Search (9 results, page 1 of 1)

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Content

The papers are organized in several sessions and tracks: general track on ontology evolution, engineering, and frameworks, semantic Web and metadata extraction, modelling, interoperability and exploratory search, data analysis, reuse and visualization; track on digital libraries, information retrieval, linked and social data; track on metadata and semantics for open repositories, research information systems and data infrastructure; track on metadata and semantics for agriculture, food and environment; track on metadata and semantics for cultural collections and applications; track on European and national projects.

LCSH

Information storage and retrieval systems

Subject

Information storage and retrieval systems

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Abstract

Current hypertext systems have been widely and effectively used on relatively small data volumes. Explores the potential of database technology for aiding the implementation of hypertext systems holding very large amounts of complex data. Databases meet many requirements of the hypermedium: persistent data management, large volumes, data modelling, multi-level architecture with abstractions and views, metadata integrated with operational data, short-term transaction processing and high-level end-user languages for searching and updating data. Describes a system implementing the storage, retrieval and recall of trails through hypertext comprising textual complex objects (to illustrate the potential for the use of data bases). Discusses weaknesses in current database systems for handling the complex modelling required

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Abstract

This book constitutes the refereed proceedings of the 8th Metadata and Semantics Research Conference, MTSR 2014, held in Karlsruhe, Germany, in November 2014. The 23 full papers and 9 short papers presented were carefully reviewed and selected from 57 submissions. The papers are organized in several sessions and tracks. They cover the following topics: metadata and linked data: tools and models; (meta) data quality assessment and curation; semantic interoperability, ontology-based data access and representation; big data and digital libraries in health, science and technology; metadata and semantics for open repositories, research information systems and data infrastructure; metadata and semantics for cultural collections and applications; semantics for agriculture, food and environment.

Content

Metadata and linked data.- Tools and models.- (Meta)data quality assessment and curation.- Semantic interoperability, ontology-based data access and representation.- Big data and digital libraries in health, science and technology.- Metadata and semantics for open repositories, research information systems and data infrastructure.- Metadata and semantics for cultural collections and applications.- Semantics for agriculture, food and environment.

LCSH

Information storage and retrieval systems

Subject

Information storage and retrieval systems

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Abstract

Improvements in network bandwidth along with dramatic drops in digital storage and processing costs have resulted in the explosive growth of multimedia (combinations of text, image, audio, and video) resources on the Internet and in digital repositories. A suite of computer technologies delivering speech, image, and natural language understanding can automatically derive descriptive metadata for such resources. Difficulties for end users ensue, however, with the tremendous volume and varying quality of automated metadata for multimedia information systems. This lecture surveys automatic metadata creation methods for dealing with multimedia information resources, using broadcast news, documentaries, and oral histories as examples. Strategies for improving the utility of such metadata are discussed, including computationally intensive approaches, leveraging multimodal redundancy, folding in context, and leaving precision-recall tradeoffs under user control. Interfaces building from automatically generated metadata are presented, illustrating the use of video surrogates in multimedia information systems. Traditional information retrieval evaluation is discussed through the annual National Institute of Standards and Technology TRECVID forum, with experiments on exploratory search extending the discussion beyond fact-finding to broader, longer term search activities of learning, analysis, synthesis, and discovery.

Content

Table of Contents: Evolution of Multimedia Information Systems: 1990-2008 / Survey of Automatic Metadata Creation Methods / Refinement of Automatic Metadata / Multimedia Surrogates / End-User Utility for Metadata and Surrogates: Effectiveness, Efficiency, and Satisfaction

Series

Synthesis lectures on information concepts, retrieval & services

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LCSH

Information storage and retrieval

Subject

Information storage and retrieval

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Abstract

E-sciences are data-intensive sciences that make a large use of the Web to share, collect, and process data. In this context, primary scientific data is becoming a new challenging issue as data must be extensively described (1) to account for empiric conditions and results that allow interpretation and/or analyses and (2) to be understandable by computers used for data storage and information retrieval. With this respect, metadata is a focal point whatever it is considered from the point of view of the user to visualize and exploit data as well as this of the search tools to find and retrieve information. Numerous disciplines are concerned with the issues of describing complex observations and addressing pertinent knowledge. In this paper, similarities and differences in data description and exploration strategies among disciplines in e-sciences are examined.

Source

Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

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LCSH

Information storage and retrieval systems

Subject

Information storage and retrieval systems

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Abstract

We propose an extension of a mediator architecture. This extension is oriented to ontology-driven data integration. In our architecture ontologies are not managed by an extemal component or service, but are integrated in the mediation layer. This approach implies rethinking the mediator design, but at the same time provides advantages from a database perspective. Some of these advantages include the application of optimization and evaluation techniques that use and combine information from all abstraction levels (physical schema, logical schema and semantic information defined by ontology). 1. Introduction Although the Web is probably the richest information repository in human history, users cannot specify what they want from it. Two major problems that arise in current search engines (Heflin, 2001) are: a) polysemy, when the same word is used with different meanings; b) synonymy, when two different words have the same meaning. Polysemy causes irrelevant information retrieval. On the other hand, synonymy produces lost of useful documents. The lack of a capability to understand the context of the words and the relationships among required terms, explains many of the lost and false results produced by search engines. The Semantic Web will bring structure to the meaningful content of Web pages, giving semantic relationships among terms and possibly avoiding the previous problems. Various proposals have appeared for meta-data representation and communication standards, and other services and tools that may eventually merge into the global Semantic Web (Berners-lee, 2001). Hopefully, in the next few years we will see the universal adoption of open standards for representation and sharing of meta-information. In this environment, software agents roaming from page to page can readily carry out sophisticated tasks for users (Berners-Lee, 2001). In this context, ontologies can be seen as metadata that represent semantic of data; providing a knowledge domain standard vocabulary, like DTDs and XML Schema do. If its pages were so structured, the Web could be seen as a heterogeneous collection of autonomous databases. This suggests that techniques developed in the Database area could be useful. Database research mainly deals with efficient storage and retrieval and with powerful query languages.

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Abstract

Information management in corporate environments is a growing problem as companies' information assets grow and their need to use them in their operations. Several management models have been practiced with application on the most diverse fronts, practices that integrate the so-called Enterprise Content Management. This study proposes a conceptual model of semantic corporate information ecosystem, based on the Universal Document Model proposed by Dagobert Soergel. It focuses on unstructured information objects, especially multimedia, increasingly used in corporate environments, adding semantics and expanding their recovery potential in the composition and reuse of dynamic documents on demand. The proposed model considers stable elements in the organizational environment, such as actors, processes, business metadata and information objects, as well as some basic infrastructures of the corporate information environment. The main objective is to establish a conceptual model that adds semantic intelligence to information assets, leveraging pre-existing infrastructure in organizations, integrating and relating objects to other objects, actors and business processes. The approach methodology considered the state of the art of Information Organization, Representation and Retrieval, Organizational Content Management and Semantic Web technologies, in the scientific literature, as bases for the establishment of an integrative conceptual model. Therefore, the research will be qualitative and exploratory. The predicted steps of the model are: Environment, Data Type and Source Definition, Data Distillation, Metadata Enrichment, and Storage. As a result, in theoretical terms the extended model allows to process heterogeneous and unstructured data according to the established cut-outs and through the processes listed above, allowing value creation in the composition of dynamic information objects, with semantic aggregations to metadata.