Search (273 results, page 1 of 14)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Rahmstorf, G.: Integriertes Management inhaltlicher Datenarten (2001) 0.12
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    Abstract
    Inhaltliche Daten sind im Unterschied zu Messdaten, Zahlen, Analogsignalen und anderen Informationen solche Daten, die sich auch sprachlich interpretieren lassen. Sie transportieren Inhalte, die sich benennen lassen. Zu inhaltlichen Daten gehören z. B. Auftragsdaten, Werbetexte, Produktbezeichnungen und Patentklassifikationen. Die meisten Daten, die im Internet kommuniziert werden, sind inhaltliche Daten. Man kann inhaltliche Daten in vier Klassen einordnen: * Wissensdaten - formatierte Daten (Fakten u. a. Daten in strukturierter Form), - nichtformatierte Daten (vorwiegend Texte); * Zugriffsdaten - Benennungsdaten (Wortschatz, Terminologie, Themen u. a.), - Begriffsdaten (Ordnungs- und Bedeutungsstrukturen). In der Wissensorganisation geht es hauptsächlich darum, die unüberschaubare Fülle des Wissens zu ordnen und wiederauffindbar zu machen. Daher befasst sich das Fach nicht nur mit dem Wissen selbst, selbst sondern auch mit den Mitteln, die dazu verwendet werden, das Wissen zu ordnen und auffindbar zu machen
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  2. Kozikowski, P. et al.: Support of part-whole relations in query answering (2016) 0.06
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    Date
    1. 2.2016 18:25:22
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  3. Shiri, A.A.; Revie, C.; Chowdhury, G.: Thesaurus-enhanced search interfaces (2002) 0.06
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    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  4. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005) 0.05
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    Date
    11. 2.2011 18:22:58
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  5. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.05
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    Date
    30. 3.2001 13:32:22
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  6. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.04
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:17:40
    Source
    Visual Interfaces to Digital Libraries. Eds.: Börner, K. u. C. Chen
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  7. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.04
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    Abstract
    The digital library system Daffodil is targeted at strategic support of users during the information search process. For searching, exploring and managing digital library objects it provides user-customisable information seeking patterns over a federation of heterogeneous digital libraries. In this paper evaluation results with respect to retrieval effectiveness, efficiency and user satisfaction are presented. The analysis focuses on strategic support for the scientific work-flow. Daffodil supports the whole work-flow, from data source selection over information seeking to the representation, organisation and reuse of information. By embedding high level search functionality into the scientific work-flow, the user experiences better strategic system support due to a more systematic work process. These ideas have been implemented in Daffodil followed by a qualitative evaluation. The evaluation has been conducted with 28 participants, ranging from information seeking novices to experts. The results are promising, as they support the chosen model.
    Date
    16.11.2008 16:22:48
    Source
    Research and advanced technology for digital libraries : 8th European conference, ECDL 2004, Bath, UK, September 12-17, 2004 : proceedings. Eds.: Heery, R. u. E. Lyon
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  8. Symonds, M.; Bruza, P.; Zuccon, G.; Koopman, B.; Sitbon, L.; Turner, I.: Automatic query expansion : a structural linguistic perspective (2014) 0.04
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    Abstract
    A user's query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques model syntagmatic associations that infer two terms co-occur more often than by chance in natural language. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches to query expansion and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process improves retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  9. Bernier-Colborne, G.: Identifying semantic relations in a specialized corpus through distributional analysis of a cooccurrence tensor (2014) 0.04
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    Abstract
    We describe a method of encoding cooccurrence information in a three-way tensor from which HAL-style word space models can be derived. We use these models to identify semantic relations in a specialized corpus. Results suggest that the tensor-based methods we propose are more robust than the basic HAL model in some respects.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  10. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005) 0.04
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    Date
    11. 2.2011 18:22:25
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  11. Koopman, B.; Zuccon, G.; Bruza, P.; Sitbon, L.; Lawley, M.: Information retrieval as semantic inference : a graph Inference model applied to medical search (2016) 0.03
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    Abstract
    This paper presents a Graph Inference retrieval model that integrates structured knowledge resources, statistical information retrieval methods and inference in a unified framework. Key components of the model are a graph-based representation of the corpus and retrieval driven by an inference mechanism achieved as a traversal over the graph. The model is proposed to tackle the semantic gap problem-the mismatch between the raw data and the way a human being interprets it. We break down the semantic gap problem into five core issues, each requiring a specific type of inference in order to be overcome. Our model and evaluation is applied to the medical domain because search within this domain is particularly challenging and, as we show, often requires inference. In addition, this domain features both structured knowledge resources as well as unstructured text. Our evaluation shows that inference can be effective, retrieving many new relevant documents that are not retrieved by state-of-the-art information retrieval models. We show that many retrieved documents were not pooled by keyword-based search methods, prompting us to perform additional relevance assessment on these new documents. A third of the newly retrieved documents judged were found to be relevant. Our analysis provides a thorough understanding of when and how to apply inference for retrieval, including a categorisation of queries according to the effect of inference. The inference mechanism promoted recall by retrieving new relevant documents not found by previous keyword-based approaches. In addition, it promoted precision by an effective reranking of documents. When inference is used, performance gains can generally be expected on hard queries. However, inference should not be applied universally: for easy, unambiguous queries and queries with few relevant documents, inference did adversely affect effectiveness. These conclusions reflect the fact that for retrieval as inference to be effective, a careful balancing act is involved. Finally, although the Graph Inference model is developed and applied to medical search, it is a general retrieval model applicable to other areas such as web search, where an emerging research trend is to utilise structured knowledge resources for more effective semantic search.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  12. Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016) 0.03
