Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Introduction to Teaching and Learning in Information Retrieval Kapitel lesen Erstes Kapitel lesen

2011 | OriginalPaper | Buchkapitel

3. Teaching IR: Curricular Considerations

verfasst von : Daniel Blank, Norbert Fuhr, Andreas Henrich, Thomas Mandl, Thomas Rölleke, Hinrich Schütze, Benno Stein

Erschienen in: Teaching and Learning in Information Retrieval

Verlag: Springer Berlin Heidelberg

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Information retrieval (IR) is nowadays accepted as an important topic in various disciplines. Information science, computer science, information systems, and library science are obvious candidates. But also in disciplines such as marketing, bioinformatics, or linguistics, IR topics are considered important and should be covered by respective curricula. For those who are teaching IR topics, this brings up serious questions: Which topics should be addressed in an IR course? Can one course serve the different target groups? What would be an appropriate set of IR courses to satisfy all potentially interested parties?
In this chapter, we try to provide a landscape giving hints with respect to the topics relevant for the different target groups. In fact, a single IR course will hardly satisfy the needs of all target groups. A coordinated set of smaller IR courses where each group can select an appropriate subset might be a solution. Another important aspect is practical exercises. An IR course has to integrate such exercises, and a huge variety of available tools and frameworks are useful in this respect. This chapter will exemplarily consider some of these tools and discuss their use in IR courses.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Fostering Student Engagement in an Online IR Course
Nächstes Kapitel Pedagogical Enhancements for Information Retrieval Courses
Fußnoten
1
http://​trec.​nist.​gov/​, last accessed: 2010-10-26.
 
2
http://​www.​clef-campaign.​org/​, last accessed: 2010-10-26.
 
4
See, e.g. http://​news.​google.​com/​, last accessed: 2010-10-26.
 
6
Middleton and Baeza-Yates (2007) give an overview and compare multiple search engine libraries. A list of links pointing to tools and libraries can also be found in the Teaching IRsubtree on the web site of FG-IR (http://​www.​fg-ir.​de, last accessed: 2010-10-26).
 
7
http://​lucene.​apache.​org/​, last accessed: 2010-10-26.
 
