Reducing the "Information Gap" Between Synchronous and Asynchronous Co-operative Design Phases

This paper aims to describe a particular role of annotations as co-operative artefacts in engineering design. In co-operative processes, where achieving a shared understanding between the participants from different domains is crucial, sharing the decisions and argumentations which lead to a solution is as important as sharing the solution itself. In our case study, we describe what we call an "information gap" between the asynchronous phase, when individual decisions are made, and the design review, when the solution is evaluated, and collective thinking influences the decisions. Then, within a conceptual design scenario, we show how semantic annotations can create a shared environment to help to reduce this gap, where all actors are able to elicit domain-specific constraints and engage discussions on design solution during the asynchronous phase.semantic annotation; engineering design; design communication; collaborative tool

Late Semantic Fusion Approach for the Retrieval of Multimedia Data

In Multimedia information retrieval late semantic fusion is used to combine textual pre-filtering with an image re-ranking. Three steps are used for retrieval processes. Visual and textual techniques are combined to help the developed Multimedia Information Retrieval System to minimize the semantic gap for given query. In the paper, different late semantic fusion approaches i.e. Product, Enrich, MaxMerge and FilterN are used and for experiments publicly available ImageCLEF Wikipedia Collection is used. DOI: 10.17762/ijritcc2321-8169.150610

Multimedia Retrieval: Survey Of Methods And Approaches

As we know there are numbers of applications present where multimedia retrieval is used and also numbers of sources are present. So accuracy is the major issue in retrieval process. There are number of techniques and datasets available to retrieve information. Some techniques uses only text-based image retrieval (TBIR), some uses content-based image retrieval (CBIR) while some are using combination of both. In this paper we are focusing on both TBIR and CBIR results and then fusing these two results. For fusing we are using late fusion. TBIR captures conceptual meaning while CBIR used to avoid false results. So final results are more accurate. In this paper our main goal is to take review of different methods and approaches used for Multimedia Retrieval

Semantic Annotation of Documents: A Comparative Study

Semantic annotation, which is considered one of the semantic web applicative aspects, has been adopted by researchers from different communities as a paramount solution that improves searching and retrieval of information by promoting the richness of the content. However, researchers are facing challenges concerning both the quality and the relevance of the semantic annotations attached to the annotated document against its content as well as its semantics, without ignoring those regarding automation process which is supposed to ensure an optimal system for information indexing and retrieval. In this article, we will introduce the semantic annotation concept by presenting a state of the art including definitions, features and a classification of annotation systems. Systems and proposed approaches in the field will be cited, as well as a study of some existing annotation tools. This study will also pinpoint various problems and limitations related to the annotation in order to offer solutions for our future work

A framework for supporting knowledge representation – an ontological based approach

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresThe World Wide Web has had a tremendous impact on society and business in just a few years by making information instantly available. During this transition from physical to electronic means for information transport, the content and encoding of information has remained natural language and is only identified by its URL. Today, this is perhaps the most significant obstacle to streamlining business processes via the web. In order that processes may execute without human intervention, knowledge sources, such as documents, must become more machine understandable and must contain other information besides their main contents and URLs. The Semantic Web is a vision of a future web of machine-understandable data. On a machine understandable web, it will be possible for programs to easily determine what knowledge sources are about. This work introduces a conceptual framework and its implementation to support the classification and discovery of knowledge sources, supported by the above vision, where such sources’ information is structured and represented through a mathematical vector that semantically pinpoints the relevance of those knowledge sources within the domain of interest of each user. The presented work also addresses the enrichment of such knowledge representations, using the statistical relevance of keywords based on the classical vector space model concept, and extending it with ontological support, by using concepts and semantic relations, contained in a domain-specific ontology, to enrich knowledge sources’ semantic vectors. Semantic vectors are compared against each other, in order to obtain the similarity between them, and better support end users with knowledge source retrieval capabilities

User-Centered Social Information Retrieval Model Exploiting Annotations and Social Relationships

International audienceSocial Information Retrieval (SIR) has extended the classical information retrieval models and systems to take into account social information of the user within his social networks. We assume that a SIR system can exploit the informational social context (ISC) of the user in order to refine his retrieval, since different users may express different information needs as the same query. Hence, we present a SIR model that takes into account the user's social data, such as his annotations and his social relationships through social networks. We propose to integrate the user's ISC into the documents indexing process, allowing the SIR system to personalize the list of documents returned to the user. Our approach has shown interesting results on a test collection built from the social collaborative bookmarking network Delicious

