Search (43 results, page 2 of 3)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × type_ss:"a"
  1. Rahmstorf, G.: Integriertes Management inhaltlicher Datenarten (2001) 0.01 
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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
  2. Arenas, M.; Cuenca Grau, B.; Kharlamov, E.; Marciuska, S.; Zheleznyakov, D.: Faceted search over ontology-enhanced RDF data (2014) 0.01 
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  3. Selvaretnam, B.; Belkhatir, M.: ¬A linguistically driven framework for query expansion via grammatical constituent highlighting and role-based concept weighting (2016) 0.01 
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  4. Wongthontham, P.; Abu-Salih, B.: Ontology-based approach for semantic data extraction from social big data : state-of-the-art and research directions (2018) 0.01 
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  5. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.01 
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    Date
    16.11.2008 16:22:48
  6. Zeng, M.L.; Gracy, K.F.; Zumer, M.: Using a semantic analysis tool to generate subject access points : a study using Panofsky's theory and two research samples (2014) 0.01 
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  7. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.01 
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    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
  8. Chen, H.; Lally, A.M.; Zhu, B.; Chau, M.: HelpfulMed : Intelligent searching for medical information over the Internet (2003) 0.01 
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  9. Koike, A.; Takagi, T.: Knowledge discovery based on an implicit and explicit conceptual network (2007) 0.01 
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    Abstract
    The amount of knowledge accumulated in published scientific papers has increased due to the continuing progress being made in scientific research. Since numerous papers have only reported fragments of scientific facts, there are possibilities for discovering new knowledge by connecting these facts. We therefore developed a system called BioTermNet to draft a conceptual network with hybrid methods of information extraction and information retrieval. Two concepts are regarded as related in this system if (a) their relationship is clearly described in MEDLINE abstracts or (b) they have distinctively co-occurred in abstracts. PRIME data, including protein interactions and functions extracted by NLP techniques, are used in the former, and the Singhalmeasure for information retrieval is used in the latter. Relationships that are not clearly or directly described in an abstract can be extracted by connecting multiple concepts. To evaluate how well this system performs, Swanson's association between Raynaud's disease and fish oil and that between migraine and magnesium were tested with abstracts that had been published before the discovery of these associations. The result was that when start and end concepts were given, plausible and understandable intermediate concepts connecting them could be detected. When only the start concept was given, not only the focused concept (magnesium and fish oil) but also other probable concepts could be detected as related concept candidates. Finally, this system was applied to find diseases related to the BRCA1 gene. Some other new potentially related diseases were detected along with diseases whose relations to BRCA1 were already known.
  10. Symonds, M.; Bruza, P.; Zuccon, G.; Koopman, B.; Sitbon, L.; Turner, I.: Automatic query expansion : a structural linguistic perspective (2014) 0.01 
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  11. Pal, D.; Mitra, M.; Datta, K.: Improving query expansion using WordNet (2014) 0.01 
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    Abstract
    This study proposes a new way of using WordNet for query expansion (QE). We choose candidate expansion terms from a set of pseudo-relevant documents; however, the usefulness of these terms is measured based on their definitions provided in a hand-crafted lexical resource such as WordNet. Experiments with a number of standard TREC collections WordNet-based that this method outperforms existing WordNet-based methods. It also compares favorably with established QE methods such as KLD and RM3. Leveraging earlier work in which a combination of QE methods was found to outperform each individual method (as well as other well-known QE methods), we next propose a combination-based QE method that takes into account three different aspects of a candidate expansion term's usefulness: (a) its distribution in the pseudo-relevant documents and in the target corpus, (b) its statistical association with query terms, and (c) its semantic relation with the query, as determined by the overlap between the WordNet definitions of the term and query terms. This combination of diverse sources of information appears to work well on a number of test collections, viz., TREC123, TREC5, TREC678, TREC robust (new), and TREC910 collections, and yields significant improvements over competing methods on most of these collections.
