Search (47 results, page 1 of 3)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Gradmann, S.; Olensky, M.: Semantische Kontextualisierung von Museumsbeständen in Europeana (2013) 0.01
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    Abstract
    Europeana ist eine Initiative der Europäischen Kommission, die 2005 den Aufbau einer "Europäischen digitalen Bibliothek" als Teil ihrer i2010 Agenda ankündigte. Europeana soll ein gemeinsamer multilingualer Zugangspunkt zu Europas digitalem Kulturerbe und gleichzeitig mehr als "nur" eine digitale Bibliothek werden: eine offene Schnittstelle (API) für Wissenschaftsanwendungen, die ein Netzwerk von Objektsurrogaren darstellt, die semantikbasiertes Objektretrieval und - verwendung ermöglichen. Einerseits ist die semantische Kontextualisierung der digitalen Objekte eine unabdingbare Voraussetzung für effektives Information Retrieval, da aufgrund der Beschaffenheit der Öbjekte (bildlich, multimedial) deskriptive Metadaten meist nicht ausreichen, auf der anderen Seite bildet sie die Grundlage für neues Wissen. Kern geisteswissenschaftlicher Arbeit ist immer schon die Reaggregation und Interpretation kultureller Artefakte gewesen und Europeana ermöglicht nun mit (teil-)automatisierbaren, semantikbasierten Öperationen über große kulturelle Quellcorpora völlig neue Perspektiven für die digital humanities. Folglich hat Europeans das Potenzial eine Schlüsselressource der Geistes- und Kulturwissenschaften und damit Teil deren zukünftiger digitaler Arbeitsumgebungen zu werden.
  2. Brezillon, P.; Saker, I.: Modeling context in information seeking (1999) 0.01
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    Abstract
    Context plays an important role in a number of domains where reasoning intervenes as in understanding, interpretation, diagnosis, etc. The reason is that reasoning activities heavily rely on a background (or experience) that is generally not made explicit and that gives a contextual dimension to knowledge. On the Web in December 1996, AItaVista gave more than 710000 pages containing the word context, when concept gives only 639000 references. A clear definition of this word stays to be found. There are several formal definitions of this concept (references are given in Brézillon, 1996): a set of preferences and/or beliefs, an infinite and only partially known collection of assumptions, a list of attributes, the product of an interpretation, possible worlds, assumptions under which a statement is true or false. One faces the same situation at the programming level: a collection of context schemas; a path in information retrieval; slots in object-oriented languages; a special, buffer-like data structure; a window on the screen, buttons which are functional customisable and shareable; an interpreter which controls the system's activity; the characteristics of the situation and the goals of the knowledge use; or entities (things or events) related in a certain way that permits to listen what is said and what is not said. Context is often assimilated at a set of restrictions (e.g., preconditions) that limit access to parts of the applications. The first works considering context explicitly are in Natural Language. Researchers in this domain focus on the linguistic context, sometimes associated with other types of contexts as: semantic context, cognitive context, physical and perceptual context, and social context (Bunt, 1997).
  3. Niemi, T.; Jämsen, J.: ¬A query language for discovering semantic associations, part II : sample queries and query evaluation (2007) 0.01
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    Abstract
    In our query language introduced in Part I (Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1559-1568) the user can formulate queries to find out (possibly complex) semantic relationships among entities. In this article we demonstrate the usage of our query language and discuss the new applications that it supports. We categorize several query types and give sample queries. The query types are categorized based on whether the entities specified in a query are known or unknown to the user in advance, and whether text information in documents is utilized. Natural language is used to represent the results of queries in order to facilitate correct interpretation by the user. We discuss briefly the issues related to the prototype implementation of the query language and show that an independent operation like Rho (Sheth et al., 2005; Anyanwu & Sheth, 2002, 2003), which presupposes entities of interest to be known in advance, is exceedingly inefficient in emulating the behavior of our query language. The discussion also covers potential problems, and challenges for future work.
  4. Ferreira, R.S.; Graça Pimentel, M. de; Cristo, M.: ¬A wikification prediction model based on the combination of latent, dyadic, and monadic features (2018) 0.01
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    Abstract
    Considering repositories of web documents that are semantically linked and created in a collaborative fashion, as in the case of Wikipedia, a key problem faced by content providers is the placement of links in the articles. These links must support user navigation and provide a deeper semantic interpretation of the content. Current wikification methods exploit machine learning techniques to capture characteristics of the concepts and its associations. In previous work, we proposed a preliminary prediction model combining traditional predictors with a latent component which captures the concept graph topology by means of matrix factorization. In this work, we provide a detailed description of our method and a deeper comparison with a state-of-the-art wikification method using a sample of Wikipedia and report a gain up to 13% in F1 score. We also provide a comprehensive analysis of the model performance showing the importance of the latent predictor component and the attributes derived from the associations between the concepts. Moreover, we include an analysis that allows us to conclude that the model is resilient to ambiguity without including a disambiguation phase. We finally report the positive impact of selecting training samples from specific content quality classes.
  5. Gillitzer, B.: Yewno (2017) 0.01
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    Abstract
