956 resultados para WORD


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Many existing information retrieval models do not explicitly take into account in- formation about word associations. Our approach makes use of rst and second order relationships found in natural language, known as syntagmatic and paradigmatic associ- ations, respectively. This is achieved by using a formal model of word meaning within the query expansion process. On ad hoc retrieval, our approach achieves statistically sig- ni cant improvements in MAP (0.158) and P@20 (0.396) over our baseline model. The ERR@20 and nDCG@20 of our system was 0.249 and 0.192 respectively. Our results and discussion suggest that information about both syntagamtic and paradigmatic associa- tions can assist with improving retrieval eectiveness on ad hoc retrieval.

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The aim of this paper is to provide a comparison of various algorithms and parameters to build reduced semantic spaces. The effect of dimension reduction, the stability of the representation and the effect of word order are examined in the context of the five algorithms bearing on semantic vectors: Random projection (RP), singular value decom- position (SVD), non-negative matrix factorization (NMF), permutations and holographic reduced representations (HRR). The quality of semantic representation was tested by means of synonym finding task using the TOEFL test on the TASA corpus. Dimension reduction was found to improve the quality of semantic representation but it is hard to find the optimal parameter settings. Even though dimension reduction by RP was found to be more generally applicable than SVD, the semantic vectors produced by RP are somewhat unstable. The effect of encoding word order into the semantic vector representation via HRR did not lead to any increase in scores over vectors constructed from word co-occurrence in context information. In this regard, very small context windows resulted in better semantic vectors for the TOEFL test.

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Many existing information retrieval models do not explicitly take into account in- formation about word associations. Our approach makes use of rst and second order relationships found in natural language, known as syntagmatic and paradigmatic associ- ations, respectively. This is achieved by using a formal model of word meaning within the query expansion process. On ad hoc retrieval, our approach achieves statistically sig- ni cant improvements in MAP (0.158) and P@20 (0.396) over our baseline model. The ERR@20 and nDCG@20 of our system was 0.249 and 0.192 respectively. Our results and discussion suggest that information about both syntagamtic and paradigmatic associa- tions can assist with improving retrieval eectiveness on ad hoc retrieval.

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Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. Previous research assumed a quantum-like model in which the semantic network was modelled as entangled qubits, however the level of activation was clearly being over-estimated. This paper explores three variations of this model, each of which are distinguished by a scaling factor designed to compensate the overestimation.

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This project was a step forward in developing and evaluating a novel, mathematical model that can deduce the meaning of words based on their use in language. This model can be applied to a wide range of natural language applications, including the information seeking process most of us undertake on a daily basis.

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In this paper we will outline a workshop that we conceived, developed, facilitated and evaluated especially for Aboriginal and Torres Strait Islander women. The Tiddas Writin’ Up Workshop specifically addressed the academic writing needs of Aboriginal and Torres Strait Islander women working in universities, institutes and TAFE colleges. We demonstrate how we can make the written word part of our toolbox for success.

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This study explored the creation, dissemination and exchange of electronic word of mouth, in the form of product reviews and ratings of digital technology products. Based on 43 in-depth interviews and 500 responses to an online survey, it reveals a new communication model describing consumers' info-active and info-passive information search styles. The study delivers an in-depth understanding of consumers' attitudes towards current advertising tools and user-generated content, and points to new marketing techniques emerging in the online environment.

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The article discusses the importance that learning to live sustainably in order to provide healthy and fulfilling lives for future generations. The things that need to be done differently and the innovative partnerships that are required are highlighted.

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Complex numbers are a fundamental aspect of the mathematical formalism of quantum physics. Quantum-like models developed outside physics often overlooked the role of complex numbers. Specifically, previous models in Information Retrieval (IR) ignored complex numbers. We argue that to advance the use of quantum models of IR, one has to lift the constraint of real-valued representations of the information space, and package more information within the representation by means of complex numbers. As a first attempt, we propose a complex-valued representation for IR, which explicitly uses complex valued Hilbert spaces, and thus where terms, documents and queries are represented as complex-valued vectors. The proposal consists of integrating distributional semantics evidence within the real component of a term vector; whereas, ontological information is encoded in the imaginary component. Our proposal has the merit of lifting the role of complex numbers from a computational byproduct of the model to the very mathematical texture that unifies different levels of semantic information. An empirical instantiation of our proposal is tested in the TREC Medical Record task of retrieving cohorts for clinical studies.

