Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgements

Cramer I, Wandmacher T, Waltinger U (2012)
In: Modeling, Learning and Processing of Text Technological Data Structures. Mehler A, Henning Lobin and Harald Lüngen and K-UK, Storrer A, Witt A (Eds); Studies in Computational Intelligence, 370. Berlin/New York: Springer: 377-396.

Sammelwerksbeitrag | Veröffentlicht | Englisch
 
Download
Es wurden keine Dateien hochgeladen. Nur Publikationsnachweis!
Autor*in
Cramer, Irene; Wandmacher, Tonio; Waltinger, UlliUniBi
Herausgeber*in
Mehler, Alexander; Henning Lobin and Harald Lüngen and, Kai-Uwe Kühnberger; Storrer, Angelika; Witt, Andreas
Abstract / Bemerkung
In the past decade various semantic relatedness, similarity, and distance measures have been proposed which play a crucial role in many NLP-applications. Researchers compete for better algorithms (and resources to base the algorithms on), and often only few percentage points seem to suffice in order to prove a new measure (or resource) more accurate than an older one. However, it is still unclear which of them performs best under what conditions. In this work we therefore present a study comparing various relatedness measures. We evaluate them on the basis of a human judgment experiment and also examine several practical issues, such as run time and coverage. We show that the performance of all measures - as compared to human estimates - is still mediocre and argue that the definition of a shared task might bring us considerably closer to results of high quality.
Erscheinungsjahr
2012
Buchtitel
Modeling, Learning and Processing of Text Technological Data Structures
Serientitel
Studies in Computational Intelligence
Band
370
Seite(n)
377-396
ISBN
978-3-642-22612-0, 978-3-642-22613-7
Page URI
https://pub.uni-bielefeld.de/record/2144379

Zitieren

Cramer I, Wandmacher T, Waltinger U. Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgements. In: Mehler A, Henning Lobin and Harald Lüngen and K-UK, Storrer A, Witt A, eds. Modeling, Learning and Processing of Text Technological Data Structures. Studies in Computational Intelligence. Vol 370. Berlin/New York: Springer; 2012: 377-396.
Cramer, I., Wandmacher, T., & Waltinger, U. (2012). Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgements. In A. Mehler, K. - U. K. Henning Lobin and Harald Lüngen and, A. Storrer, & A. Witt (Eds.), Studies in Computational Intelligence: Vol. 370. Modeling, Learning and Processing of Text Technological Data Structures (pp. 377-396). Berlin/New York: Springer. https://doi.org/10.1007/978-3-642-22613-7_18
Cramer, Irene, Wandmacher, Tonio, and Waltinger, Ulli. 2012. “Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgements”. In Modeling, Learning and Processing of Text Technological Data Structures, ed. Alexander Mehler, Kai-Uwe Kühnberger Henning Lobin and Harald Lüngen and, Angelika Storrer, and Andreas Witt, 370:377-396. Studies in Computational Intelligence. Berlin/New York: Springer.
Cramer, I., Wandmacher, T., and Waltinger, U. (2012). “Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgements” in Modeling, Learning and Processing of Text Technological Data Structures, Mehler, A., Henning Lobin and Harald Lüngen and, K. - U. K., Storrer, A., and Witt, A. eds. Studies in Computational Intelligence, vol. 370, (Berlin/New York: Springer), 377-396.
Cramer, I., Wandmacher, T., & Waltinger, U., 2012. Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgements. In A. Mehler, et al., eds. Modeling, Learning and Processing of Text Technological Data Structures. Studies in Computational Intelligence. no.370 Berlin/New York: Springer, pp. 377-396.
I. Cramer, T. Wandmacher, and U. Waltinger, “Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgements”, Modeling, Learning and Processing of Text Technological Data Structures, A. Mehler, et al., eds., Studies in Computational Intelligence, vol. 370, Berlin/New York: Springer, 2012, pp.377-396.
Cramer, I., Wandmacher, T., Waltinger, U.: Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgements. In: Mehler, A., Henning Lobin and Harald Lüngen and, K.-U.K., Storrer, A., and Witt, A. (eds.) Modeling, Learning and Processing of Text Technological Data Structures. Studies in Computational Intelligence. 370, p. 377-396. Springer, Berlin/New York (2012).
Cramer, Irene, Wandmacher, Tonio, and Waltinger, Ulli. “Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgements”. Modeling, Learning and Processing of Text Technological Data Structures. Ed. Alexander Mehler, Kai-Uwe Kühnberger Henning Lobin and Harald Lüngen and, Angelika Storrer, and Andreas Witt. Berlin/New York: Springer, 2012.Vol. 370. Studies in Computational Intelligence. 377-396.
Material in PUB:
Teil von PUB Eintrag
Modeling, learning, and processing of text-technological data structures
Mehler A, Kühnberger K-U, Lobin H, Lüngen H, Storrer A, Witt A (Eds) (2011) Studies in computational intelligence; 370.
Berlin: Springer.
Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Suchen in

Google Scholar
ISBN Suche