Paper Info
Title
The Comparative Research on the Segmentation Strategies of Tibetan Bounded-Variant Forms
Abstract
The segmentation of Tibetan bounded-variant forms (TBVFS) is one of the most foundational tasks in text processing and the segmenting results directly influence the word segmentation, portaging, syntactic parsing and the Named Entity Extraction and so on. At present, the segmenting results are unsatisfactory and cannot be applied in practice. In this article, authors firstly describe the features of TBVFS, their distributions and then test the segmenting results by using two different segmentation strategies and conclude that Statistics-based methods for morpheme position tagging is better than Rule-based methods. If some rules are used to adjust a part of mistaken segmentations in the post processing, this kind of segmentation problem can be resolved.
Year
DOI
Venue
2013
10.1109/IALP.2013.75
IALP
Keywords
Field
DocType
post processing,statistics-based methods,entity extraction,tibetan,segmentation strategies,statistical analysis,tibetan bounded-variant forms,tbvfs segmentation strategies,bounded-variant forms,named entity extraction,comparative research,rule-based method,tibetan bounded-variant form,text processing,word segmentation,portaging,mistaken segmentation,segmentation problem,natural language processing,syntactic parsing,different segmentation strategy,text analysis,tibetan bounded-variant form segmentation strategies,morpheme position tagging,statistics-based method
Morpheme,Market segmentation,Scale-space segmentation,Pattern recognition,Computer science,Segmentation,Segmentation-based object categorization,Text segmentation,Natural language processing,Artificial intelligence,Bounded function,Text processing
Conference
Citations 
PageRank 
References 
2
0.58
2
Authors
3
Name
Order
Citations
PageRank
Congjun Long184.67
Caijun Kang271.26
Di Jiang372.28