-
Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015)
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- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22
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Hölzig, C.: Google spürt Grippewellen auf : Die neue Anwendung ist bisher auf die USA beschränkt (2008)
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- 3. 5.1997 8:44:22
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- Suchmaschinen
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Klein, H.: Web Content Mining (2004)
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- Abstract
- Web Mining - ein Schlagwort, das mit der Verbreitung des Internets immer öfter zu lesen und zu hören ist. Die gegenwärtige Forschung beschäftigt sich aber eher mit dem Nutzungsverhalten der Internetnutzer, und ein Blick in Tagungsprogramme einschlägiger Konferenzen (z.B. GOR - German Online Research) zeigt, dass die Analyse der Inhalte kaum Thema ist. Auf der GOR wurden 1999 zwei Vorträge zu diesem Thema gehalten, auf der Folgekonferenz 2001 kein einziger. Web Mining ist der Oberbegriff für zwei Typen von Web Mining: Web Usage Mining und Web Content Mining. Unter Web Usage Mining versteht man das Analysieren von Daten, wie sie bei der Nutzung des WWW anfallen und von den Servern protokolliert wenden. Man kann ermitteln, welche Seiten wie oft aufgerufen wurden, wie lange auf den Seiten verweilt wurde und vieles andere mehr. Beim Web Content Mining wird der Inhalt der Webseiten untersucht, der nicht nur Text, sondern auf Bilder, Video- und Audioinhalte enthalten kann. Die Software für die Analyse von Webseiten ist in den Grundzügen vorhanden, doch müssen die meisten Webseiten für die entsprechende Analysesoftware erst aufbereitet werden. Zuerst müssen die relevanten Websites ermittelt werden, die die gesuchten Inhalte enthalten. Das geschieht meist mit Suchmaschinen, von denen es mittlerweile Hunderte gibt. Allerdings kann man nicht davon ausgehen, dass die Suchmaschinen alle existierende Webseiten erfassen. Das ist unmöglich, denn durch das schnelle Wachstum des Internets kommen täglich Tausende von Webseiten hinzu, und bereits bestehende ändern sich der werden gelöscht. Oft weiß man auch nicht, wie die Suchmaschinen arbeiten, denn das gehört zu den Geschäftsgeheimnissen der Betreiber. Man muss also davon ausgehen, dass die Suchmaschinen nicht alle relevanten Websites finden (können). Der nächste Schritt ist das Herunterladen der Websites, dafür gibt es Software, die unter den Bezeichnungen OfflineReader oder Webspider zu finden ist. Das Ziel dieser Programme ist, die Website in einer Form herunterzuladen, die es erlaubt, die Website offline zu betrachten. Die Struktur der Website wird in der Regel beibehalten. Wer die Inhalte einer Website analysieren will, muss also alle Dateien mit seiner Analysesoftware verarbeiten können. Software für Inhaltsanalyse geht davon aus, dass nur Textinformationen in einer einzigen Datei verarbeitet werden. QDA Software (qualitative data analysis) verarbeitet dagegen auch Audiound Videoinhalte sowie internetspezifische Kommunikation wie z.B. Chats.
-
Search tools (1997)
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Baeza-Yates, R.; Hurtado, C.; Mendoza, M.: Improving search engines by query clustering (2007)
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Whittle, M.; Eaglestone, B.; Ford, N.; Gillet, V.J.; Madden, A.: Data mining of search engine logs (2007)
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Shi, X.; Yang, C.C.: Mining related queries from Web search engine query logs using an improved association rule mining model (2007)
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Liu, Y.; Zhang, M.; Cen, R.; Ru, L.; Ma, S.: Data cleansing for Web information retrieval using query independent features (2007)
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Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997)
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- Date
- 5. 4.1996 15:29:15
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- Information systems. 22(1997) nos.5/6, S.333-347
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Wiegmann, S.: Hättest du die Titanic überlebt? : Eine kurze Einführung in das Data Mining mit freier Software (2023)
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- Date
- 28. 1.2022 11:05:29
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Hofstede, A.H.M. ter; Proper, H.A.; Van der Weide, T.P.: Exploiting fact verbalisation in conceptual information modelling (1997)
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- Date
- 5. 4.1996 15:29:15
- Source
- Information systems. 22(1997) nos.5/6, S.349-385
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Budzik, J.; Hammond, K.J.; Birnbaum, L.: Information access in context (2001)
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Chowdhury, G.G.: Template mining for information extraction from digital documents (1999)
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- 2. 4.2000 18:01:22
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Keim, D.A.: Data Mining mit bloßem Auge (2002)
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Kruse, R.; Borgelt, C.: Suche im Datendschungel (2002)
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Wrobel, S.: Lern- und Entdeckungsverfahren (2002)
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Borgelt, C.; Kruse, R.: Unsicheres Wissen nutzen (2002)
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Cardie, C.: Empirical methods in information extraction (1997)
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Tiefschürfen in Datenbanken (2002)
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Bath, P.A.: Data mining in health and medical information (2003)
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