  12. Xu, B.; Lin, H.; Lin, Y.: Assessment of learning to rank methods for query expansion (2016) 0.01 
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  13. Adhikari, A.; Dutta, B.; Dutta, A.; Mondal, D.; Singh, S.: ¬An intrinsic information content-based semantic similarity measure considering the disjoint common subsumers of concepts of an ontology (2018) 0.01 
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  14. Kasprzik, A.; Kett, J.: Vorschläge für eine Weiterentwicklung der Sacherschließung und Schritte zur fortgesetzten strukturellen Aufwertung der GND (2018) 0.01 
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    Abstract
    Aufgrund der fortgesetzten Publikationsflut stellt sich immer dringender die Frage, wie die Schwellen für die Titel- und Normdatenpflege gesenkt werden können - sowohl für die intellektuelle als auch die automatisierte Sacherschließung. Zu einer Verbesserung der Daten- und Arbeitsqualität in der Sacherschließung kann beigetragen werden a) durch eine flexible Visualisierung der Gemeinsamen Normdatei (GND) und anderer Wissensorganisationssysteme, so dass deren Graphstruktur intuitiv erfassbar wird, und b) durch eine investigative Analyse ihrer aktuellen Struktur und die Entwicklung angepasster automatisierter Methoden zur Ermittlung und Korrektur fehlerhafter Muster. Die Deutsche Nationalbibliothek (DNB) prüft im Rahmen des GND-Entwicklungsprogramms 2017-2021, welche Bedingungen für eine fruchtbare community-getriebene Open-Source-Entwicklung entsprechender Werkzeuge gegeben sein müssen. Weiteres Potential steckt in einem langfristigen Übergang zu einer Darstellung von Titel- und Normdaten in Beschreibungssprachen im Sinne des Semantic Web (RDF; OWL, SKOS). So profitiert die GND von der Interoperabilität mit anderen kontrollierten Vokabularen und von einer erleichterten Interaktion mit anderen Fach-Communities und kann umgekehrt auch außerhalb des Bibliothekswesens zu einem noch attraktiveren Wissensorganisationssystem werden. Darüber hinaus bieten die Ansätze aus dem Semantic Web die Möglichkeit, stärker formalisierte, strukturierende Satellitenvokabulare rund um die GND zu entwickeln. Daraus ergeben sich nicht zuletzt auch neue Perspektiven für die automatisierte Sacherschließung. Es wäre lohnend, näher auszuloten, wie und inwieweit semantisch-logische Verfahren den bestehenden Methodenmix bereichern können.
  15. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.01 
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    Date
    22. 2.1996 13:14:10
  16. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.01 
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    Date
    22. 3.2003 19:35:46
  17. Brandão, W.C.; Santos, R.L.T.; Ziviani, N.; Moura, E.S. de; Silva, A.S. da: Learning to expand queries using entities (2014) 0.01 
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    Date
    22. 8.2014 17:07:50
  18. Efthimiadis, E.N.: Interactive query expansion : a user-based evaluation in a relevance feedback environment (2000) 0.01 
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    Abstract
    A user-centered investigation of interactive query expansion within the context of a relevance feedback system is presented in this article. Data were collected from 25 searches using the INSPEC database. The data collection mechanisms included questionnaires, transaction logs, and relevance evaluations. The results discuss issues that relate to query expansion, retrieval effectiveness, the correspondence of the on-line-to-off-line relevance judgments, and the selection of terms for query expansion by users (interactive query expansion). The main conclusions drawn from the results of the study are that: (1) one-third of the terms presented to users in a list of candidate terms for query expansion was identified by the users as potentially useful for query expansion. (2) These terms were mainly judged as either variant expressions (synonyms) or alternative (related) terms to the initial query terms. However, a substantial portion of the selected terms were identified as representing new ideas. (3) The relationships identified between the five best terms selected by the users for query expansion and the initial query terms were that: (a) 34% of the query expansion terms have no relationship or other type of correspondence with a query term; (b) 66% of the remaining query expansion terms have a relationship to the query terms. These relationships were: narrower term (46%), broader term (3%), related term (17%). (4) The results provide evidence for the effectiveness of interactive query expansion. The initial search produced on average three highly relevant documents; the query expansion search produced on average nine further highly relevant documents. The conclusions highlight the need for more research on: interactive query expansion, the comparative evaluation of automatic vs. interactive query expansion, the study of weighted Webbased or Web-accessible retrieval systems in operational environments, and for user studies in searching ranked retrieval systems in general
  19. Koopman, B.; Zuccon, G.; Bruza, P.; Sitbon, L.; Lawley, M.: Information retrieval as semantic inference : a graph Inference model applied to medical search (2016) 0.01 
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  20. Bradford, R.B.: Relationship discovery in large text collections using Latent Semantic Indexing (2006) 0.01 
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    Source
    Proceedings of the Fourth Workshop on Link Analysis, Counterterrorism, and Security, SIAM Data Mining Conference, Bethesda, MD, 20-22 April, 2006. [http://www.siam.org/meetings/sdm06/workproceed/Link%20Analysis/15.pdf]

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