Search (9 results, page 1 of 1)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × theme_ss:"Suchmaschinen"
  1. Horch, A.; Kett, H.; Weisbecker, A.: Semantische Suchsysteme für das Internet : Architekturen und Komponenten semantischer Suchmaschinen (2013) 0.04 
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    Abstract
    In der heutigen Zeit nimmt die Flut an Informationen exponentiell zu. In dieser »Informationsexplosion« entsteht täglich eine unüberschaubare Menge an neuen Informationen im Web: Beispielsweise 430 deutschsprachige Artikel bei Wikipedia, 2,4 Mio. Tweets bei Twitter und 12,2 Mio. Kommentare bei Facebook. Während in Deutschland vor einigen Jahren noch Google als nahezu einzige Suchmaschine beim Zugriff auf Informationen im Web genutzt wurde, nehmen heute die u.a. in Social Media veröffentlichten Meinungen und damit die Vorauswahl sowie Bewertung von Informationen einzelner Experten und Meinungsführer an Bedeutung zu. Aber wie können themenspezifische Informationen nun effizient für konkrete Fragestellungen identifiziert und bedarfsgerecht aufbereitet und visualisiert werden? Diese Studie gibt einen Überblick über semantische Standards und Formate, die Prozesse der semantischen Suche, Methoden und Techniken semantischer Suchsysteme, Komponenten zur Entwicklung semantischer Suchmaschinen sowie den Aufbau bestehender Anwendungen. Die Studie erläutert den prinzipiellen Aufbau semantischer Suchsysteme und stellt Methoden der semantischen Suche vor. Zudem werden Softwarewerkzeuge vorgestellt, mithilfe derer einzelne Funktionalitäten von semantischen Suchmaschinen realisiert werden können. Abschließend erfolgt die Betrachtung bestehender semantischer Suchmaschinen zur Veranschaulichung der Unterschiede der Systeme im Aufbau sowie in der Funktionalität.
    RSWK
    Suchmaschine / Semantic Web / Information Retrieval
    Suchmaschine / Information Retrieval / Ranking / Datenstruktur / Kontextbezogenes System
    Subject
    Suchmaschine / Semantic Web / Information Retrieval
    Suchmaschine / Information Retrieval / Ranking / Datenstruktur / Kontextbezogenes System
  2. Jindal, V.; Bawa, S.; Batra, S.: ¬A review of ranking approaches for semantic search on Web (2014) 0.01 
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    Abstract
    With ever increasing information being available to the end users, search engines have become the most powerful tools for obtaining useful information scattered on the Web. However, it is very common that even most renowned search engines return result sets with not so useful pages to the user. Research on semantic search aims to improve traditional information search and retrieval methods where the basic relevance criteria rely primarily on the presence of query keywords within the returned pages. This work is an attempt to explore different relevancy ranking approaches based on semantics which are considered appropriate for the retrieval of relevant information. In this paper, various pilot projects and their corresponding outcomes have been investigated based on methodologies adopted and their most distinctive characteristics towards ranking. An overview of selected approaches and their comparison by means of the classification criteria has been presented. With the help of this comparison, some common concepts and outstanding features have been identified.
    Source
    Information processing and management. 50(2014) no.2, S.416-425
  3. Roy, R.S.; Agarwal, S.; Ganguly, N.; Choudhury, M.: Syntactic complexity of Web search queries through the lenses of language models, networks and users (2016) 0.00 
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    Abstract
    Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication.
    Source
    Information processing and management. 52(2016) no.5, S.923-948
  4. Scholer, F.; Williams, H.E.; Turpin, A.: Query association surrogates for Web search (2004) 0.00 
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    Abstract
    Collection sizes, query rates, and the number of users of Web search engines are increasing. Therefore, there is continued demand for innovation in providing search services that meet user information needs. In this article, we propose new techniques to add additional terms to documents with the goal of providing more accurate searches. Our techniques are based an query association, where queries are stored with documents that are highly similar statistically. We show that adding query associations to documents improves the accuracy of Web topic finding searches by up to 7%, and provides an excellent complement to existing supplement techniques for site finding. We conclude that using document surrogates derived from query association is a valuable new technique for accurate Web searching.
    Source
    Journal of the American Society for Information Science and technology. 55(2004) no.7, S.637-650
  5. Gillitzer, B.: Yewno (2017) 0.00 
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    Date
    22. 2.2017 10:16:49
  6. Poynder, R.: Web research engines? (1996) 0.00 
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    Source
    Information world review. 1996, no.120, S.47-48
  7. Schwartz, C.: Web search engines (1998) 0.00 
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    Source
    Journal of the American Society for Information Science. 49(1998) no.11, S.973-982
  8. Pahlevi, S.M.; Kitagawa, H.: Conveying taxonomy context for topic-focused Web search (2005) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.2, S.173-188
  9. Vidinli, I.B.; Ozcan, R.: New query suggestion framework and algorithms : a case study for an educational search engine (2016) 0.00 
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    Source
    Information processing and management. 52(2016) no.5, S.733-752

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