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dc.contributor.authorIngelby, Michael
dc.contributor.authorSharoff, Serge
dc.date.accessioned2021-05-07T12:04:35Z
dc.date.available2021-05-07T12:04:35Z
dc.date.issued2019-08
dc.identifier.urihttp://hdl.handle.net/11071/10467
dc.descriptionPaper presented at the 5th Strathmore International Mathematics Conference (SIMC 2019), 12 - 16 August 2019, Strathmore University, Nairobi, Kenyaen_US
dc.description.abstractFor the purposes of language teaching or automatic language processing it is important to know how frequent a word is. However, a simple procedure counting the number of times a word occurs in a collection of texts leads to many unfortunate artefacts because some words occur too often in a small number of texts leading to frequency bursts. Our task in this paper is to introduce a statistical model which uses methods from robust statistics to estimate the frequencies of words in a collection of texts.en_US
dc.description.sponsorshipUniversity of Leeds, United Kingdom.en_US
dc.language.isoen_USen_US
dc.publisherStrathmore Universityen_US
dc.subjectRobust statisticsen_US
dc.subjectWord frequenciesen_US
dc.subjectCore lexiconen_US
dc.titleA Robust statistical model of word frequenciesen_US
dc.typeArticleen_US


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  • SIMC 2019 [99]
    5th Strathmore International Mathematics Conference (August 12 – 16, 2019)

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