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	<title>Natural Language Processing &#187; POS Tagging</title>
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		<title>Baum Welch Algorithm</title>
		<link>http://language.worldofcomputing.net/pos-tagging/baum-welch-algorithm.html</link>
		<comments>http://language.worldofcomputing.net/pos-tagging/baum-welch-algorithm.html#comments</comments>
		<pubDate>Mon, 21 Dec 2009 03:35:04 +0000</pubDate>
		<dc:creator>Robin</dc:creator>
				<category><![CDATA[POS Tagging]]></category>
		<category><![CDATA[Algorithms]]></category>

		<guid isPermaLink="false">http://language.worldofcomputing.net/?p=139</guid>
		<description><![CDATA[Baum-Welch Algorithm
Baum-Welch Algorithm, also known as forward-backword algorithm was invented by Leonard E. Baum and Lloyd R Welch. It is a special case of Estimation Maximization (EM) method. Baum-Welch algorithm is very effective to train a Markov model without using manually annotated corpora. 
Baum Welch algorithm works by assigning initial probabilities to all the parameters. [...]]]></description>
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		<title>Maximum Entropy</title>
		<link>http://language.worldofcomputing.net/pos-tagging/maximum-entropy.html</link>
		<comments>http://language.worldofcomputing.net/pos-tagging/maximum-entropy.html#comments</comments>
		<pubDate>Mon, 21 Dec 2009 03:26:49 +0000</pubDate>
		<dc:creator>Robin</dc:creator>
				<category><![CDATA[POS Tagging]]></category>

		<guid isPermaLink="false">http://language.worldofcomputing.net/?p=130</guid>
		<description><![CDATA[Maximum Entropy Tagging
Maximum Entropy Tagging aims to find a model with maximum entropy. The term, maximum entropy here means maximum randomness or minimum additional structure. It exploits some of the good properties of tranformation-based learning and Markov model tagging. It allows flexibility in cues used to disambiguate words. The outputs of the maximum entropy tagging [...]]]></description>
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		<title>Transformation Based Learning</title>
		<link>http://language.worldofcomputing.net/pos-tagging/transformation-based-learning.html</link>
		<comments>http://language.worldofcomputing.net/pos-tagging/transformation-based-learning.html#comments</comments>
		<pubDate>Thu, 17 Dec 2009 03:32:02 +0000</pubDate>
		<dc:creator>Robin</dc:creator>
				<category><![CDATA[POS Tagging]]></category>

		<guid isPermaLink="false">http://language.worldofcomputing.net/?p=123</guid>
		<description><![CDATA[What is Transformation-Based Learning? 
Transformation-based learning (TBL) is a rule-based algorithm for automatic tagging of parts-of-speech to the given text. TBL transforms one state to another using transformation rules in order to find the suitable tag for each word. TBL allows us to have linguistic knowledge in a readable form.  It extracts linguistic information [...]]]></description>
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		<title>Markov Models</title>
		<link>http://language.worldofcomputing.net/pos-tagging/markov-models.html</link>
		<comments>http://language.worldofcomputing.net/pos-tagging/markov-models.html#comments</comments>
		<pubDate>Wed, 16 Dec 2009 03:10:05 +0000</pubDate>
		<dc:creator>Robin</dc:creator>
				<category><![CDATA[POS Tagging]]></category>
		<category><![CDATA[HMM]]></category>
		<category><![CDATA[Markov Models]]></category>

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		<description><![CDATA[Markov Models: Overview
Morkov models extract linguistic knowledge automatically from the large corpora  and do POS tagging. Morkov models are alternatives for laborious and time-consuming manual tagging. 
Markov Property 
The name Markov model is derived from the term Markov property. Markov property is an assumption that allows the system to be analyzed.  According to [...]]]></description>
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		<title>Rule Based POS Tagging</title>
		<link>http://language.worldofcomputing.net/pos-tagging/rule-based-pos-tagging.html</link>
		<comments>http://language.worldofcomputing.net/pos-tagging/rule-based-pos-tagging.html#comments</comments>
		<pubDate>Wed, 16 Dec 2009 03:07:10 +0000</pubDate>
		<dc:creator>Robin</dc:creator>
				<category><![CDATA[POS Tagging]]></category>
		<category><![CDATA[rule based]]></category>

		<guid isPermaLink="false">http://language.worldofcomputing.net/?p=110</guid>
		<description><![CDATA[Rule-based Parts-Of-Speech Tagging
Rule-based part-of-speech tagging is the oldest approach that uses hand-written rules for tagging.  Rule based taggers depends on dictionary or lexicon to get possible tags for each word to be tagged. Hand-written rules are used to identify the correct tag when a word has more than one possible tag.  Disambiguation is [...]]]></description>
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