reductionist cognitive explanations of human and technological relationships, it appears that inclusive design still requires an explanation of temporal changes to human cognition in later life. Whilst there is a burgeoning area of design related research dealing with this issue—an area this thesis defines as ‘cognitively inclusive design’—the underlying assumptions and claims supporting this body of research suggests its theorists and practitioners are struggling to move beyond conceptualising older people as passive consumers suffering a deterioration in key cognitive abilities. The thesis argues that, by revisiting the cognitive sciences for alternative explanations for the basis of human cognition, it is possible to relieve this problem by opening up new spaces for designers to critically reflect upon the manner in which older people interact with digital media. In taking a position that design is required to support human cognitive enactment, the thesis develops a new approach to conceptualising temporal changes in human cognition, defined as ‘senescent cognition’. From this new critical lens, the thesis provides an alternative ‘senescentechnic’ explanation of cognitive disconnections between older people and digital media that eschews reductionism and moves beyond a deterministic process of deterioration. In reassessing what ageing cognition means, new strategies for the future of inclusive design are proposed that emphasise the role of creating space for older people to actively explore, reflect upon and enact their own cognitive couplings with technology.Arts and Humanities Research Counci

    Understanding and Representing Natural Language Meaning

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    Coordinated Science Laboratory was formerly known as Control Systems LaboratoryOffice of Naval Research / N00014-75-C-061

    Driving semantics for a limited domain

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