Recent research has shown that the navigability of tagging systems leaves much to be desired. In general, it was observed that tagging systems are not navigable if the resource lists of the tagging system are limited to a certain factor k. Hence, in this paper a novel resource list generation approach is introduced that addresses this issue. The proposed approach is based on a hierarchical netw...

Accurate part-of-speech (POS) tagging of natural language text data can add power to automated information retrieval and extraction. Brill's transformation-based learning (TBL) approach to automated POS tagging was introduced in 1992, combining virtues of rule-based and stochastic methods. Brill's innovative idea was to use machine learning techniques to search through all of rule space for the...

How to deal with part of speech (POS) tagging is a very important problem when we build a syntactic parsing system. We could preprocess the text with a POS tagger before perform parsing in a pipelined approach. Alternatively, we could perform POS tagging and parsing simultaneously in an integrated approach. Few, if any, comparisons have been made on such architecture issues for Chinese parsing....

We proposed a subword-based tagging for Chinese word segmentation to improve the existing character-based tagging. The subword-based tagging was implemented using the maximum entropy (MaxEnt) and the conditional random fields (CRF) methods. We found that the proposed subword-based tagging outperformed the character-based tagging in all comparative experiments. In addition, we proposed a confide...

Abstract Background With the increase in telemetry studies over past decade, improving understanding of how different tagging methods influence probability presence a receiver array is important maximizing resulting data. Disappearance from may be due to mortality surgery complications, tag loss, predation, or emigration. Internally fish on boat can cause barotrauma injuries, increased stress p...

Sparsity is one of the major problems in natural language processing. The problem becomes even more severe in agglutinating languages that are highly prone to be inflected. We deal with sparsity in Turkish by adopting morphological features for part-of-speech tagging. We learn inflectional and derivational morpheme tags in Turkish by using conditional random fields (CRF) and we employ the morph...

Many approaches to Part-of-Speech tagging have reached accuracy about 96-97% which is close to the upper bound, and little improvement was made in recent years. In this project, we propose an idea of increasing tagging accuracy by learning the di erence of results of multiple taggers. Since the errors of di erent taggers might be complementary, we can avoid some of them by using di erent tagger...