947 resultados para semantic annotation
Resumo:
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.
Resumo:
The realization of the Semantic Web is constrained by a knowledge acquisition bottleneck, i.e. the problem of how to add RDF mark-up to the millions of ordinary web pages that already exist. Information Extraction (IE) has been proposed as a solution to the annotation bottleneck. In the task based evaluation reported here, we compared the performance of users without access to annotation, users working with annotations which had been produced from manually constructed knowledge bases, and users working with annotations augmented using IE. We looked at retrieval performance, overlap between retrieved items and the two sets of annotations, and usage of annotation options. Automatically generated annotations were found to add value to the browsing experience in the scenario investigated. Copyright 2005 ACM.
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The usability of research papers on the Web would be enhanced by a system that explicitly modelled the rhetorical relations between claims in related papers. We describe ClaiMaker, a system for modelling readers’ interpretations of the core content of papers. ClaiMaker provides tools to build a Semantic Web representation of the claims in research papers using an ontology of relations. We demonstrate how the system can be used to make inter-document queries.
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This paper identifies gaps in standardization of agri-food logistics. Out of the European FP7 SmartAgriFood project a framework for classifying existing standards within the agri-food supply chain is introduced. Furthermore the characteristics to which a semantic standard should adhere are investigated. The standards classified as semantic out of the framework are assessed along these properties. The resulting conclusion is that the standards that are already present in the chain are more focused on syntax and lack semantic properties.
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Disasters cause widespread harm and disrupt the normal functioning of society, and effective management requires the participation and cooperation of many actors. While advances in information and networking technology have made transmission of data easier than it ever has been before, communication and coordination of activities between actors remain exceptionally difficult. This paper employs semantic web technology and Linked Data principles to create a network of intercommunicating and inter-dependent on-line sites for managing resources. Each site publishes available resources openly and a lightweight opendata protocol is used to request and respond to requests for resources between sites in the network.
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The expansion of the Internet has made the task of searching a crucial one. Internet users, however, have to make a great effort in order to formulate a search query that returns the required results. Many methods have been devised to assist in this task by helping the users modify their query to give better results. In this paper we propose an interactive method for query expansion. It is based on the observation that documents are often found to contain terms with high information content, which can summarise their subject matter. We present experimental results, which demonstrate that our approach significantly shortens the time required in order to accomplish a certain task by performing web searches.
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Increasingly, people's digital identities are attached to, and expressed through, their mobile devices. At the same time digital sensors pervade smart environments in which people are immersed. This paper explores different perspectives in which users' modelling features can be expressed through the information obtained by their attached personal sensors. We introduce the PreSense Ontology, which is designed to assign meaning to sensors' observations in terms of user modelling features. We believe that the Sensing Presence ( PreSense ) Ontology is a first step toward the integration of user modelling and "smart environments". In order to motivate our work we present a scenario and demonstrate how the ontology could be applied in order to enable context-sensitive services. © 2012 Springer-Verlag.
Resumo:
In order to address problems of information overload in digital imagery task domains we have developed an interactive approach to the capture and reuse of image context information. Our framework models different aspects of the relationship between images and domain tasks they support by monitoring the interactive manipulation and annotation of task-relevant imagery. The approach allows us to gauge a measure of a user's intentions as they complete goal-directed image tasks. As users analyze retrieved imagery their interactions are captured and an expert task context is dynamically constructed. This human expertise, proficiency, and knowledge can then be leveraged to support other users in carrying out similar domain tasks. We have applied our techniques to two multimedia retrieval applications for two different image domains, namely the geo-spatial and medical imagery domains. © Springer-Verlag Berlin Heidelberg 2007.
Resumo:
G protein-coupled receptors (GPCR) are amongst the best studied and most functionally diverse types of cell-surface protein. The importance of GPCRs as mediates or cell function and organismal developmental underlies their involvement in key physiological roles and their prominence as targets for pharmacological therapeutics. In this review, we highlight the requirement for integrated protocols which underline the different perspectives offered by different sequence analysis methods. BLAST and FastA offer broad brush strokes. Motif-based search methods add the fine detail. Structural modelling offers another perspective which allows us to elucidate the physicochemical properties that underlie ligand binding. Together, these different views provide a more informative and a more detailed picture of GPCR structure and function. Many GPCRs remain orphan receptors with no identified ligand, yet as computer-driven functional genomics starts to elaborate their functions, a new understanding of their roles in cell and developmental biology will follow.
Resumo:
The aim of our work is to present solutions and a methodical support for automated techniques and procedures in domain engineering, in particular for variability modeling. Our approach is based upon Semantic Modeling concepts, for which semantic description, representation patterns and inference mechanisms are defined. Thus, model-driven techniques enriched with semantics will allow flexibility and variability in representation means, reasoning power and the required analysis depth for the identification, interpretation and adaptation of artifact properties and qualities.
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Possibilities for using semantic parsing to estimate the correspondence of text materials to teaching aims, correspondence of test task to theoretical materials and other problems arising during the distance course designing and educational process itself in e-learning environments.
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Dance videos are interesting and semantics-intensive. At the same time, they are the complex type of videos compared to all other types such as sports, news and movie videos. In fact, dance video is the one which is less explored by the researchers across the globe. Dance videos exhibit rich semantics such as macro features and micro features and can be classified into several types. Hence, the conceptual modeling of the expressive semantics of the dance videos is very crucial and complex. This paper presents a generic Dance Video Semantics Model (DVSM) in order to represent the semantics of the dance videos at different granularity levels, identified by the components of the accompanying song. This model incorporates both syntactic and semantic features of the videos and introduces a new entity type called, Agent, to specify the micro features of the dance videos. The instantiations of the model are expressed as graphs. The model is implemented as a tool using J2SE and JMF to annotate the macro and micro features of the dance videos. Finally examples and evaluation results are provided to depict the effectiveness of the proposed dance video model.
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False friends are pairs of words in two languages that are perceived as similar but have different meanings. We present an improved algorithm for acquiring false friends from sentence-level aligned parallel corpus based on statistical observations of words occurrences and co-occurrences in the parallel sentences. The results are compared with an entirely semantic measure for cross-lingual similarity between words based on using the Web as a corpus through analyzing the words’ local contexts extracted from the text snippets returned by searching in Google. The statistical and semantic measures are further combined into an improved algorithm for identification of false friends that achieves almost twice better results than previously known algorithms. The evaluation is performed for identifying cognates between Bulgarian and Russian but the proposed methods could be adopted for other language pairs for which parallel corpora and bilingual glossaries are available.
Resumo:
Electronic publishing exploits numerous possibilities to present or exchange information and to communicate via most current media like the Internet. By utilizing modern Web technologies like Web Services, loosely coupled services, and peer-to-peer networks we describe the integration of an intelligent business news presentation and distribution network. Employing semantics technologies enables the coupling of multinational and multilingual business news data on a scalable international level and thus introduce a service quality that is not achieved by alternative technologies in the news distribution area so far. Architecturally, we identified the loose coupling of existing services as the most feasible way to address multinational and multilingual news presentation and distribution networks. Furthermore we semantically enrich multinational news contents by relating them using AI techniques like the Vector Space Model. Summarizing our experiences we describe the technical integration of semantics and communication technologies in order to create a modern international news network.
Resumo:
This article presents the principal results of the doctoral thesis “Semantic-oriented Architecture and Models for Personalized and Adaptive Access to the Knowledge in Multimedia Digital Library” by Desislava Ivanova Paneva-Marinova (Institute of Mathematics and Informatics), successfully defended before the Specialised Academic Council for Informatics and Mathematical Modelling on 27 October, 2008.