MARKOF MODEL: A PROBABILITY MODEL FOR DISAMBIGUATION IN COMPUTATIONAL LINGUISTICS

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DAFTARINEZHAD E.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF HUMANITIES Year:2007 | Volume:16-17 | Issue:63-64 (SPECIAL ISSUE ON LINGUISTICS) Page(s): 107-139

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Title

MARKOF MODEL: A PROBABILITY MODEL FOR DISAMBIGUATION IN COMPUTATIONAL LINGUISTICS

Author(s)

DAFTARINEZHAD E. | Issue Writer Certificate

Keywords

LINGUISTICSQ2

MARKOFS PROCEDUREQ4

TAGGINGQ3

DISAMBIGUATIONQ3

TEXT SEGMENTATIONQ3

Abstract

One of the most important issues in language processing is the problem of ambiguity. In general, the systems developed for DISAMBIGUATION can be classified into two groups: rule-based and statistical. MARKOFS PROCEDURE is one of the statistical models for DISAMBIGUATION used frequently in linguistic studies in general, and in computational LINGUISTICS in particular. So far, this procedure has been one of the best methods for DISAMBIGUATION especially for parts of speech, in addition to automatic TAGGING of language corpora. In this paper, the methods of TAGGING and DISAMBIGUATION within the framework of Markof’s Model are described and then a simplified version of the formula based on the first edition of ' Constituent-Likelihood Automatic Word-tagging System' (CLAWS) which follows Markof’s procedure will be modeled. In this regard, two sample sentences are chosen, and then for each word or syntactic role, the frequency of occurrences and also its possible transfer from that word to the next one or from the syntactic role of that word to the syntactic role of the next one will be recorded in separate tables.The numeric value related to the multiplication of these numbers, that is, the computation of the probability in the structures of the two words and the sum of these probabilities is the basis of language analysis. The greater the number, the greater the possibilities of the tags found for the words to be correct in new sentences. If instead of the two sample sentences, we analyze the sentences of a language corpus using this method and record the probabilities of two or three - words structures in tables, then we can compute the sum of these probabilities and provide a computer program so as to tag and disambiguate different sentences.

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References

PROPOUNDING A NEW METHOD FOR THE IDENTIFICATION OF THE ORTHOGRAPHIC SYSTEM OF ENGLISH, FRENCH, FARSI, ARABIC AND TURKISH

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APA: Copy

DAFTARINEZHAD, E.. (2007). MARKOF MODEL: A PROBABILITY MODEL FOR DISAMBIGUATION IN COMPUTATIONAL LINGUISTICS. JOURNAL OF HUMANITIES, 16-17(63-64 (SPECIAL ISSUE ON LINGUISTICS)), 107-139. SID. https://sid.ir/paper/13809/en

Vancouver: Copy

DAFTARINEZHAD E.. MARKOF MODEL: A PROBABILITY MODEL FOR DISAMBIGUATION IN COMPUTATIONAL LINGUISTICS. JOURNAL OF HUMANITIES[Internet]. 2007;16-17(63-64 (SPECIAL ISSUE ON LINGUISTICS)):107-139. Available from: https://sid.ir/paper/13809/en

IEEE: Copy

E. DAFTARINEZHAD, “MARKOF MODEL: A PROBABILITY MODEL FOR DISAMBIGUATION IN COMPUTATIONAL LINGUISTICS,” JOURNAL OF HUMANITIES, vol. 16-17, no. 63-64 (SPECIAL ISSUE ON LINGUISTICS), pp. 107–139, 2007, [Online]. Available: https://sid.ir/paper/13809/en

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