Using Text Surrounding Method to Enhance Retrieval of Online Images by Google Search Engine

Purpose: the current research aimed to compare the effectiveness of various tags and codes for retrieving images from the Google. Design/methodology: selected images with different characteristics in a registered domain were carefully studied. The exception was that special conceptual features have been apportioned for each group of images separately. In this regard, each image group surrounding texts was dissimilar. Images were allocated with captionsincluding language in Farsi and English, alt text, image title, file name, free and controlled languages and appropriation text to images properties. Findings: allocating texts to images on a website causes Google to retrieve more images. Chi-square test for identification of significant differences among retrieved images in 5 Codes and revealed that in different codes, various numbers of images that were retrieved were significantly different. Caption allocation in English proved to have the best effect in retrieving images in the study sample, whereas file name had less effect in image retrieval ranking. Results of the Kruskal-Wallis test to assess the group differences in 5 codes revealed that differences were significant. Originality/Value: This paper tries to recall the importance of some elements which a search engine like Google may consider in indexing and retrieval of images. Widespread use of image tagging on the web enables Google and also other search engines to successfully retrieve images

Lexicalização de ontologias : o relacionamento entre conteúdo e significado no contexto da Recuperação da Informação

Esta proposta visa representar a linguagem natural na forma adequada às ontologias e vice-versa. Para tanto, propõe-se à criação semiautomática de base de léxicos em português brasileiro, contendo informações morfológicas, sintáticas e semânticas apropriadas para a leitura por máquinas, permitindo vincular dados estruturados e não estruturados, bem como integrar a leitura em modelo de recuperação da informação para aumentar a precisão. Os resultados alcançados demonstram a utilização da metodologia, no domínio de risco financeiro em português, para a elaboração da ontologia, da base léxico-semântica e da proposta do modelo de recuperação da informação semântica. Para avaliar a performance do modelo proposto, foram selecionados documentos contendo as principais definições do domínio de risco financeiro. Esses foram indexados com e sem anotação semântica. Para possibilitar a comparação entre as abordagens, foram criadas duas bases, a primeira representando a busca tradicional, e a segunda contendo o índice construído, a partir dos textos com as anotações semânticas para representar a busca semântica. A avaliação da proposta é baseada na revocação e na precisão. As consultas submetidas ao modelo mostram que a busca semântica supera o desempenho da tradicional e validam a metodologia empregada. O procedimento, embora adicione complexidade em sua elaboração, pode ser reproduzido em qualquer outro domínio.The proposal presented in this study seeks to properly represent natural language to ontologies and vice-versa. Therefore, the semi-automatic creation of a lexical database in Brazilian Portuguese containing morphological, syntactic, and semantic information that can be read by machines was proposed, allowing the link between structured and unstructured data and its integration into an information retrieval model to improve precision. The results obtained demonstrated that the methodology can be used in the risco financeiro (financial risk) domain in Portuguese for the construction of an ontology and the lexical-semantic database and the proposal of a semantic information retrieval model. In order to evaluate the performance of the proposed model, documents containing the main definitions of the financial risk domain were selected and indexed with and without semantic annotation. To enable the comparison between the approaches, two databases were created based on the texts with the semantic annotations to represent the semantic search. The first one represents the traditional search and the second contained the index built based on the texts with the semantic annotations to represent the semantic search. The evaluation of the proposal was based on recall and precision. The queries submitted to the model showed that the semantic search outperforms the traditional search and validates the methodology used. Although more complex, the procedure proposed can be used in all kinds of domains

Resources Annotation, Retrieval and Presentation: a semantic annotation management system

International audienceThis paper addresses the problem of the management of resources metadata. A variety of responses are discussed, and we describe one possible way forward, which uses a semantic annotation management tool. The term 'semantic' describes the ability to create, retrieve, query and navigate knowledgeably about things identified by a Web URI. The support for this semantic tool is RDF, through the integration of Jena, an open-source RDF API provided by HP laboratory. Thanks to RDF capabilities, this tool offers new search features such as hierarchical browsing based on the structure of RDF vocabularies and faceted-browsing using properties lists defined by the end-user. The navigation inside annotations uses intuitive modes such as left/right and backward/forward movements. Presentation is controlled by the user using a subset of the Fresnel language to specify how RDF graphs are presented. This work is ongoing; certain open issues are raised