-
Poulakos, I.: ¬"Die Leute suchen immer dasselbe" (2001)
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- Date
- 18. 1.1997 12:15:22
-
Chang, C.-H.; Hsu, C.-C.: Customizable multi-engine search tool with clustering (1997)
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- Date
- 1. 8.1996 22:08:06
-
Hsieh-Yee, I.: ¬The retrieval power of selected search engines : how well do they address general reference questions and subject questions? (1998)
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- Date
- 25.12.1998 19:22:51
-
Fluhr, C.: Crosslingual access to photo databases (2012)
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- Date
- 17. 4.2012 14:25:22
- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
-
Chen, L.-C.: Next generation search engine for the result clustering technology (2012)
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- Date
- 17. 4.2012 15:22:11
- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
-
Kurzke, C.; Galle, M.; Bathelt, M.: WebAssistant : a user profile specific information retrieval assistant (1998)
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- Date
- 1. 8.1996 22:08:06
-
Jenkins, C.: Automatic classification of Web resources using Java and Dewey Decimal Classification (1998)
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- Date
- 1. 8.1996 22:08:06
-
Williamson, N.J.: Knowledge structures and the Internet : progress and prospects (2006)
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- Date
- 27.12.2008 15:56:22
- Source
- Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch
-
Hastik, C.; Schuster, A.; Knauerhase, A.: Wissenschaftliche Suchmaschinen : Usability Evaluation und Betrachtung des Suchverhaltens potentieller Nutzer (2009)
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- Date
- 23. 3.2009 14:49:22
-
Su, L.T.: ¬A comprehensive and systematic model of user evaluation of Web search engines : Il. An evaluation by undergraduates (2003)
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- Abstract
- This paper presents an application of the model described in Part I to the evaluation of Web search engines by undergraduates. The study observed how 36 undergraduate used four major search engines to find information for their own individual problems and how they evaluated these engines based an actual interaction with the search engines. User evaluation was based an 16 performance measures representing five evaluation criteria: relevance, efficiency, utility, user satisfaction, and connectivity. Non-performance (user-related) measures were also applied. Each participant searched his/ her own topic an all four engines and provided satisfaction ratings for system features and interaction and reasons for satisfaction. Each also made relevance judgements of retrieved items in relation to his/her own information need and participated in post-search Interviews to provide reactions to the search results and overall performance. The study found significant differences in precision PR1 relative recall, user satisfaction with output display, time saving, value of search results, and overall performance among the four engines and also significant engine by discipline interactions an all these measures. In addition, the study found significant differences in user satisfaction with response time among four engines, and significant engine by discipline interaction in user satisfaction with search interface. None of the four search engines dominated in every aspect of the multidimensional evaluation. Content analysis of verbal data identified a number of user criteria and users evaluative comments based an these criteria. Results from both quantitative analysis and content analysis provide insight for system design and development, and useful feedback an strengths and weaknesses of search engines for system improvement
- Date
- 24. 1.2004 18:27:22
- Footnote
- Teil I im selben Heft
-
Li, L.; Shang, Y.; Zhang, W.: Improvement of HITS-based algorithms on Web documents
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- Content
- Vgl.: http%3A%2F%2Fdelab.csd.auth.gr%2F~dimitris%2Fcourses%2Fir_spring06%2Fpage_rank_computing%2Fp527-li.pdf. Vgl. auch: http://www2002.org/CDROM/refereed/643/.
-
Rowlands, I.; Nicholas, D.; Williams, P.; Huntington, P.; Fieldhouse, M.; Gunter, B.; Withey, R.; Jamali, H.R.; Dobrowolski, T.; Tenopir, C.: ¬The Google generation : the information behaviour of the researcher of the future (2008)
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- Footnote
- Vgl. auch: Rowlands, I.: Google generation: issues in information literacy. In: http://www.lucis.me.uk/retrieval%20issues.pdf.
-
Huvila, I.: Affective capitalism of knowing and the society of search engine (2016)
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- Date
- 20. 1.2015 18:30:22
-
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)
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- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
-
Bouidghaghen, O.; Tamine, L.: Spatio-temporal based personalization for mobile search (2012)
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- Date
- 20. 4.2012 13:19:22
- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
-
Krüger, C.: Evaluation des WWW-Suchdienstes GERHARD unter besonderer Beachtung automatischer Indexierung (1999)
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- Pages
- I,46,III S
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Lehrke, C.: Architektur von Suchmaschinen : Googles Architektur, insb. Crawler und Indizierer (2005)
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Chaudiron, S.; Ihadjadene, M.: Studying Web search engines from a user perspective : key concepts and main approaches (2012)
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- Date
- 20. 4.2012 13:22:37
- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
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Baeza-Yates, R.; Boldi, P.; Castillo, C.: Generalizing PageRank : damping functions for linkbased ranking algorithms (2006)
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- Date
- 16. 1.2016 10:22:28
-
Next generation search engines : advanced models for information retrieval (2012)
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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.
Vert, S.: Extensions of Web browsers useful to knowledge workers. Chen, L.-C.: Next generation search engine for the result clustering technology. Biskri, I., L. Rompré: Using association rules for query reformulation. Habernal, I., M. Konopík u. O. Rohlík: Question answering. Grau, B.: Finding answers to questions, in text collections or Web, in open domain or specialty domains. Berri, J., R. Benlamri: Context-aware mobile search engine. Bouidghaghen, O., L. Tamine: Spatio-temporal based personalization for mobile search. Chaudiron, S., M. Ihadjadene: Studying Web search engines from a user perspective: key concepts and main approaches. Karaman, F.: Artificial intelligence enabled search engines (AIESE) and the implications. Lewandowski, D.: A framework for evaluating the retrieval effectiveness of search engines.
- Editor
- Jouis, C. u.a.