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  13. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.03
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    Date
    1. 2.2016 18:25:22
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  14. Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016) 0.03
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  15. Mayr, P.; Schaer, P.; Mutschke, P.: ¬A science model driven retrieval prototype (2011) 0.03
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    Abstract
    This paper is about a better understanding of the structure and dynamics of science and the usage of these insights for compensating the typical problems that arises in metadata-driven Digital Libraries. Three science model driven retrieval services are presented: co-word analysis based query expansion, re-ranking via Bradfordizing and author centrality. The services are evaluated with relevance assessments from which two important implications emerge: (1) precision values of the retrieval services are the same or better than the tf-idf retrieval baseline and (2) each service retrieved a disjoint set of documents. The different services each favor quite other - but still relevant - documents than pure term-frequency based rankings. The proposed models and derived retrieval services therefore open up new viewpoints on the scientific knowledge space and provide an alternative framework to structure scholarly information systems.
    Source
    Concepts in context: Proceedings of the Cologne Conference on Interoperability and Semantics in Knowledge Organization July 19th - 20th, 2010. Eds.: F. Boteram, W. Gödert u. J. Hubrich
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  16. Drexel, G.: Knowledge engineering for intelligent information retrieval (2001) 0.03
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    Abstract
    This paper presents a clustered approach to designing an overall ontological model together with a general rule-based component that serves as a mapping device. By observational criteria, a multi-lingual team of experts excerpts concepts from general communication in the media. The team, then, finds equivalent expressions in English, German, French, and Spanish. On the basis of a set of ontological and lexical relations, a conceptual network is built up. Concepts are thought to be universal. Objects unique in time and space are identified by names and will be explained by the universals as their instances. Our approach relies on multi-relational descriptions of concepts. It provides a powerful tool for documentation and conceptual language learning. First and foremost, our multi-lingual, polyhierarchical ontology fills the gap of semantically-based information retrieval by generating enhanced and improved queries for internet search
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  17. Buckley, C.; Allan, J.; Salton, G.: Automatic routing and retrieval using Smart : TREC-2 (1995) 0.03
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    Abstract
    The Smart information retrieval project emphazises completely automatic approaches to the understanding and retrieval of large quantities of text. The work in the TREC-2 environment continues, performing both routing and ad hoc experiments. The ad hoc work extends investigations into combining global similarities, giving an overall indication of how a document matches a query, with local similarities identifying a smaller part of the document that matches the query. The performance of ad hoc runs is good, but it is clear that full advantage of the available local information is not been taken advantage of. The routing experiments use conventional relevance feedback approaches to routing, but with a much greater degree of query expansion than was previously done. The length of a query vector is increased by a factor of 5 to 10 by adding terms found in previously seen relevant documents. This approach improves effectiveness by 30-40% over the original query
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  18. Shiri, A.A.; Revie, C.; Chowdhury, G.: Thesaurus-assisted search term selection and query expansion : a review of user-centred studies (2002) 0.03
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    Abstract
    This paper provides a review of the literature related to the application of domain-specific thesauri in the search and retrieval process. Focusing an studies that adopt a user-centred approach, the review presents a survey of the methodologies and results from empirical studies undertaken an the use of thesauri as sources of term selection for query formulation and expansion during the search process. It summarises the ways in which domain-specific thesauri from different disciplines have been used by various types of users and how these tools aid users in the selection of search terms. The review consists of two main sections: first, studies an thesaurus-aided search term selection; and second, studies dealing with query expansion using thesauri. Both sections are illustrated with case studies that have adopted a user-centred approach.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  19. Pontis, S.; Kefalidou, G.; Blandford, A.; Forth, J.; Makri, S.; Sharples, S.; Wiggins, G.; Woods, M.: Academics' responses to encountered information : context matters (2016) 0.03
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    Abstract
    An increasing number of tools are being developed to help academics interact with information, but little is known about the benefits of those tools for their users. This study evaluated academics' receptiveness to information proposed by a mobile app, the SerenA Notebook: information that is based in their inferred interests but does not relate directly to a prior recognized need. The evaluated app aimed at creating the experience of serendipitous encounters: generating ideas and inspiring thoughts, and potentially triggering follow-up actions, by providing users with suggestions related to their work and leisure interests. We studied how 20 academics interacted with messages sent by the mobile app (3 per day over 10 consecutive days). Collected data sets were analyzed using thematic analysis. We found that contextual factors (location, activity, and focus) strongly influenced their responses to messages. Academics described some unsolicited information as interesting but irrelevant when they could not make immediate use of it. They highlighted filtering information as their major struggle rather than finding information. Some messages that were positively received acted as reminders of activities participants were meant to be doing but were postponing, or were relevant to ongoing activities at the time the information was received.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  20. Srinivasan, P.: Query expansion and MEDLINE (1996) 0.03
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    Abstract
    Evaluates the retrieval effectiveness of query expansion strategies on a test collection of the medical database MEDLINE using Cornell University's SMART retrieval system. Tests 3 expansion strategies for their ability to identify appropriate MeSH terms for user queries. Compares retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a collection of 75 queries and 2.334 Medline citations. Recommends query expansions using retrieval feedback for adding MeSH search terms to a user's initial query
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a

Years

Languages

  • e 228
  • d 40
  • f 2
  • chi 1
  • More… Less…

Types

  • a 235
  • el 28
  • m 19
  • r 8
  • x 4
  • p 2
  • s 2
  • More… Less…