896 resultados para semantic cache


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Previous studies have shown that users’ cognitive styles play an important role during Web searching. However, only limited studies have showed the relationship between cognitive styles and Web search behavior. Most importantly, it is not clear which components of Web search behavior are influenced by cognitive styles. This paper examines the relationships between users’ cognitive styles and their Web searching and develops a model that portrays the relationship. The study uses qualitative and quantitative analyses to inform the study results based on data gathered from 50 participants. A questionnaire was utilised to collect participants’ demographic information, and Riding’s (1991) Cognitive Style Analysis (CSA) test to assess their cognitive styles. Results show that users’ cognitive styles influenced their information searching strategies, query reformulation behaviour, Web navigational styles and information processing approaches. The user model developed in this study depicts the fundamental relationships between users’ Web search behavior and their cognitive styles. Modeling Web search behavior with a greater understanding of user’s cognitive styles can help information science researchers and information systems designers to bridge the semantic gap between the user and the systems. Implications of the research for theory and practice, and future work are discussed.

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With the widespread of social media websites in the internet, and the huge number of users participating and generating infinite number of contents in these websites, the need for personalisation increases dramatically to become a necessity. One of the major issues in personalisation is building users’ profiles, which depend on many elements; such as the used data, the application domain they aim to serve, the representation method and the construction methodology. Recently, this area of research has been a focus for many researchers, and hence, the proposed methods are increasing very quickly. This survey aims to discuss the available user modelling techniques for social media websites, and to highlight the weakness and strength of these methods and to provide a vision for future work in user modelling in social media websites.

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Robust descriptor matching across varying lighting conditions is important for vision-based robotics. We present a novel strategy for quantifying the lighting variance of descriptors. The strategy works by utilising recovered low dimensional mappings from Isomap and our measure of the lighting variance of each of these mappings. The resultant metric allows different descriptors to be compared given a dataset and a set of keypoints. We demonstrate that the SIFT descriptor typically has lower lighting variance than other descriptors, although the result depends on semantic class and lighting conditions.

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Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, which has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering is rarely known. Patterns are always thought to be more representative than single terms for representing documents. In this paper, a novel information filtering model, Pattern-based Topic Model(PBTM) , is proposed to represent the text documents not only using the topic distributions at general level but also using semantic pattern representations at detailed specific level, both of which contribute to the accurate document representation and document relevance ranking. Extensive experiments are conducted to evaluate the effectiveness of PBTM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model achieves outstanding performance.

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INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2013 evaluation campaign, which consisted of four activities addressing three themes: searching professional and user generated data (Social Book Search track); searching structured or semantic data (Linked Data track); and focused retrieval (Snippet Retrieval and Tweet Contextualization tracks). INEX 2013 was an exciting year for INEX in which we consolidated the collaboration with (other activities in) CLEF and for the second time ran our workshop as part of the CLEF labs in order to facilitate knowledge transfer between the evaluation forums. This paper gives an overview of all the INEX 2013 tracks, their aims and task, the built test-collections, and gives an initial analysis of the results

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This paper uses innovative content analysis techniques to map how the death of Oscar Pistorius' girlfriend, Reeva Steenkamp, was framed on Twitter conversations. Around 1.5 million posts from a two-week timeframe are analyzed with a combination of syntactic and semantic methods. This analysis is grounded in the frame analysis perspective and is different than sentiment analysis. Instead of looking for explicit evaluations, such as “he is guilty” or “he is innocent”, we showcase through the results how opinions can be identified by complex articulations of more implicit symbolic devices such as examples and metaphors repeatedly mentioned. Different frames are adopted by users as more information about the case is revealed: from a more episodic one, highly used in the very beginning, to more systemic approaches, highlighting the association of the event with urban violence, gun control issues, and violence against women. A detailed timeline of the discussions is provided.

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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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Here, we investigate the genetic basis of human memory in healthy individuals and the potential role of two polymorphisms, previously implicated in memory function. We have explored aspects of retrospective and prospective memory including semantic, short term, working and long-term memory in conjunction with brain derived neurotrophic factor (BDNF) and tumor necrosis factor-alpha (TNF-alpha). The memory scores for healthy individuals in the population were obtained for each memory type and the population was genotyped via restriction fragment length polymorphism for the BDNF rs6265 (Val66Met) SNP and via pyrosequencing for the TNF-alpha rs113325588 SNP. Using univariate ANOVA, a significant association of the BDNF polymorphism with visual and spatial memory retention and a significant association of the TNF-alpha polymorphism was observed with spatial memory retention. In addition, a significant interactive effect between BDNF and TNF-alpha polymorphisms was observed in spatial memory retention. In practice visual memory involves spatial information and the two memory systems work together, however our data demonstrate that individuals with the Val/Val BDNF genotype have poorer visual memory but higher spatial memory retention, indicating a level of interaction between TNF-alpha and BDNF in spatial memory retention. This is the first study to use genetic analysis to determine the interaction between BDNF and TNF-alpha in relation to memory in normal adults and provides important information regarding the effect of genetic determinants and gene interactions on human memory.

