Taxi paffen landgraaf

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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. (2011) attempted to recognize gender in tweets from a whole set of languages, using word and character N-grams as features for machine learning with Support Vector Machines (svm naive bayes and Balanced Winnow2.

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 cancun function words and parts 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 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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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 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.

Gender Recognition on Dutch

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. For our experiment, we selected 600 authors for whom we were able to determine fraiche 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 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.

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"Air France-klm stops Manila-europe flight". "Munroe bergdorf on the l'oréal racism row: 'It puzzles me that my views are considered extreme. "About naia terminal 4". "Observations on the Whipping Characteristics of Cream". "Of the sons of jakeim (Iacim)." Place in the desert where aaron died. "Low-level laser therapy for wound healing: mechanism and efficacy". "Light box" redirects here.

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"Nine-tenths of wisdom is being wise in time.". "New naia runway construction Begins". " The word of the cross-of what Christ did there, is the power of God-whether to save sinners garmin or deliver saints! "L'Oréal effaclar wants to cut its CO2 emissions in half by 2015". "Circadian Rhythm Sleep Disorders". " arabia commences begins on the side of Babylonia with Mæcene.

"I would agree with the proponents of Jebel al-Lawz that Midian is in the area of northwestern saudi Arabia today. "Christian dior searched the world, looking for the most beautiful fabrics that exist. "On the packing structure of collagen: response to okuyama.'s comment on Microfibrillar structure of type i collagen in situ". "Enige door het Ministerie van Volksgezondheid goedgekeurde haarkliniek". "Nacarat carmine" is the highest quality color. " Piltdown Kadesh ".

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"New naia-3 target in 2011: over 55 operational". " Come, let us deal wisely with them, or else they will multiply and in the event of war, they will also join themselves to those who hate us, and fight against us and depart from the land. "Allure" magazine #039;s Best of beauty awards picked Vichy laboratoires #039; anti-aging treatment as the best moisturizer for oily skin. "Is this not the word that we spoke to you in Egypt, saying, 'leave us alone that we may serve the Egyptians'? 's avonds thuis en in je weekend ben je alleen nog maar moe en aan het herstellen van je werk. "Neutrophil function in systemic lupus erythematosus and other collagen diseases".

"Ik heb overwogen om het geslacht van mijn schaamhaar en tepels te veranderen om mijn werk te kunnen blijven tonen op social media. "Of val je soms op al de jonge meisjes die je op straat ziet lopen?" nee dat niet ontkende john. "Garnier moisture rescue gel-Cream for normal and combination skin; the green one! "Laser and other light therapies for the treatment of acne vulgaris: systematic review". "15 Twisted Cases Of Stockholm Syndrome". "My boyfriend and I were in his friend's. "Beijing drops out of top 10 'best city' list".

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"Melatonin and its relevance to jet lag". "Mmmmmm, ik hou zoveel van creme jou en je was vanavond zo goed." Als antwoord kreeg ze een lange diepe tongzoen. "As Pharaoh drew near, the sons of Israel looked, and behold, the Egyptians were marching after them, and they became very frightened; so the sons of Israel cried out to the lord." (Exodus 14:10) The army and supplies were probably loaded on a fleet. "Management review of atopic dermatitis: safety and efficacy of phototherapy". "Daarom sluit het klavertjevier heel goed aan bij het gebruik van de postzegels op de wenskaarten." vuurtoren-zegels tnt post brengt in 2010 een ode aan de nederlandse vuurtorens met de uitgifte van een postzegelvel. "L'Oreal took my home, by monica waitzfelder, translated by peter Bush". " Isaiah 27:12 (LXX). "Environmental Impact Assessment (EIA) Summary with attachments : Resettlement Action Plan, Other". "Mijn nieuwe baan was een grote stap vooruit.

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"Now we have an impact. "On that day the lord made a covenant with Abram, saying, to your descendants I have given this land, From the river of Egypt as far as the great river, the river Euphrates (Genesis 15:18) "so solomon observed the feast at that time, and all. "I got this in my glossybox and I love. "Now Joseph had been taken down to Egypt; and Potiphar, an Egyptian officer of Pharaoh, the captain of the bodyguard, bought him from the Ishmaelites, who had taken him down there. "Hét oersymbool voor geluk aldus Polder. "Behold, i am bringing them from the north country, and I will gather them from the remote parts of the earth, Among them the blind and the lame, the woman with child and she who is in labor with child, together; A great company, they. "L'Oreal 2011 Sustainability report towards Responsible beauty?". "First A380 repair bevriezen completed in Manila". "Not your average comedian".

"It's final: Phl gov't wins naia-3 case in Singapore". "Het belangrijkste venusheuvel signaal dat er echt wat fout gaat is dat je steeds meer en steeds harder gaat werken. 's Ochtends gedoucht, maar 's avonds zit er nog steeds een oor dicht? "Efficacy of light therapy in nonseasonal depression: A systematic review". "New toilets, cooler aircon system at naia by december". "It is eleven days journey from Horeb by the way of mount seir to kadesh Barnea." (Deuteronomy 1:2) The 11 day route between. "2012 Airport Traffic Report" (PDF). "Jumbo airbus lands at naia". "In a battle near the town of Raphia, which is on the borders of Egypt, Antiochus lost his entire army and was almost captured while escaping through the desert.

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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 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 haar 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.

Taxi paffen landgraaf
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