@techreport{
 title = {Towards combining rule-based and statistical part of speech tagging in agglutinative languages},
 type = {techreport},
 year = {2007},
 source = {Computer engineering},
 volume = {1},
 issue = {1},
 id = {4ef9a84d-1641-3d3f-92cb-12d791197a23},
 created = {2019-10-12T11:01:01.071Z},
 accessed = {2019-10-12},
 file_attached = {true},
 profile_id = {1971c810-6732-3a00-9f6b-d217e1a53071},
 group_id = {cbcfbfec-195f-3b99-b6a1-d26e1dd80ff5},
 last_modified = {2019-10-12T11:01:01.147Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {We present a composite part of speech tagger for Turkish which combines the rule-based and statistical approaches. The tagger makes use of word frequencies and n-gram statistics from a corpus. We use the output of a morphological analyzer in order to get more accurate results and also to eliminate the sparse data problem. In addition, we employ a heuristics about the position of words in the sentences. Although the experiments have been performed on a very small corpus, the results have shown that the use of a composite approach and heuristics improves the accuracy of the tagger. Keywords: agglutinative language, part of speech tagger, rule-based and statistical method},
 bibtype = {techreport},
 author = {Altunyurt, Levent and Orhan, Zihni and Güngör, Tunga}
}

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