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Techniques for automatic normalizati...

Blum, Yakov Peretz.

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Techniques for automatic normalization of orthographically variant Yiddish texts.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Techniques for automatic normalization of orthographically variant Yiddish texts./
作者:	Blum, Yakov Peretz.
面頁冊數:	49 p.
附註:	Source: Masters Abstracts International, Volume: 54-03.
Contained By:	Masters Abstracts International54-03(E).
標題:	Linguistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1584235
ISBN:	9781321573305

Techniques for automatic normalization of orthographically variant Yiddish texts.
Blum, Yakov Peretz.

Techniques for automatic normalization of orthographically variant Yiddish texts. - 49 p.

Source: Masters Abstracts International, Volume: 54-03.

Thesis (M.A.)--City University of New York, 2015.

Yiddish is characterized by a multitude of orthographic systems. A number of approaches to automatic normalization of variant orthography have been explored for the processing of historic texts of languages whose orthography has since been standardized. However, these approaches have not yet been applied to Yiddish.

ISBN: 9781321573305Subjects--Topical Terms:

524476
Linguistics.

Techniques for automatic normalization of orthographically variant Yiddish texts.
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245 1 0 $a Techniques for automatic normalization of orthographically variant Yiddish texts.
300 $a 49 p.
500 $a Source: Masters Abstracts International, Volume: 54-03.
500 $a Adviser: Martin Chodorow.
502 $a Thesis (M.A.)--City University of New York, 2015.
520 $a Yiddish is characterized by a multitude of orthographic systems. A number of approaches to automatic normalization of variant orthography have been explored for the processing of historic texts of languages whose orthography has since been standardized. However, these approaches have not yet been applied to Yiddish.
520 $a Using a manually normalized set of 16 Yiddish documents as a training and test corpus, four techniques for automatic normalization were compared: a hand-crafted set of transformation rules, an off-the-shelf spell checker, edit distance minimization with manually set weights, and edit distance minimization with weights learned through a training set.
520 $a Performance was evaluated by calculating the proportion of correctly normalized words in a test set, and by measuring precision and recall in a test of information retrieval.
520 $a For the given test corpus, normalization by minimization of edit distance with multi-character edit operations and learned weights was found to perform best in all tests.
590 $a School code: 0046.
650 4 $a Linguistics. $3 524476
650 4 $a Information science. $3 554358
650 4 $a Judaic studies. $3 2144743
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710 2 $a City University of New York. $b Linguistics. $3 1022754
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792 $a 2015
793 $a English
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