Search (258 results, page 13 of 13)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Qu, R.; Fang, Y.; Bai, W.; Jiang, Y.: Computing semantic similarity based on novel models of semantic representation using Wikipedia (2018) 0.00
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    Source
    Information processing and management. 54(2018) no.6, S.1002-1021
  2. Fernández-Reyes, F.C.; Hermosillo-Valadez, J.; Montes-y-Gómez, M.: ¬A prospect-guided global query expansion strategy using word embeddings (2018) 0.00
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    Information processing and management. 54(2018) no.1, S.1-13
  3. Caro Castro, C.; Travieso Rodríguez, C.: Ariadne's thread : knowledge structures for browsing in OPAC's (2003) 0.00
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    Abstract
    Subject searching is the most common but also the most conflictive searching for end user. The aim of this paper is to check how users expressions match subject headings and to prove if knowledge structure used in online catalogs enhances searching effectiveness. A bibliographic revision about difficulties in subject access and proposed methods to improve it is also presented. For the empirical analysis, transaction logs from two university libraries, online catalogs (CISNE and FAMA) were collected. Results show that more than a quarter of user queries are effective due to an alphabetical subject index approach and browsing through hypertextual links. 1. Introduction Since the 1980's, online public access catalogs (OPAC's) have become usual way to access bibliographic information. During the last two decades the technological development has helped to extend their use, making feasible the access for a whole of users that is getting more and more extensive and heterogeneous, and also to incorporate information resources in electronic formats and to interconnect systems. However, technology seems to have developed faster than our knowledge about the tasks where it has been applied and than the evolution of our capacities for adapting to it. The conceptual model of OPAC has been hardly modified recently, and for interacting with them, users still need to combine the same skills and basic knowledge than at the beginning of its introduction (Borgman, 1986, 2000): a) conceptual knowledge to translate the information need into an appropriate query because of a well-designed mental model of the system, b) semantic and syntactic knowledge to be able to implement that query (access fields, searching type, Boolean logic, etc.) and c) basic technical skills in computing. At present many users have the essential technical skills to make use, with more or less expertise, of a computer. This number is substantially reduced when it is referred to the conceptual, semantic and syntactic knowledge that is necessary to achieve a moderately satisfactory search. An added difficulty arises in subject searching, as users should concrete their unknown information needs in terms that the information retrieval system can understand. Many researches have focused an unskilled searchers' difficulties to enter an effective query. The mental models influence, users assumption about characteristics, structure, contents and operation of the system they interact with have been analysed (Dillon, 2000; Dimitroff, 2000). Another issue that implies difficulties is vocabulary: how to find the right terms to implement a query and to modify it as the case may be. Terminology and expressions characteristics used in searching (Bates, 1993), the match between user terms and the subject headings from the catalog (Carlyle, 1989; Drabensttot, 1996; Drabensttot & Vizine-Goetz, 1994), the incidence of spelling errors (Drabensttot and Weller, 1996; Ferl and Millsap, 1996; Walker and Jones, 1987), users problems
    Pages
    S.500-509
  4. Efthimiadis, E.N.: Interactive query expansion : a user-based evaluation in a relevance feedback environment (2000) 0.00
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    Source
    Journal of the American Society for Information Science. 51(2000) no.11, S.989-1003
  5. Otto, A.: Ordnungssysteme als Wissensbasis für die Suche in textbasierten Datenbeständen : dargestellt am Beispiel einer soziologischen Bibliographie (1998) 0.00
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    Pages
    S.249-258
  6. Brezillon, P.; Saker, I.: Modeling context in information seeking (1999) 0.00
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    Pages
    S.479-493
  7. Jun, W.: ¬A knowledge network constructed by integrating classification, thesaurus and metadata in a digital library (2003) 0.00
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    Source
    Bulletin of the American Society for Information Science. 29(2003) no.2, S.24-28
  8. Bilal, D.; Kirby, J.: Differences and similarities in information seeking : children and adults as Web users (2002) 0.00
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    Source
    Information processing and management. 38(2002) no.5, S.649-670
  9. Imhof, A.: RSWK/SWD und Faceted Browsing : neue Möglichkeiten einer inhaltlich-intuitiven Navigation (2006) 0.00
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    Source
    Bibliotheksdienst. 40(2006) H.8/9, S.1015-1025
  10. Schek, M.: Automatische Klassifizierung in Erschließung und Recherche eines Pressearchivs (2006) 0.00
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    Pages
    S.313-324
  11. Tudhope, D.; Binding, C.; Blocks, D.; Cunliffe, D.: FACET: thesaurus retrieval with semantic term expansion (2002) 0.00
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    Pages
    S.384
  12. Shah, C.: Collaborative information seeking : the art and science of making the whole greater than the sum of all (2012) 0.00
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    Pages
    XXI, 185 S
  13. Koopman, B.; Zuccon, G.; Bruza, P.; Sitbon, L.; Lawley, M.: Information retrieval as semantic inference : a graph Inference model applied to medical search (2016) 0.00
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    Source
    Information Retrieval Journal. 19(2016) no.1, S.6-37
  14. Layfield, C.; Azzopardi, J,; Staff, C.: Experiments with document retrieval from small text collections using Latent Semantic Analysis or term similarity with query coordination and automatic relevance feedback (2017) 0.00
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    Pages
    S.25-36
  15. Vo, D.-T.; Bagheri, E.: Feature-enriched matrix factorization for relation extraction (2019) 0.00
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    Source
    Information processing and management. 56(2019) no.3, S.424-444
  16. Sebastian, Y.: Literature-based discovery by learning heterogeneous bibliographic information networks (2017) 0.00
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    Pages
    xix, 215 S
  17. Hannech, A.: Système de recherche d'information étendue basé sur une projection multi-espaces (2018) 0.00
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    Abstract
    Since its appearance in the early 90's, the World Wide Web (WWW or Web) has provided universal access to knowledge and the world of information has been primarily witness to a great revolution (the digital revolution). It quickly became very popular, making it the largest and most comprehensive database and knowledge base thanks to the amount and diversity of data it contains. However, the considerable increase and evolution of these data raises important problems for users, in particular for accessing the documents most relevant to their search queries. In order to cope with this exponential explosion of data volume and facilitate their access by users, various models are offered by information retrieval systems (IRS) for the representation and retrieval of web documents. Traditional SRIs use simple keywords that are not semantically linked to index and retrieve these documents. This creates limitations in terms of the relevance and ease of exploration of results. To overcome these limitations, existing techniques enrich documents by integrating external keywords from different sources. However, these systems still suffer from limitations that are related to the exploitation techniques of these sources of enrichment. When the different sources are used so that they cannot be distinguished by the system, this limits the flexibility of the exploration models that can be applied to the results returned by this system. Users then feel lost to these results, and find themselves forced to filter them manually to select the relevant information. If they want to go further, they must reformulate and target their search queries even more until they reach the documents that best meet their expectations. In this way, even if the systems manage to find more relevant results, their presentation remains problematic. In order to target research to more user-specific information needs and improve the relevance and exploration of its research findings, advanced SRIs adopt different data personalization techniques that assume that current research of user is directly related to his profile and / or previous browsing / search experiences.
    Pages
    351 S
  18. Zhang, J.; Mostafa, J.; Tripathy, H.: Information retrieval by semantic analysis and visualization of the concept space of D-Lib® magazine (2002) 0.00
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    Source
    D-Lib magazine. 8(2002) no.10, x S

Years

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  • m 19
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