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oapen-20.500.12657-237162024-03-22T19:23:05Z Chapter Dependency-sensitive typological distance Hammarström, Harald O’Connor, Loretta Saxena, Anju Borin, Lars linguistics linguistic differences thema EDItEUR::C Language and Linguistics::CF Linguistics In this paper, we will develop two kinds of dependency-sensitive distance metrics. The first captures the idea that if it can be shown that one feature can be (partly) predicted by another, then the predictable feature should be (partly) “discounted”. This strategy tackles dependencies between features as a whole, not between specific values of features. The second dependency-sensitive metric addresses the significance of similarities between specific values of features. Globally, a specific combination of values may be very predictable, or, on the other end of the scale, a combination of values may be extremely unusual. Accordingly, when comparing two specific languages, scores may be weighted as to whether they share something predictable or something quirky. 2019-11-19 23:55 2020-01-07 16:47:06 2020-04-01T09:26:44Z 2020-04-01T09:26:44Z 2013 chapter 1006428 OCN: 1135848635 9783110488081 http://library.oapen.org/handle/20.500.12657/23716 eng application/pdf n/a 22_[9783110305258 - Approaches ] Dependency.pdf De Gruyter Approaches to Measuring Linguistic Differences 10.1515/9783110305258.329 10.1515/9783110305258.329 2b386f62-fc18-4108-bcf1-ade3ed4cf2f3 d344d431-123c-48b3-94be-c8d10c495b20 7292b17b-f01a-4016-94d3-d7fb5ef9fb79 9783110488081 European Research Council (ERC) Berlin/Boston 230310 FP7 Ideas: European Research Council FP7-IDEAS-ERC - Specific Programme: "Ideas" Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013) open access
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OAPEN
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DSpace
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English
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In this paper, we will develop two kinds of dependency-sensitive distance metrics. The first captures the idea that if it can be shown that one feature can be (partly) predicted by another, then the predictable feature should be (partly) “discounted”. This strategy tackles dependencies between features as a whole, not between specific values of features. The second dependency-sensitive metric addresses the significance of similarities between specific values of features. Globally, a specific combination of values may be very predictable, or, on the other end of the scale, a combination of values may be extremely unusual. Accordingly, when comparing two specific languages, scores may be weighted as to whether they share something predictable or something quirky.
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22_[9783110305258 - Approaches ] Dependency.pdf
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| spellingShingle |
22_[9783110305258 - Approaches ] Dependency.pdf
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| title_short |
22_[9783110305258 - Approaches ] Dependency.pdf
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| title_full |
22_[9783110305258 - Approaches ] Dependency.pdf
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| title_fullStr |
22_[9783110305258 - Approaches ] Dependency.pdf
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| title_full_unstemmed |
22_[9783110305258 - Approaches ] Dependency.pdf
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| title_sort |
22_[9783110305258 - approaches ] dependency.pdf
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De Gruyter
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2019
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1799945208525225984
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