42 resultados para natural user interface


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The semantic web (SW) vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language (NL) and an ontology as input, and returns answers drawn from one or more knowledge bases (KB). AquaLog presents an elegant solution in which different strategies are combined together in a novel way. AquaLog novel ontology-based relation similarity service makes sense of user queries.

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Automatic ontology building is a vital issue in many fields where they are currently built manually. This paper presents a user-centred methodology for ontology construction based on the use of Machine Learning and Natural Language Processing. In our approach, the user selects a corpus of texts and sketches a preliminary ontology (or selects an existing one) for a domain with a preliminary vocabulary associated to the elements in the ontology (lexicalisations). Examples of sentences involving such lexicalisation (e.g. ISA relation) in the corpus are automatically retrieved by the system. Retrieved examples are validated by the user and used by an adaptive Information Extraction system to generate patterns that discover other lexicalisations of the same objects in the ontology, possibly identifying new concepts or relations. New instances are added to the existing ontology or used to tune it. This process is repeated until a satisfactory ontology is obtained. The methodology largely automates the ontology construction process and the output is an ontology with an associated trained leaner to be used for further ontology modifications.

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Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. miniDVMS v1.8 provides a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualisation domain. The advantage of this interface is that the user is directly involved in the data mining process. Principled projection methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), are integrated with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, and user interaction facilities, to provide this integrated visual data mining framework. The software also supports conventional visualisation techniques such as principal component analysis (PCA), Neuroscale, and PhiVis. This user manual gives an overview of the purpose of the software tool, highlights some of the issues to be taken care while creating a new model, and provides information about how to install and use the tool. The user manual does not require the readers to have familiarity with the algorithms it implements. Basic computing skills are enough to operate the software.

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The emergence of pen-based mobile devices such as PDAs and tablet PCs provides a new way to input mathematical expressions to computer by using handwriting which is much more natural and efficient for entering mathematics. This paper proposes a web-based handwriting mathematics system, called WebMath, for supporting mathematical problem solving. The proposed WebMath system is based on client-server architecture. It comprises four major components: a standard web server, handwriting mathematical expression editor, computation engine and web browser with Ajax-based communicator. The handwriting mathematical expression editor adopts a progressive recognition approach for dynamic recognition of handwritten mathematical expressions. The computation engine supports mathematical functions such as algebraic simplification and factorization, and integration and differentiation. The web browser provides a user-friendly interface for accessing the system using advanced Ajax-based communication. In this paper, we describe the different components of the WebMath system and its performance analysis.

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This paper aims to identify the communication goal(s) of a user's information-seeking query out of a finite set of within-domain goals in natural language queries. It proposes using Tree-Augmented Naive Bayes networks (TANs) for goal detection. The problem is formulated as N binary decisions, and each is performed by a TAN. Comparative study has been carried out to compare the performance with Naive Bayes, fully-connected TANs, and multi-layer neural networks. Experimental results show that TANs consistently give better results when tested on the ATIS and DARPA Communicator corpora.

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This paper presents the design and results of a task-based user study, based on Information Foraging Theory, on a novel user interaction framework - uInteract - for content-based image retrieval (CBIR). The framework includes a four-factor user interaction model and an interactive interface. The user study involves three focused evaluations, 12 simulated real life search tasks with different complexity levels, 12 comparative systems and 50 subjects. Information Foraging Theory is applied to the user study design and the quantitative data analysis. The systematic findings have not only shown how effective and easy to use the uInteract framework is, but also illustrate the value of Information Foraging Theory for interpreting user interaction with CBIR. © 2011 Springer-Verlag Berlin Heidelberg.

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This paper presents an interactive content-based image retrieval framework—uInteract, for delivering a novel four-factor user interaction model visually. The four-factor user interaction model is an interactive relevance feedback mechanism that we proposed, aiming to improve the interaction between users and the CBIR system and in turn users overall search experience. In this paper, we present how the framework is developed to deliver the four-factor user interaction model, and how the visual interface is designed to support user interaction activities. From our preliminary user evaluation result on the ease of use and usefulness of the proposed framework, we have learnt what the users like about the framework and the aspects we could improve in future studies. Whilst the framework is developed for our research purposes, we believe the functionalities could be adapted to any content-based image search framework.

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This paper describes the work undertaken in the Scholarly Ontologies Project. The aim of the project has been to develop a computational approach to support scholarly sensemaking, through interpretation and argumentation, enabling researchers to make claims: to describe and debate their view of a document's key contributions and relationships to the literature. The project has investigated the technicalities and practicalities of capturing conceptual relations, within and between conventional documents in terms of abstract ontological structures. In this way, we have developed a new kind of index to distributed digital library systems. This paper reports a case study undertaken to test the sensemaking tools developed by the Scholarly Ontologies project. The tools used were ClaiMapper, which allows the user to sketch argument maps of individual papers and their connections, ClaiMaker, a server on which such models can be stored and saved, which provides interpretative services to assist the querying of argument maps across multiple papers and ClaimFinder, a novice interface to the search services in ClaiMaker.

