Donker blauwe haarverf

donker blauwe haarverf

"And who may you be?" one of them suddenly asked pierre, evidently meaning what pierre himself had in mind, namely: "If you want to eat we'll give you some food, only let us know whether you are an honest man." by rights i. 'café' is the general name for a place licenced to sell alcohol: a bar. 'waarvoor gebruik je je smartphone het meest?' was asked by a user of Poll everywhere to a live audience who responded via text messaging or the web. 'hoe laat is het, vroeg hij zich. #cocinaconestefi #goodmorning Nota: si algo no les queda claro no duden es preguntar read more media removed buenos días Amaneciendo y con antojos Tostadas de #omelette con mis @huevoskikes. #Palapizza #ParaTodos #pizzataco media removed Comida de hoy! #paulasaludable #glutenfree #vegan #food read more media removed nuestros amigos de Chiriquí se unen al Burger Party con su "Meto burger 6 onzas de carne certified Angus beef bacon, chorizo español, queso americano, queso nacional, aguacate, cebollas crocantes, salsa honey bbq y jalea de ají. #venezolanosenenvigado #areparellena #arepaskb #quehacerenmedellin #secomechevere read more media removed Rollitos picantes rellenos de paté de zanahoria, rábanos, aguacate y queso crema de jalapeños.

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The men, on the other hand, seem to be more interested in computers, leading to important content words like software and game, and correspondingly more determiners and prepositions. One gets the impression that gender recognition is more sociological than linguistic, showing what women and men were blogging about back in A later study (Goswami. 2009) managed to increase the gender recognition quality.2, using sentence length, 35 non-dictionary words, and 52 slang words. The authors do not report the set of slang words, but the non-dictionary words appear to be more related to style than to content, showing that purely linguistic behaviour can contribute information for gender recognition as well. Gender recognition has also already been applied to Tweets. (2010) examined various traits of authors from India tweeting in English, combining character N-grams and sociolinguistic features like manner of laughing, honorifics, and smiley use. With lexical N-grams, they reached an accuracy.7, which the combination with the sociolinguistic features increased.33.

donker blauwe haarverf

In (Koppel. 2002) they report gender recognition on formal written texts taken from the British National Corpus (and also give a good overview of previous work reaching about 80 correct attributions using function words and parts kalken of speech. Later, in 2004, the group collected a blog Authorship Corpus (BAC; (Schler. 2006 containing about 700,000 posts to m (in total about 140 million words) by almost 20,000 bloggers. For each blogger, metadata is present, including the blogger s self-provided gender, age, industry and astrological sign. This corpus has coloscopie been used extensively since.

The creators themselves used it for various classification tasks, including gender recognition (Koppel. They report an overall accuracy.1. Slightly more information seems to be coming from content (75.1 accuracy) than from style (72.0 accuracy). However, even style appears to mirror content. We see the women focusing on personal matters, leading to important content words like love and boyfriend, and important style words like i and other personal pronouns.

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C 2014 egel van Halteren and Speerstra. Gender Recognition Gender recognition is a subtask in the general field of authorship recognition and profiling, which has reached maturity in the last decades(for an overview, see. (Juola 2008) and (Koppel. Currently the field is getting an impulse for further development now that vast data sets of user generated data is becoming available. (2012) show that authorship recognition is also possible (to some degree) if the number of candidate authors is as high as 100,000 (as compared to the usually less than ten in traditional studies). Even so, there are circumstances where outright recognition is not an option, but where one must be content with profiling,. The identification of author traits like gender, age and geographical background. In this baby paper we restrict ourselves to gender recognition, and it is also this aspect we will discuss further in this section. A group which is very active in studying gender recognition (among other traits) on the basis of text is that around Moshe koppel.

donker blauwe haarverf

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For our experiment, we selected 600 authors for whom we were able to determine with a high degree of certainty a) that they were human individuals and b) what gender they were. We then experimented with several author profiling techniques, namely support Vector Regression (as provided by libsvm; (Chang and Lin 2011 linguistic Profiling (LP; (van Halteren 2004 and timbl (Daelemans. 2004 with and without preprocessing the input vectors with Principal Component Analysis (PCA; (Pearson filler 1901 (Hotelling 1933). We also varied the recognition features provided to the techniques, using both character and token n-grams. For all techniques and features, we ran the same 5-fold cross-validation experiments in order to determine how well they could be used to distinguish between male and female authors of tweets. In the following sections, we first present some previous work on gender recognition (Section 2). Then we describe our experimental data and the evaluation method (Section 3 after which we proceed to describe the various author profiling strategies that we investigated (Section 4). Then follow the results (Section 5 and Section 6 concludes the paper. For whom we already know that they are an individual person rather than, say, a husband and wife couple or a board of editors for an official Twitterfeed.

1 Computational Linguistics in the netherlands journal 4 (2014) Submitted 06/2014; Published 12/2014 Gender Recognition on Dutch Tweets Hans van Halteren Nander Speerstra radboud University nijmegen, cls, linguistics Abstract In this paper, we investigate gender recognition on Dutch Twitter material, using a corpus consisting. We achieved the best results,.5 correct assignment in a 5-fold cross-validation on our corpus, with Support Vector Regression on all token unigrams. Two other machine learning systems, linguistic Profiling and timbl, come avon close to this result, at least when the input is first preprocessed with pca. Introduction In the netherlands, we have a rather unique resource in the form of the Twinl data set: a daily updated collection that probably contains at least 30 of the dutch public tweet production since 2011 (Tjong Kim Sang and van den Bosch 2013). However, as any collection that is harvested automatically, its usability is reduced by a lack of reliable metadata. In this case, the Twitter profiles of the authors are available, but these consist of freeform text rather than fixed information fields. And, obviously, it is unknown to which degree the information that is present is true. The resource would become even more useful if we could deduce complete and correct metadata from the various available information sources, such as the provided metadata, user relations, profile photos, and the text of the tweets. In this paper, we start modestly, by attempting to derive just the gender of the authors 1 automatically, purely on the basis of the content of their tweets, using author profiling techniques.

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Donker blauwe haarverf
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Recensies voor het bericht donker blauwe haarverf

  1. Yteco hij schrijft:

    Wij gebruiken onder meer analytische cookies voor optimalisatie van jouw gebruik van onze website. Reactie infoteur, hi, dit is natuurlijk erg lastig te beantwoorden. Je vraagt wat je moet doen. Ik heb uw tip wel gelezen.

  2. Ozuqev hij schrijft:

    Erika, 13:19 #6, hallo, al meer dan 20 jaar verf ik zelf mijn haar thuis met kleurshampoo met prima resultaat. De kleur blijft lang mooi en de haarverf is na opening nog 12 maanden houdbaar. Via de haarkleur adviestool krijg je kleuradvies op maat.

  3. Beguhyzu hij schrijft:

    Op dit moment is mijn haar reeds goed afgebleekt van de zon en voor een themaweekend heb ik nu kleurenshampoo 'donker blond' gekocht om het iets bleker te krijgen. Heb wel ervaring met verven etc. M/pin/ / - dat dus.

  4. Olalilu hij schrijft:

    Hoeveel percentage moet dat zijn? Hoe kan ik dit doen? Sla dus niet te snel weer aan het blonderen. Sabrina, 05:07 #1, beste, ik heb zelf zwart haar en ik een rood violetbruin kleur gekocht van keune.



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