Search (36 results, page 1 of 2)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × language_ss:"e"
  1. Fieldhouse, M.; Hancock-Beaulieu, M.: ¬The design of a graphical user interface for a highly interactive information retrieval system (1996) 0.02 
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    Pages
    S.205-218
    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  2. Context: nature, impact, and role : 5th International Conference on Conceptions of Library and Information Science, CoLIS 2005, Glasgow 2005; Proceedings (2005) 0.01 
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    Classification
    SS 4800 [Informatik # Enzyklopädien und Handbücher. Kongreßberichte Schriftenreihe. Tafeln und Formelsammlungen # Schriftenreihen (indiv. Sign.) # Lecture notes in computer science]
    Footnote
    Rez. in: Mitt. VÖB 59(2006) H.3, S.100-103 (O. Oberhauser): "Dieses als Band 3507 der bekannten, seit 1973 erscheinenden Springer-Serie Lecture Notes in Computer Science (LNCS) publizierte Buch versammelt die Vorträge der 5. Tagung "Conceptions of Library and Information Science". CoLIS hat sich in den letzten anderthalb Jahrzehnten als internationales Forum für die Präsentation und Rezeption von Forschung auf den Fachgebieten Informatik und Informationswissenschaft etabliert. Auf die 1992 in Tampere (Finnland) anlässlich des damals 20jährigen Bestehens des dortigen Instituts für Informationswissenschaft abgehaltene erste Tagung folgten weitere in Kopenhagen (1996), Dubrovnik (1999) und Seattle, WA (2002). Die zuletzt an der Strathclyde University in Glasgow (2005) veranstaltete Konferenz war dem Thema "Context" im Rahmen der informationsbezogenen Forschung gewidmet, einem komplexen, dynamischen und multidimensionalen Begriff von grosser Bedeutung für das Verhalten und die Interaktion von Mensch und Maschine. . . .
    Mehrere Beiträge befassen sich mit dem Problem der Relevanz. Erica Cosijn und Theo Bothma (Pretoria) argumentieren, dass für das Benutzerverhalten neben der thematischen Relevanz auch verschiedene andere Relevanzdimensionen eine Rolle spielen und schlagen auf der Basis eines (abermals auf Ingwersen zurückgehenden) erweiterten Relevanzmodells vor, dass IR-Systeme die Möglichkeit zur Abgabe auch kognitiver, situativer und sozio-kognitiver Relevanzurteile bieten sollten. Elaine Toms et al. (Kanada) berichten von einer Studie, in der versucht wurde, die schon vor 30 Jahren von Tefko Saracevic3 erstellten fünf Relevanzdimensionen (kognitiv, motivational, situativ, thematisch und algorithmisch) zu operationalisieren und anhand von Recherchen mit einer Web-Suchmaschine zu untersuchen. Die Ergebnisse zeigten, dass sich diese fünf Dimensionen in drei Typen vereinen lassen, die Benutzer, System und Aufgabe repräsentieren. Von einer völlig anderen Seite nähern sich Olof Sundin und Jenny Johannison (Boras, Schweden) der Relevanzthematik, indem sie einen kommunikationsorientierten, neo-pragmatistischen Ansatz (nach Richard Rorty) wählen, um Informationssuche und Relevanz zu analysieren, und dabei auch auf das Werk von Michel Foucault zurückgreifen. Weitere interessante Artikel befassen sich mit Bradford's Law of Scattering (Hjørland & Nicolaisen), Information Sharing and Timing (Widén-Wulff & Davenport), Annotations as Context for Searching Documents (Agosti & Ferro), sowie dem Nutzen von neuen Informationsquellen wie Web Links, Newsgroups und Blogs für die sozial- und informationswissenschaftliche Forschung (Thelwall & Wouters). In Summe liegt hier ein interessantes und anspruchsvolles Buch vor - inhaltlich natürlich nicht gerade einheitlich und geschlossen, doch dies darf man bei einem Konferenzband ohnedies nicht erwarten. Manche der abgedruckten Beiträge sind sicher nicht einfach zu lesen, lohnen aber die Mühe. Auch für Praktiker aus Bibliothek und Information ist einiges dabei, sofern sie sich für die wissenschaftliche Basis ihrer Tätigkeit interessieren. Fachlich einschlägige Spezial- und grössere Allgemeinbibliotheken sollten das Werk daher unbedingt führen.
    RVK
    SS 4800 [Informatik # Enzyklopädien und Handbücher. Kongreßberichte Schriftenreihe. Tafeln und Formelsammlungen # Schriftenreihen (indiv. Sign.) # Lecture notes in computer science]
  3. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.01 
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    Date
    1. 8.1996 22:08:06
    Theme
    Internet
  4. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.00 
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:17:40
  5. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.00 
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    Date
    30. 3.2001 13:32:22
  6. Khan, M.S.; Khor, S.: Enhanced Web document retrieval using automatic query expansion (2004) 0.00 
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    Abstract
    The ever growing popularity of the Internet as a source of information, coupled with the accompanying growth in the number of documents made available through the World Wide Web, is leading to an increasing demand for more efficient and accurate information retrieval tools. Numerous techniques have been proposed and tried for improving the effectiveness of searching the World Wide Web for documents relevant to a given topic of interest. The specification of appropriate keywords and phrases by the user is crucial for the successful execution of a query as measured by the relevance of documents retrieved. Lack of users' knowledge an the search topic and their changing information needs often make it difficult for them to find suitable keywords or phrases for a query. This results in searches that fail to cover all likely aspects of the topic of interest. We describe a scheme that attempts to remedy this situation by automatically expanding the user query through the analysis of initially retrieved documents. Experimental results to demonstrate the effectiveness of the query expansion scheure are presented.