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The concept of affordance has different interpretations in the field of Human-Computer Interaction (HCI). However, its treatment has been merely as a one-to-one relationship between a user and a technology. We believe that a broader view of affordances is needed which encompasses social and cultural aspects of our everyday life. We propose an interaction-centered view of affordance that can be useful for developing better understandings of designed artefacts. An interaction-centered view of affordance suggests that affordance is an interpretative relationship between users and the technology that emerges during the users' interaction with the technology in the lived environments. We distinguish two broad classes of affordances: affordance in Information and affordance in Articulation. Affordance in information refers to users' understanding of a technology based on their semantic and syntactic interpretation; and affordance in articulation refers to users' interpretations about the use of the technology. We also argue that the notion of affordance should be treated at two levels: at the 'artefact level' and at the 'practice level'. Consequently, we provide two examples to demonstrate our arguments.

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True creativity sits in stark contrast with global trends to standardise education systems. It is, though, an attractive semantic and conjures up all sorts of positives. However none of the positive potentials of the creativity push are likely to materialise while process-oriented bureaucratic understandings of creativity dominate curriculum policy and development. Creativity requires pedagogy to forego substantial levels of control. It also requires ethical content because “creative” is an empty epithet, applying equally to the creation of beautiful music as it does to the creation of a nuclear weapon. In responding to Kapitzke and Hay, this chapter outlines the stark contradictions embedded in the creativity push.

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More and more traditional manufacturing companies form or join inter-organizational networks to bundle their physical products with related services to offer superior value propositions to their customers. Some of these product-related services can be digitized completely and thus fully delivered electronically. Other services require the physical integration of external factors, but can still be coordinated electronically. In both cases companies and consumers face the problem of discovering appropriate product-related service offerings in the network or market. Based on ideas from the web service discovery discipline we propose a meet-in-the-middle approach between heavy-weight semantic technologies and simple boolean search to address this issue. Our approach is able to consider semantic relations in service descriptions and queries and thus delivers better results than syntax-based search. However – unlike most semantic approaches – it does not require the use of any formal language for semantic markup and thus requires less resources and skills for both service providers and consumers. To fully realize the potentials of the proposed approach a domain ontology is needed. In this research-in-progress paper we construct such an ontology for the domain of product-service bundles through analysis and synthesis of related work on service description. This will serve as an anchor for future research to iteratively improve and evaluate the ontology through collaborative design efforts and practical application.

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We identify relation completion (RC) as one recurring problem that is central to the success of novel big data applications such as Entity Reconstruction and Data Enrichment. Given a semantic relation, RC attempts at linking entity pairs between two entity lists under the relation. To accomplish the RC goals, we propose to formulate search queries for each query entity α based on some auxiliary information, so that to detect its target entity β from the set of retrieved documents. For instance, a pattern-based method (PaRE) uses extracted patterns as the auxiliary information in formulating search queries. However, high-quality patterns may decrease the probability of finding suitable target entities. As an alternative, we propose CoRE method that uses context terms learned surrounding the expression of a relation as the auxiliary information in formulating queries. The experimental results based on several real-world web data collections demonstrate that CoRE reaches a much higher accuracy than PaRE for the purpose of RC.

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Health care systems are highly dynamic not just due to developments and innovations in diagnosis and treatments, but also by virtue of emerging management techniques supported by modern information and communication technology. A multitude of stakeholders such as patients, nurses, general practitioners or social carers can be integrated by modeling complex interactions necessary for managing the provision and consumption of health care services. Furthermore, it is the availability of Service-oriented Architecture (SOA) that supports those integration efforts by enabling the flexible and reusable composition of autonomous, loosely-coupled and web-enabled software components. However, there is still the gap between SOA and predominantly business-oriented perspectives (e.g. business process models). The alignment of both views is crucial not just for the guided development of SOA but also for the sustainable evolution of holistic enterprise architectures. In this paper, we combine the Semantic Object Model (SOM) and the Business Process Modelling Notation (BPMN) towards a model-driven approach to service engineering. By addressing a business system in Home Telecare and deriving a business process model, which can eventually be controlled and executed by machines; in particular by composed web services, the full potential of a process-centric SOA is exploited.

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This thesis investigates the fusion of 3D visual information with 2D image cues to provide 3D semantic maps of large-scale environments in which a robot traverses for robotic applications. A major theme of this thesis was to exploit the availability of 3D information acquired from robot sensors to improve upon 2D object classification alone. The proposed methods have been evaluated on several indoor and outdoor datasets collected from mobile robotic platforms including a quadcopter and ground vehicle covering several kilometres of urban roads.

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At a time when theatre practitioners and companies are concerned with dwindling audience numbers, funding and interest (so what’s new?), what this paper discusses is less about theatre ‘changing direction’ and more about ‘changing theatre Direction’. A subtle semantic shift perhaps but one which has proven enormously useful over 25 years as a professional creator, director, performer, designer and teacher for stage, screen – and other contexts. Applying theatrical skills to apparently unrelated contexts is not new, however it bears re-examining. My own experience as a ‘directorial specialist’ in mime and movement confirms the fundamental theatricality in all human communication – whether stage, screen, auditorium or meeting room – I would argue that there is no professional context completely devoid of some measure of ‘performance’. And if you’re going to do performance, however minutely, subtly and in whatever context, at least make it the best performance you can by ‘directing it’. This paper examines the adaptation of theatre direction to other contexts and discusses:- • which other contexts • directing non-performers • what theatre direction provides