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This text elaborates on the city as cultural construct and representation and Lisbocópio, the installation by Pancho Guedes and Ricardo Jacinto in the context of the Official Representation of Portugal at the 10. Mostra Internazionale di Architettura-La Biennale di Venezia.

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This paper explores the literature and analyses the different uses and understandings of the word “design” in Portuguese colonised countries, using Brazil as the main example. It investigates the relationship between the linguistic existence of terms to define and describe “design” as an activity and field, and the roles and perceptions of Design by the general society. It also addresses the effects that the lack of a proper translation causes on the local community from a cultural point of view. The current perception of Design in Portuguese colonies is associated to two main aspects: linguistic and historical. Both of them differentiate the countries taken into consideration from other countries that have a different background. The changes associated to the meaning of “design” throughout the years, caused a great impact on the perceptions that people have about Design. On the other hand, the development of Design has also influenced the changes on the meaning of the term, as a result of the legacy from the colonisation period and also as a characteristic of the Portuguese language. Design has developed and reached a level of excellence in Portuguese colonised countries that competes with the most traditional Design cultures in the world. However, this level of Design is enmeshed into an elite belonging to universities and specialised markets, therefore Design is not democratised. The ultimate aim of this study is to promote discussions on how to make the discourse surrounding this area more accessible to people from non-English speaking countries that do not have the word “design” in their local language.

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Increased longevity and the need to fund living and care expenses across late old age, greater proportions of blended and culturally diverse families and concerns about the increasing possibility of contestation of wills highlight the importance of understanding current will making practices and intentions. Yet, there is no current national data on the prevalence of wills, intended beneficiaries, the principles and practices surrounding will making and the patterns and outcomes of contestation. This project sought to address this gap. This report summarises the results of a four year program of research examining will making and will contestation in Australia. The project was funded by the Australian Research Council (LP10200891) in conjunction with seven Public Trustee Organisations across Australia. The interdisciplinary research team with expertise in social science, social work, law and social policy are from The University of Queensland, Queensland University of Technology and Victoria University. The project comprised five research studies: a national prevalence survey, a judicial case review, a review of Public Trustee files, an online survey of will drafters and in-depth interviews with key groups of interest. The report outlines key findings. On the basis of the evidence provided recommendations are presented to support the achievement of these policy goals: increasing will making in the Australian population, ensuring that the wills of those Australians who have taken this step reflect their current situation and intentions, and reducing will contestation.

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This article presents and evaluates a model to automatically derive word association networks from text corpora. Two aspects were evaluated: To what degree can corpus-based word association networks (CANs) approximate human word association networks with respect to (1) their ability to quantitatively predict word associations and (2) their structural network characteristics. Word association networks are the basis of the human mental lexicon. However, extracting such networks from human subjects is laborious, time consuming and thus necessarily limited in relation to the breadth of human vocabulary. Automatic derivation of word associations from text corpora would address these limitations. In both evaluations corpus-based processing provided vector representations for words. These representations were then employed to derive CANs using two measures: (1) the well known cosine metric, which is a symmetric measure, and (2) a new asymmetric measure computed from orthogonal vector projections. For both evaluations, the full set of 4068 free association networks (FANs) from the University of South Florida word association norms were used as baseline human data. Two corpus based models were benchmarked for comparison: a latent topic model and latent semantic analysis (LSA). We observed that CANs constructed using the asymmetric measure were slightly less effective than the topic model in quantitatively predicting free associates, and slightly better than LSA. The structural networks analysis revealed that CANs do approximate the FANs to an encouraging degree.