Search (273 results, page 1 of 14)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Vallet, D.; Fernández, M.; Castells, P.: ¬An ontology-based information retrieval model (2005) 0.15 
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    Abstract
    Semantic search has been one of the motivations of the Semantic Web since it was envisioned. We propose a model for the exploitation of ontologybased KBs to improve search over large document repositories. Our approach includes an ontology-based scheme for the semi-automatic annotation of documents, and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with keyword-based search to achieve tolerance to KB incompleteness. Our proposal is illustrated with sample experiments showing improvements with respect to keyword-based search, and providing ground for further research and discussion.
    Source
    The Semantic Web: research and applications ; second European Semantic WebConference, ESWC 2005, Heraklion, Crete, Greece, May 29 - June 1, 2005 ; proceedings. Eds.: A. Gómez-Pérez u. J. Euzenat
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  2. Kozikowski, P. et al.: Support of part-whole relations in query answering (2016) 0.10 
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    Date
    1. 2.2016 18:25:22
    Source
    Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  3. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.08 
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    Date
    1. 2.2016 18:25:22
    Source
    Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  4. Gauch, S.; Wang, J.: Corpus analysis for TREC 5 query expansion (1997) 0.06 
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    Source
    The Fifth Text Retrieval Conference (TREC-5). Ed.: E.M. Voorhees u. D.K. Harman
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  5. Ross, J.: ¬A new way of information retrieval : 3-D indexing and concept mapping (2000) 0.06 
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    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  6. 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
  7. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.05 
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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
  8. Mayr, P.; Schaer, P.; Mutschke, P.: ¬A science model driven retrieval prototype (2011) 0.05 
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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
  9. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.05 
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    Abstract
    We present a deductive data model for concept-based query expansion. It is based on three abstraction levels: the conceptual, linguistic and occurrence levels. Concepts and relationships among them are represented at the conceptual level. The expression level represents natural language expressions for concepts. Each expression has one or more matching models at the occurrence level. Each model specifies the matching of the expression in database indices built in varying ways. The data model supports a concept-based query expansion and formulation tool, the ExpansionTool, for environments providing heterogeneous IR systems. Expansion is controlled by adjustable matching reliability.
    Source
    Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  10. Bhogal, J.; Macfarlane, A.; Smith, P.: ¬A review of ontology based query expansion (2007) 0.05 
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    Abstract
    This paper examines the meaning of context in relation to ontology based query expansion and contains a review of query expansion approaches. The various query expansion approaches include relevance feedback, corpus dependent knowledge models and corpus independent knowledge models. Case studies detailing query expansion using domain-specific and domain-independent ontologies are also included. The penultimate section attempts to synthesise the information obtained from the review and provide success factors in using an ontology for query expansion. Finally the area of further research in applying context from an ontology to query expansion within a newswire domain is described.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  11. 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
  12. Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016) 0.04 
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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. Gao, J.; Zhang, J.: Clustered SVD strategies in latent semantic indexing (2005) 0.04 
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    Abstract
    The text retrieval method using latent semantic indexing (LSI) technique with truncated singular value decomposition (SVD) has been intensively studied in recent years. The SVD reduces the noise contained in the original representation of the term-document matrix and improves the information retrieval accuracy. Recent studies indicate that SVD is mostly useful for small homogeneous data collections. For large inhomogeneous datasets, the performance of the SVD based text retrieval technique may deteriorate. We propose to partition a large inhomogeneous dataset into several smaller ones with clustered structure, on which we apply the truncated SVD. Our experimental results show that the clustered SVD strategies may enhance the retrieval accuracy and reduce the computing and storage costs.
