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know more,; opening up new perspectives by considering how a country or an actor. Brinker: Linguistische Textanalyse. By Nigel  .Q:

Why don’t strings appear in Natural Language Processing?

Natural Language Processing is typically done with Strings, e.g.

stochastic language models
inference with HMMs
…

Yet, most strings in software (web pages, RSS feeds,…) are represented by bytes. Or do we count letters as a special case of strings?
Am I missing a point or is this a misconception? I never considered this much before.

A:

Short answer:
No, you don’t count them as a special case.
Long answer:
These days, there are general purpose languages like Python/Ruby that make it easy to deal with both strings and bytes. Just write your code in the language you prefer. In Python, for instance,
‘utf-8’: ‘the answer is 42’
‘ascii’: ‘the answer is 42’

is equivalent to
‘the answer is 42’.encode(‘utf-8’)
‘the answer is 42’.decode(‘utf-8’)

and does exactly the same thing. There’s no need to classify the type of data you’re dealing with and worry about it all the time. This frees your mind for the more fun and higher-order stuff.

A:

Yes, you are missing a point. Don’t bother to worry about the subtle nuances of what’s a string and what’s not. Simply use the languages that have the construct you need. Java Strings, python dictionaries of strings, ruby hashes of strings, every language out there has an equivalent of string – in fact, every language has an equivalent of bytes – in fact, every language has an equivalent of numbers.
This is just a bit of pain you have to go through.

A:

No. Strings are not a special type of data. They are just as random as the other ones.
Often you can use text processing libraries in a generic way where anything that can be represented as a string is also a string.
(for example I wrote

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XIAP (X-linked inhibitor of apoptosis) is a potent inhibitor of apoptosis and is a major target of oncogenic growth factor signals. In the present study, we sought to determine whether XIAP was regulated by oncogenic growth factor signaling in breast cancer and to define the role of XIAP in breast cancer development. Using bioinformatic analysis and a human breast cancer expression array, we identified XIAP as a candidate proto-oncogene. RT-PCR revealed that the expression of XIAP in breast cancers was dependent on the activation of HER2 and the growth factor signal transduction pathways. The human XIAP promoter region was identified by PCR analysis of human genomic DNA and was cloned into a pGL3-basic luciferase reporter vector. With this vector, we demonstrated that the transcription activity of the promoter was growth factor and oncogenic-signal dependent, as with HER2. The minimal promoter region was located in the upstream of exon 1, which required functional AP1, SP1, and TPA-response elements. The function of the XIAP promoter was further
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(Reich, S. Linguistische Analyse von Texten [Verlag Suhrkamp, Frankfurt am Main 2000] (Brinker, K. Linguistische Textanalyse, Eine Einfuhrung in die Theorie [Suhrkamp, Trier 1996]. German Language and Linguistics (Brinker, K. : Linguistische Textanalyse.
use of relevant examples, the role of adverbs and the free. Brinker, Klaus 2000: Textanalyse, Methoden, Metaphorik und Text.
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