    Theme
    Internet
  7. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.00 
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    Date
    1. 2.2016 18:25:22
  8. 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
  9. 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
  10. 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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    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  11. Sacco, G.M.: Dynamic taxonomies and guided searches (2006) 0.00 
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    Date
    22. 7.2006 17:56:22
  12. Schwartz, C.: Web search engines (1998) 0.00 
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    Abstract
    This reviews looks briefly at the history of WWW search engine development, considers the current state of affairs, and reflects on the future. Networked discovery tools have evolved along with Internet resource availability. WWW search engines display some complexity in their variety, content, resource acquisition strategies, and in the array of tools the deploy to assist users. A small but growing body of evaluation literature, much of it not systematic in nature, indicates that performance effectiveness is difficult to assess in this setting. Significant improvements in general-content search engine retrieval and ranking performance may not be possible, and are probalby not worth the effort, although search engine providers have introduced some rudimentary attempts at personalization, summarization, and query expansion. The shift to distributed search across multitype database systems could extend general networked discovery and retrieval to include smaller resource collections with rich metadata and navigation tools
  13. Menczer, F.: Lexical and semantic clustering by Web links (2004) 0.00 
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    Theme
    Internet
  14. Drexel, G.: Knowledge engineering for intelligent information retrieval (2001) 0.00 
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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
  15. Wang, Y.-H.; Jhuo, P.-S.: ¬A semantic faceted search with rule-based inference (2009) 0.00 
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    Abstract
    Semantic Search has become an active research of Semantic Web in recent years. The classification methodology plays a pretty critical role in the beginning of search process to disambiguate irrelevant information. However, the applications related to Folksonomy suffer from many obstacles. This study attempts to eliminate the problems resulted from Folksonomy using existing semantic technology. We also focus on how to effectively integrate heterogeneous ontologies over the Internet to acquire the integrity of domain knowledge. A faceted logic layer is abstracted in order to strengthen category framework and organize existing available ontologies according to a series of steps based on the methodology of faceted classification and ontology construction. The result showed that our approach can facilitate the integration of inconsistent or even heterogeneous ontologies. This paper also generalizes the principles of picking appropriate facets with which our facet browser completely complies so that better semantic search result can be obtained.
  16. Bettencourt, N.; Silva, N.; Barroso, J.: Semantically enhancing recommender systems (2016) 0.00 
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    Abstract
    As the amount of content and the number of users in social relationships is continually growing in the Internet, resource sharing and access policy management is difficult, time-consuming and error-prone. Cross-domain recommendation of private or protected resources managed and secured by each domain's specific access rules is impracticable due to private security policies and poor sharing mechanisms. This work focus on exploiting resource's content, user's preferences, users' social networks and semantic information to cross-relate different resources through their meta information using recommendation techniques that combine collaborative-filtering techniques with semantics annotations, by generating associations between resources. The semantic similarities established between resources are used on a hybrid recommendation engine that interprets user and resources' semantic information. The recommendation engine allows the promotion and discovery of unknown-unknown resources to users that could not even know about the existence of those resources thus providing means to solve the cross-domain recommendation of private or protected resources.
  17. Efthimiadis, E.N.: End-users' understanding of thesaural knowledge structures in interactive query expansion (1994) 0.00 
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    Date
    30. 3.2001 13:35:22
  18. Chen, H.; Lally, A.M.; Zhu, B.; Chau, M.: HelpfulMed : Intelligent searching for medical information over the Internet (2003) 0.00 
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  19. Bergamaschi, S.; Domnori, E.; Guerra, F.; Rota, S.; Lado, R.T.; Velegrakis, Y.: Understanding the semantics of keyword queries on relational data without accessing the instance (2012) 0.00 
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    Abstract
    The birth of the Web has brought an exponential growth to the amount of the information that is freely available to the Internet population, overloading users and entangling their efforts to satisfy their information needs. Web search engines such Google, Yahoo, or Bing have become popular mainly due to the fact that they offer an easy-to-use query interface (i.e., based on keywords) and an effective and efficient query execution mechanism. The majority of these search engines do not consider information stored on the deep or hidden Web [9,28], despite the fact that the size of the deep Web is estimated to be much bigger than the surface Web [9,47]. There have been a number of systems that record interactions with the deep Web sources or automatically submit queries them (mainly through their Web form interfaces) in order to index their context. Unfortunately, this technique is only partially indexing the data instance. Moreover, it is not possible to take advantage of the query capabilities of data sources, for example, of the relational query features, because their interface is often restricted from the Web form. Besides, Web search engines focus on retrieving documents and not on querying structured sources, so they are unable to access information based on concepts.
  20. Bhansali, D.; Desai, H.; Deulkar, K.: ¬A study of different ranking approaches for semantic search (2015) 0.00 
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    Abstract
    Search Engines have become an integral part of our day to day life. Our reliance on search engines increases with every passing day. With the amount of data available on Internet increasing exponentially, it becomes important to develop new methods and tools that help to return results relevant to the queries and reduce the time spent on searching. The results should be diverse but at the same time should return results focused on the queries asked. Relation Based Page Rank [4] algorithms are considered to be the next frontier in improvement of Semantic Web Search. The probability of finding relevance in the search results as posited by the user while entering the query is used to measure the relevance. However, its application is limited by the complexity of determining relation between the terms and assigning explicit meaning to each term. Trust Rank is one of the most widely used ranking algorithms for semantic web search. Few other ranking algorithms like HITS algorithm, PageRank algorithm are also used for Semantic Web Searching. In this paper, we will provide a comparison of few ranking approaches.

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