Search (25 results, page 1 of 2)

  • × theme_ss:"Suchmaschinen"
  • × year_i:[2010 TO 2020}
  1. Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015) 0.08 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22
    Theme
    Data Mining
  2. Sleem-Amer, M.; Bigorgne, I.; Brizard, S.; Santos, L.D.P.D.; Bouhairi, Y. El; Goujon, B.; Lorin, S.; Martineau, C.; Rigouste, L.; Varga, L.: Intelligent semantic search engines for opinion and sentiment mining (2012) 0.03 
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    Abstract
    Over the last years, research and industry players have become increasingly interested in analyzing opinions and sentiments expressed on the social media web for product marketing and business intelligence. In order to adapt to this need search engines not only have to be able to retrieve lists of documents but to directly access, analyze, and interpret topics and opinions. This article covers an intermediate phase of the ongoing industrial research project 'DoXa' aiming at developing a semantic opinion and sentiment mining search engine for the French language. The DoXa search engine enables topic related opinion and sentiment extraction beyond positive and negative polarity using rich linguistic resources. Centering the work on two distinct business use cases, the authors analyze both unstructured Web 2.0 contents (e.g., blogs and forums) and structured questionnaire data sets. The focus is on discovering hidden patterns in the data. To this end, the authors present work in progress on opinion topic relation extraction and visual analytics, linguistic resource construction as well as the combination of OLAP technology with semantic search.
  3. Next generation search engines : advanced models for information retrieval (2012) 0.02 
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    Content
    Enthält die Beiträge: Das, A., A. Jain: Indexing the World Wide Web: the journey so far. Ke, W.: Decentralized search and the clustering paradox in large scale information networks. Roux, M.: Metadata for search engines: what can be learned from e-Sciences? Fluhr, C.: Crosslingual access to photo databases. Djioua, B., J.-P. Desclés u. M. Alrahabi: Searching and mining with semantic categories. Ghorbel, H., A. Bahri u. R. Bouaziz: Fuzzy ontologies building platform for Semantic Web: FOB platform. Lassalle, E., E. Lassalle: Semantic models in information retrieval. Berry, M.W., R. Esau u. B. Kiefer: The use of text mining techniques in electronic discovery for legal matters. Sleem-Amer, M., I. Bigorgne u. S. Brizard u.a.: Intelligent semantic search engines for opinion and sentiment mining. Hoeber, O.: Human-centred Web search.
    LCSH
    Data mining
    Subject
    Data mining
  4. Clewley, N.; Chen, S.Y.; Liu, X.: Cognitive styles and search engine preferences : field dependence/independence vs holism/serialism (2010) 0.02 
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    Abstract
    Purpose - Cognitive style has been identified to be significantly influential in deciding users' preferences of search engines. In particular, Witkin's field dependence/independence has been widely studied in the area of web searching. It has been suggested that this cognitive style has conceptual links with the holism/serialism. This study aims to investigate the differences between the field dependence/independence and holism/serialism. Design/methodology/approach - An empirical study was conducted with 120 students from a UK university. Riding's cognitive style analysis (CSA) and Ford's study preference questionnaire (SPQ) were used to identify the students' cognitive styles. A questionnaire was designed to identify users' preferences for the design of search engines. Data mining techniques were applied to analyse the data obtained from the empirical study. Findings - The results highlight three findings. First, a fundamental link is confirmed between the two cognitive styles. Second, the relationship between field dependent users and holists is suggested to be more prominent than that of field independent users and serialists. Third, the interface design preferences of field dependent and field independent users can be split more clearly than those of holists and serialists. Originality/value - The contributions of this study include a deeper understanding of the similarities and differences between field dependence/independence and holists/serialists as well as proposing a novel methodology for data analyses.
  5. Lewandowski, D.: Query understanding (2011) 0.01 
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    Date
    18. 9.2018 18:22:18
  6. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.01 
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    Date
    17.12.2013 11:02:22
  7. Tober, M.; Hennig, L.; Furch, D.: SEO Ranking-Faktoren und Rang-Korrelationen 2014 : Google Deutschland (2014) 0.01 
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    Date
    13. 9.2014 14:45:22
  8. Schaat, S.: Von der automatisierten Manipulation zur Manipulation der Automatisierung (2019) 0.01 
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    Date
    19. 2.2019 17:22:00
  9. Mandalka, M.: Open semantic search zum unabhängigen und datenschutzfreundlichen Erschliessen von Dokumenten (2015) 0.01 
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    Content
    Automatische Texterkennung (OCR) Dokumente, die nicht im Textformat, sondern als Grafiken vorliegen, wie z.B. Scans werden automatisch durch automatische Texterkennung (OCR) angereichert und damit auch der extrahierte Text durchsuchbar. Auch für eingebettete Bilddateien bzw. Scans innerhalb von PDF-Dateien. Unscharfe Suche mit Listen Ansonsten ist auch das Recherche-Tool bzw. die Such-Applikation "Suche mit Listen" integriert, mit denen sich schnell und komfortabel abgleichen lässt, ob es zu den einzelnen Einträgen in Listen jeweils Treffer in der durchsuchbaren Dokumentensammlung gibt. Mittels unscharfer Suche findet das Tool auch Ergebnisse, die in fehlerhaften oder unterschiedlichen Schreibweisen vorliegen. Semantische Suche und Textmining Im Recherche, Textanalyse und Document Mining Tutorial zu den enthaltenen Recherche-Tools und verschiedenen kombinierten Methoden zur Datenanalyse, Anreicherung und Suche wird ausführlicher beschrieben, wie auch eine große heterogene und unstrukturierte Dokumentensammlung bzw. eine grosse Anzahl von Dokumenten in verschiedenen Formaten leicht durchsucht und analysiert werden kann.
  10. Fluhr, C.: Crosslingual access to photo databases (2012) 0.01 
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    Date
    17. 4.2012 14:25:22
  11. Chen, L.-C.: Next generation search engine for the result clustering technology (2012) 0.01 
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    Date
    17. 4.2012 15:22:11
  12. Bouidghaghen, O.; Tamine, L.: Spatio-temporal based personalization for mobile search (2012) 0.01 
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    Date
    20. 4.2012 13:19:22
  13. Lewandowski, D.: ¬Die Macht der Suchmaschinen und ihr Einfluss auf unsere Entscheidungen (2014) 0.01 
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    Date
    22. 9.2014 18:54:11
  14. Huvila, I.: Affective capitalism of knowing and the society of search engine (2016) 0.01 
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    Date
    20. 1.2015 18:30:22
  15. Chaudiron, S.; Ihadjadene, M.: Studying Web search engines from a user perspective : key concepts and main approaches (2012) 0.01 
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    Date
    20. 4.2012 13:22:37
  16. Lewandowski, D.; Spree, U.: Ranking of Wikipedia articles in search engines revisited : fair ranking for reasonable quality? (2011) 0.01 
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    Date
    30. 9.2012 19:27:22
  17. Aloteibi, S.; Sanderson, M.: Analyzing geographic query reformulation : an exploratory study (2014) 0.01 
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    Date
    26. 1.2014 18:48:22
  18. Alqaraleh, S.; Ramadan, O.; Salamah, M.: Efficient watcher based web crawler design (2015) 0.01 
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    20. 1.2015 18:30:22
  19. epd: Kaiserslauterer Forscher untersuchen Google-Suche (2017) 0.01 
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    Date
    22. 7.2004 9:42:33
  20. Lewandowski, D.; Sünkler, S.: What does Google recommend when you want to compare insurance offerings? (2019) 0.01 
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    Date
    20. 1.2015 18:30:22

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