[Corpora-List] Deviations in language models on the web

Wed Nov 17 00:05:18 UTC 2010

Fair point, but then how do you distinguish between what is and what is not valid content for the purposes of filtering spam?
Using a "content model"? :-)

Justin Washtell
University of Leeds

________________________________________
From: corpora-bounces at uib.no [corpora-bounces at uib.no] On Behalf Of Oliver Mason [O.Mason at bham.ac.uk]
Sent: 16 November 2010 23:20
To: Adam Kilgarriff
Cc: CORPORA at UIB.NO
Subject: Re: [Corpora-List] Deviations in language models on the web

I would think that if a comprehensive model of text structure can at
some point be created, then it would not be possible (or at least very
hard) to generate 'random' texts, as they'd be incoherent. Generating
a 'proper' text would require a lot of input (or content) that would
have to be used for language generation. Though my usage of 'language
model on text level' here is probably different from what some other
people in this thread understand by it! And I think we're still years
away from such a model.

Best,
Oliver

On 16 November 2010 21:55, Adam Kilgarriff <adam at lexmasterclass.com> wrote:
> Oliver,
> there are easier ways that taking lg models beyond the sentence. (And even
> if we did, the  clever spammer could use those lg models in 'generation'
> mode so keep ahead of us.)  One is to piggyback on the large amounts of work
> that Google and Bing do to stay ahead of the spammers, eg by using BootCaT.
>  They are putting lots of effort into not giving spam as top search hits, so
> if we use pages that they propose, we avoid most spam
>
> Adam
> On 16 November 2010 14:54, Oliver Mason <O.Mason at bham.ac.uk> wrote:
>>
>> I believe language models need to take structure beyond the sentence
>> into account. Then it would be fairly obvious that you're looking at a
>> list of sentences rather than a text; just as we can already
>> distinguish between a list of words and a proper sentence.
>>
>> The problem, then, is how to push language models up one level...
>>
>> Oliver
>>
>> On 16 November 2010 12:34, Justin Washtell <lec3jrw at leeds.ac.uk> wrote:
>> > Hi Serge,
>> >
>> > I can think of one or two half-hearted angles of attack, but nothing off
>> > the top of my head which couldn't readily be out-foxed by the very next wave
>> > of link-spammers. Indeed, any half-decent language models we do develop, are
>> > ripe for exploitation directly by the spammers. Given that very fundamental
>> > trait of language: its generative capacity, I am inclined to think that the
>> > spammers have the upper hand in this one. It's a bit like a war between
>> > viruses and anti-virus software, except in a world where a "legitimate"
>> > program is largely defined by the fact that it self-replicates and
>> > self-obfuscates. My initial suspicion is therefore that this is a genuinely
>> > hard - borderline impossible - problem. Mind you, that's exactly what makes
>> > it interesting... so I shall give it some more thought :-)
>> >
>> > Justin Washtell
>> > University of Leeds
>> >
>> > ________________________________________
>> > From: corpora-bounces at uib.no [corpora-bounces at uib.no] On Behalf Of Serge
>> > Sharoff [s.sharoff at leeds.ac.uk]
>> > Sent: 16 November 2010 09:12
>> > To: corpora at uib.no
>> > Subject: [Corpora-List] Deviations in language models on the web
>> >
>> > Dear all,
>> >
>> > in doing webcrawls for linguistic purposes, I recently came across an
>> > approach to link spamming or SEO optimisation that involves taking
>> > sentences from a large range of texts (mostly out-of-copyright fiction),
>> > mixing the sentences randomly, injecting the name of a product (or other
>> > keywords) and creating thousands of webpages.
>> >
>> > The intent is probably to fool search engines into thinking these are
>> > product reviews or descriptions, but the implication for linguistics is
>> > that we get polluted language models, in which mobile phones collocate
>> > with horse drawn carriages.
>> >
>> > SEO-enhanced pages I came across in the past contained random word lists
>> > with keywords injected.  It was possible to deal with such cases by
>> > n-gram filtering.  However, this simple trick doesn't work any longer,
>> > as the sentences are to a very large extent entirely grammatical.
>> >
>> > Any experience from others and suggestions on how to deal with this
>> > phenomenon.
>> >
>> > Best,
>> > Serge
>> >
>> >
>> > _______________________________________________
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>> > Corpora at uib.no
>> > http://mailman.uib.no/listinfo/corpora
>> >
>> > _______________________________________________
>> > Corpora mailing list
>> > Corpora at uib.no
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>> >
>>
>>
>>
>> --
>> Dr Oliver Mason
>> Technical Director of the Centre for Corpus Research
>> Head of Postgraduate Studies (Doctoral Research)
>> School of English, Drama, and ACS
>> The University of Birmingham
>> Birmingham B15 2TT
>>
>> _______________________________________________
>> Corpora mailing list
>> Corpora at uib.no
>> http://mailman.uib.no/listinfo/corpora
>
>
>
> --
> ================================================
> Adam Kilgarriff
> http://www.kilgarriff.co.uk
> Lexical Computing Ltd                   http://www.sketchengine.co.uk
> Lexicography MasterClass Ltd      http://www.lexmasterclass.com
> Universities of Leeds and Sussex       adam at lexmasterclass.com
> ================================================
>

--
Dr Oliver Mason
Technical Director of the Centre for Corpus Research
Head of Postgraduate Studies (Doctoral Research)
School of English, Drama, and ACS
The University of Birmingham
Birmingham B15 2TT

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