    "Die Bayerische Staatsbibliothek testet den semantischen "Discovery Service" Yewno als zusätzliche thematische Suchmaschine für digitale Volltexte. Der Service ist unter folgendem Link erreichbar: https://www.bsb-muenchen.de/recherche-und-service/suchen-und-finden/yewno/. Das Identifizieren von Themen, um die es in einem Text geht, basiert bei Yewno alleine auf Methoden der künstlichen Intelligenz und des maschinellen Lernens. Dabei werden sie nicht - wie bei klassischen Katalogsystemen - einem Text als Ganzem zugeordnet, sondern der jeweiligen Textstelle. Die Eingabe eines Suchwortes bzw. Themas, bei Yewno "Konzept" genannt, führt umgehend zu einer grafischen Darstellung eines semantischen Netzwerks relevanter Konzepte und ihrer inhaltlichen Zusammenhänge. So ist ein Navigieren über thematische Beziehungen bis hin zu den Fundstellen im Text möglich, die dann in sogenannten Snippets angezeigt werden. In der Test-Anwendung der Bayerischen Staatsbibliothek durchsucht Yewno aktuell 40 Millionen englischsprachige Dokumente aus Publikationen namhafter Wissenschaftsverlage wie Cambridge University Press, Oxford University Press, Wiley, Sage und Springer, sowie Dokumente, die im Open Access verfügbar sind. Nach der dreimonatigen Testphase werden zunächst die Rückmeldungen der Nutzer ausgewertet. Ob und wann dann der Schritt von der klassischen Suchmaschine zum semantischen "Discovery Service" kommt und welche Bedeutung Anwendungen wie Yewno in diesem Zusammenhang einnehmen werden, ist heute noch nicht abzusehen. Die Software Yewno wurde vom gleichnamigen Startup in Zusammenarbeit mit der Stanford University entwickelt, mit der auch die Bayerische Staatsbibliothek eng kooperiert. [Inetbib-Posting vom 22.02.2017].
    Date
    22. 2.2017 10:16:49
  6. Shiri, A.A.; Revie, C.; Chowdhury, G.: Thesaurus-enhanced search interfaces (2002) 0.01
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    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  7. Michel, D.: Taxonomy of Subject Relationships (1997) 0.01
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    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  8. Jarvelin, K.: ¬A deductive data model for thesaurus navigation and query expansion (1996) 0.01
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    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  9. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.01
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:17:40
  10. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.01
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    Date
    30. 3.2001 13:32:22
  11. Shapiro, C.D.; Yan, P.-F.: Generous tools : thesauri in digital libraries (1996) 0.00
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    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  12. Chen, H.; Martinez, J.; Kirchhoff, A.; Ng, T.D.; Schatz, B.R.: Alleviating search uncertainty through concept associations : automatic indexing, co-occurence analysis, and parallel computing (1998) 0.00
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    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  13. Shiri, A.A.; Revie, C.; Chowdhury, G.: Thesaurus-assisted search term selection and query expansion : a review of user-centred studies (2002) 0.00
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    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  14. Shiri, A.A.; Revie, C.: End-user interaction with thesauri : an evaluation of cognitive overlap in search term selection (2004) 0.00
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    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  15. Spiteri, L.F.: ¬The essential elements of faceted thesauri (1999) 0.00
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    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  16. Hannech, A.: Système de recherche d'information étendue basé sur une projection multi-espaces (2018) 0.00
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    Abstract
    However, this assumption does not hold in all cases, the needs of the user evolve over time and can move away from his previous interests stored in his profile. In other cases, the user's profile may be misused to extract or infer new information needs. This problem is much more accentuated with ambiguous queries. When multiple POIs linked to a search query are identified in the user's profile, the system is unable to select the relevant data from that profile to respond to that request. This has a direct impact on the quality of the results provided to this user. In order to overcome some of these limitations, in this research thesis, we have been interested in the development of techniques aimed mainly at improving the relevance of the results of current SRIs and facilitating the exploration of major collections of documents. To do this, we propose a solution based on a new concept and model of indexing and information retrieval called multi-spaces projection. This proposal is based on the exploitation of different categories of semantic and social information that enrich the universe of document representation and search queries in several dimensions of interpretations. The originality of this representation is to be able to distinguish between the different interpretations used for the description and the search for documents. This gives a better visibility on the results returned and helps to provide a greater flexibility of search and exploration, giving the user the ability to navigate one or more views of data that interest him the most. In addition, the proposed multidimensional representation universes for document description and search query interpretation help to improve the relevance of the user's results by providing a diversity of research / exploration that helps meet his diverse needs and those of other different users. This study exploits different aspects that are related to the personalized search and aims to solve the problems caused by the evolution of the information needs of the user. Thus, when the profile of this user is used by our system, a technique is proposed and used to identify the interests most representative of his current needs in his profile. This technique is based on the combination of three influential factors, including the contextual, frequency and temporal factor of the data. The ability of users to interact, exchange ideas and opinions, and form social networks on the Web, has led systems to focus on the types of interactions these users have at the level of interaction between them as well as their social roles in the system. This social information is discussed and integrated into this research work. The impact and how they are integrated into the IR process are studied to improve the relevance of the results.
  17. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.00
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    Date
    1. 2.2016 18:25:22
  18. Kozikowski, P. et al.: Support of part-whole relations in query answering (2016) 0.00
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    Date
    1. 2.2016 18:25:22
  19. Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016) 0.00
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  20. Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016) 0.00
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    Source
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Years

Languages

  • e 38
  • d 8
  • f 1
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Types

  • a 39
  • el 6
  • m 2
  • r 2
  • x 2
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