Literatur
Al-Maskari A, Sanderson M, Clough P (2007) The relationship between IR effectiveness measures and user satisfaction. In: Proceedings of the 30th annual international ACM SIGIR conference, Amsterdam, pp 773–774
Baeza-Yates R, Ribeiro-Neto B (1999) Modern information retrieval. Addison-Wesley, England
Bates MJ (1989) The design of browsing and berrypicking techniques for the online search interface. Online Inf Rev 13(5):407–424CrossRef
Bates MJ (1990) Where should the person stop and the information search interface start? Inf Process Manag 26(5):575–591MathSciNetCrossRef
Belew RK (2000) Finding out about: a cognitive perspective on search engine technology and the WWW. Cambridge University Press, Cambridge, UKMATH
Belkin NJ (1980) Anomalous states of knowledge as a basis for information retrieval. Can J Inf Sci 5:133–143
Brin S, Page L (1998) The anatomy of a large-scale hypertextual web search engine. Comput Netw ISDN Syst 30(1–7):107–117CrossRef
Buckley C, Lewit FA (1985) Optimization of inverted vector searches. In: Proceedings of the 8th annual international ACM SIGIR conference, Montréal, Québec, Canada, pp 97–110
Buckley C, Voorhees EM (2005) TREC: experiment and evaluation in information retrieval. Retrieval system evaluation. Digital libraries and electronic publishing series. MIT, Cambridge, MA, pp 53–75
Croft B (1995) What do people want from information retrieval? (the top 10 research issues for companies that use and sell IR systems). D-Lib Mag 1:5
Croft B, Lafferty J (2003) (eds) Language modeling for information retrieval. The information retrieval series, vol 13. Kluwer, Amsterdam
Croft B, Metzler D, Strohman T (2009) Search engines: information retrieval in practice. Pearson Higher Education, Old Tappan, NJ
Ellis D (1989) A behavioural approach to information retrieval system design. J Document 45(3):171–212CrossRef
Fernández-Luna JM, Huete JF, Macfarlane A, Efthimiadis EN (2009) Teaching and learning in information retrieval. Inf Retr 12(2):201–226CrossRef
Grossman DA, Frieder O (2004) Information retrieval: algorithms and heuristics. The information retrieval series, vol 15, 2nd edn. Springer, Dordrecht
Hearst MA (2009) Search user interfaces. Cambridge University Press, Cambridge
Ingwersen P (1992) Information retrieval interaction. Taylor Graham, London
Järvelin K, Kekäläinen J (2002) Cumulated gain-based evaluation of IR techniques. ACM Trans Inf Syst Security 20(4):422–446
Jurafsky D, Martin J (2008) Speech and language processing. Prentice Hall, Upper Saddle River, NJ
Kuhlthau CC (1988) Developing a model of the library search process: cognitive and affective aspects. Ref Quart 28(2):232–242
Lieberman H (1995) Letizia: an agent that assists Web browsing. In: International joint conference on artificial intelligence, Montréal, Québec, Canada, pp 924–929
Liu X, Croft BW (2004) Cluster-based retrieval using language models. In: Proceedings of the 27th annual international ACM SIGIR conference, Sheffield, UK, pp 186–193
Mandl T (2008) Recent developments in the evaluation of information retrieval systems: moving towards diversity and practical relevance. Informatica 32:27–38MATH
Manning CD, Schütze H (1999) Foundations of statistical natural language processing. MIT, Cambridge, MAMATH
Manning CD, Raghavan P, Schütze H (2008) Introduction to information retrieval. Cambridge University Press, Cambridge, MAMATHCrossRef
Melucci M, Hawking D (2006) Introduction: a perspective on web information retrieval. Inf Retr 9(2):119–122CrossRef
Moffat A, Zobel J, Hawking D (2005) Recommended reading for IR research students. SIGIR Forum 39(2):3–14CrossRef
Riggs KR (2002) Exploring IR with Unix tools. J Comput Sci Coll 17(4):179–194
Robertson S (2004) Understanding inverse document frequency: On theoretical arguments for idf. J Document 60(5):503–520CrossRef
Robertson S (2008) On the history of evaluation in IR. J Inf Sci 34(4):439–456CrossRef
Robertson SE, Sparck Jones K (1976) Relevance weighting of search terms. J Am Soc Inf Sci 27(3):129–146CrossRef
Robertson SE, Walker S, Jones S, Hancock-Beaulieu M, Gatford M (1994) Okapi at TREC-3. In: NIST Special Publication 500–226: Overview of the Third Text Retrieval Conference (TREC-3), pp 109–126
Rölleke T, Tsikrika T, Kazai G (2006) A general matrix framework for modelling information retrieval. Inf Process Manag 42(1):4–30MATHCrossRef
Salton G, Wong A, Yang CS (1975) A vector space model for automatic indexing. Commun ACM 18(11):613–620MATHCrossRef
Schaefer A, Jordan M, Klas C-P, Fuhr N (2005) Active support for query formulation in virtual digital libraries: a case study with DAFFODIL. In: 9th European conference on digital libraries, Vienna, Austria, pp 414–425
Shadbolt N, Berners-Lee T, Hall W (2006) The semantic web revisited. IEEE Intell Syst 21(3):96–101CrossRef
Shneiderman B (1998) Designing the user interface. Addison-Wesley, Boston, MA
Shneiderman B, Maes P (1997) Direct manipulation vs interface agents. ACM Interact 4(6):42–61CrossRef
Sparck Jones K, Willett P (eds) (1997) Readings in information retrieval. The Morgan Kaufmann series in multimedia information and systems. Morgan Kaufmann, San Francisco
Stein B (2007) Principles of hash-based text retrieval. In: Proceedings of the 30th annual international ACM SIGIR conference, Amsterdam, pp 527–534
Witten I, Moffat A, Bell T (1999) Managing gigabytes: compressing and indexing documents and images. Morgan Kaufmann, San Francisco
Wong SKM, Yao Y (1995) On modeling information retrieval with probabilistic inference. ACM Trans Inf Syst Security 13(1):38–68
Metadaten
Titel
Teaching IR: Curricular Considerations
verfasst von
Daniel Blank
Norbert Fuhr
Andreas Henrich
Thomas Mandl
Thomas Rölleke
Hinrich Schütze
Benno Stein
Copyright-Jahr
2011
Verlag
Springer Berlin Heidelberg
Buch
Teaching and Learning in Information Retrieval

Print ISBN: 978-3-642-22510-9

Electronic ISBN: 978-3-642-22511-6

Copyright-Jahr: 2011

DOI
https://doi.org/10.1007/978-3-642-22511-6_3

Neuer Inhalt

    Bildnachweise