    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) 0.04 
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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. Zarri, G.P.: Utilisation de structures conceptuelles complexes pour représenter le "contenu sémantique" de textes narratifs (1999) 0.04 
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    Source
    Organisation des connaissances en vue de leur intégration dans les systèmes de représentation et de recherche d'information. Ed.: J. Maniez, et al
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  16. Ahn, J.-w.; Brusilovsky, P.: Adaptive visualization for exploratory information retrieval (2013) 0.03 
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    Abstract
    As the volume and breadth of online information is rapidly increasing, ad hoc search systems become less and less efficient to answer information needs of modern users. To support the growing complexity of search tasks, researchers in the field of information developed and explored a range of approaches that extend the traditional ad hoc retrieval paradigm. Among these approaches, personalized search systems and exploratory search systems attracted many followers. Personalized search explored the power of artificial intelligence techniques to provide tailored search results according to different user interests, contexts, and tasks. In contrast, exploratory search capitalized on the power of human intelligence by providing users with more powerful interfaces to support the search process. As these approaches are not contradictory, we believe that they can re-enforce each other. We argue that the effectiveness of personalized search systems may be increased by allowing users to interact with the system and learn/investigate the problem in order to reach the final goal. We also suggest that an interactive visualization approach could offer a good ground to combine the strong sides of personalized and exploratory search approaches. This paper proposes a specific way to integrate interactive visualization and personalized search and introduces an adaptive visualization based search system Adaptive VIBE that implements it. We tested the effectiveness of Adaptive VIBE and investigated its strengths and weaknesses by conducting a full-scale user study. The results show that Adaptive VIBE can improve the precision and the productivity of the personalized search system while helping users to discover more diverse sets of information.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  17. Quiroga, L.M.; Mostafa, J.: ¬An experiment in building profiles in information filtering : the role of context of user relevance feedback (2002) 0.03 
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    Abstract
    An experiment was conducted to see how relevance feedback could be used to build and adjust profiles to improve the performance of filtering systems. Data was collected during the system interaction of 18 graduate students with SIFTER (Smart Information Filtering Technology for Electronic Resources), a filtering system that ranks incoming information based on users' profiles. The data set came from a collection of 6000 records concerning consumer health. In the first phase of the study, three different modes of profile acquisition were compared. The explicit mode allowed users to directly specify the profile; the implicit mode utilized relevance feedback to create and refine the profile; and the combined mode allowed users to initialize the profile and to continuously refine it using relevance feedback. Filtering performance, measured in terms of Normalized Precision, showed that the three approaches were significantly different ( [small alpha, Greek] =0.05 and p =0.012). The explicit mode of profile acquisition consistently produced superior results. Exclusive reliance on relevance feedback in the implicit mode resulted in inferior performance. The low performance obtained by the implicit acquisition mode motivated the second phase of the study, which aimed to clarify the role of context in relevance feedback judgments. An inductive content analysis of thinking aloud protocols showed dimensions that were highly situational, establishing the importance context plays in feedback relevance assessments. Results suggest the need for better representation of documents, profiles, and relevance feedback mechanisms that incorporate dimensions identified in this research.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  18. Sacco, G.M.: Dynamic taxonomies and guided searches (2006) 0.03 
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    Abstract
    A new search paradigm, in which the primary user activity is the guided exploration of a complex information space rather than the retrieval of items based on precise specifications, is proposed. The author claims that this paradigm is the norm in most practical applications, and that solutions based on traditional search methods are not effective in this context. He then presents a solution based on dynamic taxonomies, a knowledge management model that effectively guides users to reach their goal while giving them total freedom in exploring the information base. Applications, benefits, and current research are discussed.
    Date
    22. 7.2006 17:56:22
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  19. Efthimiadis, E.N.: End-users' understanding of thesaural knowledge structures in interactive query expansion (1994) 0.03 
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    Abstract
    The process of term selection for query expansion by end-users is discussed within the context of a study of interactive query expansion in a relevance feedback environment. This user study focuses on how users' perceive and understand term relationships, such as hierarchical and associative relationships, in their searches
    Date
    30. 3.2001 13:35:22
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  20. Lin, J.; DiCuccio, M.; Grigoryan, V.; Wilbur, W.J.: Navigating information spaces : a case study of related article search in PubMed (2008) 0.03 
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    Abstract
    The concept of an "information space" provides a powerful metaphor for guiding the design of interactive retrieval systems. We present a case study of related article search, a browsing tool designed to help users navigate the information space defined by results of the PubMed® search engine. This feature leverages content-similarity links that tie MEDLINE® citations together in a vast document network. We examine the effectiveness of related article search from two perspectives: a topological analysis of networks generated from information needs represented in the TREC 2005 genomics track and a query log analysis of real PubMed users. Together, data suggest that related article search is a useful feature and that browsing related articles has become an integral part of how users interact with PubMed.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a

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