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Term dependence is a natural consequence of language use. Its successful representation has been a long standing goal for Information Retrieval research. We present a methodology for the construction of a concept hierarchy that takes into account the three basic dimensions of term dependence. We also introduce a document evaluation function that allows the use of the concept hierarchy as a user profile for Information Filtering. Initial experimental results indicate that this is a promising approach for incorporating term dependence in the way documents are filtered.

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Over the past two years there have been several large-scale disasters (Haitian earthquake, Australian floods, UK riots, and the Japanese earthquake) that have seen wide use of social media for disaster response, often in innovative ways. This paper provides an analysis of the ways in which social media has been used in public-to-public communication and public-to-government organisation communication. It discusses four ways in which disaster response has been changed by social media: 1. Social media appears to be displacing the traditional media as a means of communication with the public during a crisis. In particular social media influences the way traditional media communication is received and distributed. 2. We propose that user-generated content may provide a new source of information for emergency management agencies during a disaster, but there is uncertainty with regards to the reliability and usefulness of this information. 3. There are also indications that social media provides a means for the public to self-organise in ways that were not previously possible. However, the type and usefulness of self-organisation sometimes works against efforts to mitigate the outcome of the disaster. 4. Social media seems to influence information flow during a disaster. In the past most information flowed in a single direction from government organisation to public, but social media negates this model. The public can diffuse information with ease, but also expect interaction with Government Organisations rather than a simple one-way information flow. These changes have implications for the way government organisations communicate with the public during a disaster. The predominant model for explaining this form of communication, the Crisis and Emergency Risk Communication (CERC), was developed in 2005 before social media achieved widespread popularity. We will present a modified form of the CERC model that integrates social media into the disaster communication cycle, and addresses the ways in which social media has changed communication between the public and government organisations during disasters.

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Over the past two years there have been several large-scale disasters (Haitian earthquake, Australian floods, UK riots, and the Japanese earthquake) that have seen wide use of social media for disaster response, often in innovative ways. This paper provides an analysis of the ways in which social media has been used in public-to-public communication and public-to-government organisation communication. It discusses four ways in which disaster response has been changed by social media: 1. Social media appears to be displacing the traditional media as a means of communication with the public during a crisis. In particular social media influences the way traditional media communication is received and distributed. 2. We propose that user-generated content may provide a new source of information for emergency management agencies during a disaster, but there is uncertainty with regards to the reliability and usefulness of this information. 3. There are also indications that social media provides a means for the public to self-organise in ways that were not previously possible. However, the type and usefulness of self-organisation sometimes works against efforts to mitigate the outcome of the disaster. 4. Social media seems to influence information flow during a disaster. In the past most information flowed in a single direction from government organisation to public, but social media negates this model. The public can diffuse information with ease, but also expect interaction with Government Organisations rather than a simple one-way information flow. These changes have implications for the way government organisations communicate with the public during a disaster. The predominant model for explaining this form of communication, the Crisis and Emergency Risk Communication (CERC), was developed in 2005 before social media achieved widespread popularity. We will present a modified form of the CERC model that integrates social media into the disaster communication cycle, and addresses the ways in which social media has changed communication between the public and government organisations during disasters.

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Objectives: To develop a decision support system (DSS), myGRaCE, that integrates service user (SU) and practitioner expertise about mental health and associated risks of suicide, self-harm, harm to others, self-neglect, and vulnerability. The intention is to help SUs assess and manage their own mental health collaboratively with practitioners. Methods: An iterative process involving interviews, focus groups, and agile software development with 115 SUs, to elicit and implement myGRaCE requirements. Results: Findings highlight shared understanding of mental health risk between SUs and practitioners that can be integrated within a single model. However, important differences were revealed in SUs' preferred process of assessing risks and safety, which are reflected in the distinctive interface, navigation, tool functionality and language developed for myGRaCE. A challenge was how to provide flexible access without overwhelming and confusing users. Conclusion: The methods show that practitioner expertise can be reformulated in a format that simultaneously captures SU expertise, to provide a tool highly valued by SUs. A stepped process adds necessary structure to the assessment, each step with its own feedback and guidance. Practice Implications: The GRiST web-based DSS (www.egrist.org) links and integrates myGRaCE self-assessments with GRiST practitioner assessments for supporting collaborative and self-managed healthcare.