Computational detection of Uyghur multiword expressions

This paper describes some important properties of Uyghur multiword expressions (MWEs). MWEs are significantly difficult to handle in any languages for natural language processing. There are many sub-fields in natural language studies such as automatic word correction, sentence correction, sentence fragmentation, machine translation, bilingual MWEs alignment and text mining etc. In all these fields, it is very important to detect a word in a sentence correctly. By their structure, MWEs are very complex and difficult to be defined or identified properly. In general, MWEs consists of more than one word or phrases. In some cases, these words that create a MWE are written together as a single (compound) word, however sometimes these words are written separately as completely different words (non-compound) each other. In this paper, Uyghur MWEs are analyzed by their structure and some practical approaches suggested detecting them effectively at the initial stage. End of this paper, these approaches evaluated some scientific results and given some general for future studies.

[1]  Chao Wang,et al.  Chinese Syntactic Reordering for Statistical Machine Translation , 2007, EMNLP.

[2]  Runli Guo Proper name knowledge acquisition for text understanding , 2002 .

[3]  Takenobu Tokunaga,et al.  Proceedings of the ACL 2003 workshop on Multiword expressions: analysis, acquisition and treatment - Volume 18 , 2003 .

[4]  Kim-Teng Lua,et al.  The development of Tagged Uyghur Corpus , 2003, PACLIC.

[5]  Dawn Archer,et al.  Extracting Multiword Expressions with A Semantic Tagger , 2003, ACL 2003.

[6]  Richard Sproat,et al.  Morphology and computation , 1992 .

[7]  Magnus Merkel,et al.  Knowledge-lite extraction of multi-word units with language filters and entropy thresholds , 2000, RIAO.

[8]  Kemal Oflazer Two-level description of Turkish morphology , 1993 .

[9]  Dekang Lin,et al.  Automatic Identification of Non-compositional Phrases , 1999, ACL.

[10]  Kemal Oflazer,et al.  Name Tagging Using Lexical, Contextual, and Morphological Information , 2000 .

[11]  Frank Smadja,et al.  Retrieving Collocations from Text: Xtract , 1993, CL.

[12]  Kemal Oflazer,et al.  Two-level Description of Turkish Morphology , 1993, EACL.

[13]  Beatrice Daille,et al.  Combined approach for terminology extraction: lexical statistics and linguistic filtering , 1995 .

[14]  Kenneth Ward Church,et al.  Termight: Identifying and Translating Technical Terminology , 1994, ANLP.

[15]  Yusup Abaidula,et al.  The Research and Development of Computer Aided Contemporary Uighur Language Tagging System , 2005, J. Chin. Lang. Comput..

[16]  Murat Orhun,et al.  Rule Based Analysis of the Uyghur Nouns , 2009, Int. J. Asian Lang. Process..

[17]  Kemal Oflazer,et al.  Computer Analysis of the Turkmen Language Morphology , 2006, FinTAL.

[18]  Anthony McEnery,et al.  Corpus Linguistics by the Lune: A Festschrift for Geoffrey Leech , 2003 .

[19]  Gulila Altenbek Rule-based Person Name Recognition for Xinjiang Minority Languages , 2005, J. Chin. Lang. Comput..

[20]  Ilyas Cicekli,et al.  A Morphological Analyser for Crimean Tatar , 2001 .