Glossary
- Feature:
-
A characteristic property of a document. Usually, a document’s terms are used as features, but virtually every measurable document property can be chosen, such as word classes, average sentence lengths, principal components of term-document-occurrence matrices, or term synonyms.
- Information need:
-
Specifically here: A lack of information or knowledge that can be satisfied by a set of text documents.
- Query:
-
Specifically here: A small set of terms that expresses a user’s information need.
- Relevance:
-
The extent to which a document is capable to satisfy an information need. Within probabilistic retrieval models, relevance is modeled as a binary random variable.
Definition
A retrieval model provides a formal means to address (information) retrieval tasks with the aid of a computer.
Introduction
A retrieval task is given if an information need is to be satisfied by exploiting an information resource....
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References
Blei DM, Ng AY, Jordan MI (2003) Latent dirichlet allocation. J Mach Learn Res 3:993–1022
Deerwester S, Dumais S, Landauer T, Furnas G, Harshman R (1990) Indexing by latent semantic analysis. J Am Soc Inf Sci 41(6):391–407
Gabrilovich E, Markovitch S (2007) Computing semantic relatedness using Wikipedia-based explicit semantic analysis. In: IJCAI 2007, proceedings of the 20th international joint conference on artificial intelligence, Hyderabad, 6–12 Jan 2007, pp 1606–1611
Gurevych I, Hovy E, Slonim N, Stein B (2016) Debating technologies (Dagstuhl Seminar 15512). Dagstuhl Reports 5(12):18–46, doi: 10.4230/DagRep.5.12.18. URL http://drops.dagstuhl.de/opus/volltexte/2016/5803
Le QV, Mikolov T (2014) Distributed representations of sentences and documents. In: Proceedings of the 31th international conference on machine learning (ICML2014), Beijing, pp 1188–1196
Meyer zu Eißen S, Stein B, Potthast M (2005) The suffix tree document model revisited. In: Tochtermann K, Maurer H (eds) 5th international conference on knowledge management (IKNOW 05), Know-Center, Graz. Journal of Universal Computer Science, pp 596–603
Page L et al. (1999) The pagerank citation ranking: bringing order to the we
Ponte J, Croft W (1998) A language modeling approach to information retrieval. In: SIGIR’98: proceedings of the 21st annual international ACM SIGIR conference on research and development in information retrieval. ACM Press, New York, pp 275–281. doi:10.1145/290941.291008
Potthast M, Stein B, Anderka M (2008) A Wikipedia-based multilingual retrieval model. In: Macdonald C, Ounis I, Plachouras V, Ruthven I, White R (eds) Advances in information retrieval. 30th European conference on IR research (ECIR 08). Lecture notes in computer science, vol 4956. Springer, Berlin/Heidelberg/New York, pp 522–530
Robertson S (1997) The probability ranking principle in IR. Morgan Kaufmann Publishers, San Francisco
Robertson S, Sparck-Jones K (1976) Relevance weighting of search terms. J Am Soc Inf Sci 27(3):129–146
Robertson S, Walker S (1994) Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval. In: SIGIR’94: proceedings of the 17th annual international ACM SIGIR conference on research and development in information retrieval. Springer, New York, pp 232–241
Salton G, McGill M (1983) Introduction to modern information retrieval. McGraw-Hill, New York
Salton G, Wong A, Yang C (1975) A vector space model for automatic indexing. Commun ACM 18(11):613–620
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Stein, B., Gollub, T., Anderka, M. (2017). Retrieval Models. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7163-9_117-1
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DOI: https://doi.org/10.1007/978-1-4614-7163-9_117-1
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