Extending Zipf’s law to n-grams for large corpora

Experiments show that for a large corpus, Zipf’s law does not hold for all rank of words: the frequencies fall below those predicted by Zipf’s law for ranks greater than about 5,000 word types in the English language and about 30,000 word types in the inflected languages Irish and Latin. It also does not hold for syllables or words in the syllable-based languages, Chinese or Vietnamese. However, when single words are combined together with word n-grams in one list and put in rank order, the frequency of tokens in the combined list extends Zipf’s law with a slope close to -1 on a log-log plot in all five languages. Further experiments have demonstrated the validity of this extension of Zipf’s law to n-grams of letters, phonemes or binary bits in English. It is shown theoretically that probability theory
alone can predict this behavior in randomly created n-grams of binary bits.

How could Human Rights Law be used by the Courts to assist Victims of Domestic Violence? A Comparative Study

It has been increasingly recognised in recent years that domestic violence constitutes a human rights issue. This article seeks to shed light on the question of how human rights law may be used in the area of domestic violence through the medium of a litigation strategy. The method used is a comparative assessment of the approaches taken towards gender issues by the Constitutional Courts in three states that have famously dynamic judiciaries- India, South Africa and Canada. A number of the obstacles to the effectiveness of human rights law are also examined.