| dc.contributor.author | Ingelby, Michael | |
| dc.contributor.author | Sharoff, Serge | |
| dc.date.accessioned | 2021-05-07T12:04:35Z | |
| dc.date.available | 2021-05-07T12:04:35Z | |
| dc.date.issued | 2019-08 | |
| dc.identifier.uri | http://hdl.handle.net/11071/10467 | |
| dc.description | Paper presented at the 5th Strathmore International Mathematics Conference (SIMC 2019), 12 - 16 August 2019, Strathmore University, Nairobi, Kenya | en_US |
| dc.description.abstract | For 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.sponsorship | University of Leeds, United Kingdom. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Strathmore University | en_US |
| dc.subject | Robust statistics | en_US |
| dc.subject | Word frequencies | en_US |
| dc.subject | Core lexicon | en_US |
| dc.title | A Robust statistical model of word frequencies | en_US |
| dc.type | Article | en_US |
