title: Feature Review of Matthew Bannister (1999) Positively George Street: A personal history of Sneaky Feelings and the Dunedin Sound, Auckland: Reed

authors: McCleay, Colin

subjects: Sneaky Feeling

abstract: Feature review of the book: Matthew Bannister (1999) Positively George Street: A personal history of Sneaky Feelings and the Dunedin Sound, Auckland: Reed.

text: Feature Review of Matthew Bannister (1999) Positively George Street: A personal history of Sneaky Feelings and the Dunedin Sound, Auckland: Reed Feature review of the book: Matthew Bannister (1999) Positively George Street: A personal history of Sneaky Feelings and the Dunedin Sound, Auckland: Reed.

year: 2001

title: Exuberance in historical stock prices during the Mississippi and South Seas bubble episodes

authors: Hu, Yang

abstract: The Mississippi Bubble and the South Sea Bubble are the two most famous and earliest episodes in the history of speculation, which can be dated back to the eighteenth century. Unlike most studies focus on some recent financial bubble footprints, we pay special attention to the most remarkable events in 1720. We empirically test for evidence of exuberance in historical stock prices of the Mississippi Company and the South Sea Company during the well-documented Mississippi Bubble and South Sea Bubble episodes, respectively. The right-tailed unit root test of Phillips, Shi and Yu (2015, PSY) is utilised in this paper. In addition, contagion in these historical markets is also considered.

text: Exuberance in historical stock prices during the Mississippi and South Seas bubble episodes The Mississippi Bubble and the South Sea Bubble are the two most famous and earliest episodes in the history of speculation, which can be dated back to the eighteenth century. Unlike most studies focus on some recent financial bubble footprints, we pay special attention to the most remarkable events in 1720. We empirically test for evidence of exuberance in historical stock prices of the Mississippi Company and the South Sea Company during the well-documented Mississippi Bubble and South Sea Bubble episodes, respectively. The right-tailed unit root test of Phillips, Shi and Yu (2015, PSY) is utilised in this paper. In addition, contagion in these historical markets is also considered.

year: 2017

title: Diacritic Restoration and the Development of a Part-of-Speech Tagset for the Māori Language

authors: Cocks, John

subjects: Māori

abstract: This thesis investigates two fundamental problems in natural language processing: diacritic restoration and part-of-speech tagging. Over the past three decades, statistical approaches to diacritic restoration and part-of-speech tagging have grown in interest as a consequence of the increasing availability of manually annotated training data in major languages such as English and French. However, these approaches are not practical for most minority languages, where appropriate training data is either non-existent or not publically available. Furthermore, before developing a part-of-speech tagging system, a suitable tagset is required for that language. In this thesis, we make the following contributions to bridge this gap:

Firstly, we propose a method for diacritic restoration based on naive Bayes classifiers that act at word-level. Classifications are based on a rich set of features, extracted automatically from training data in the form of diacritically marked text. This method requires no additional resources, which makes it language independent. The algorithm was evaluated on one language, namely Māori, and an accuracy exceeding 99% was observed.

Secondly, we present our work on creating one of the necessary resources for the development of a part-of-speech tagging system in Māori, that of a suitable tagset. The tagset described was developed in accordance with the EAGLES guidelines for morphosyntactic annotation of corpora, and was the result of in-depth analysis of the Māori grammar.

text: Diacritic Restoration and the Development of a Part-of-Speech Tagset for the Māori Language This thesis investigates two fundamental problems in natural language processing: diacritic restoration and part-of-speech tagging. Over the past three decades, statistical approaches to diacritic restoration and part-of-speech tagging have grown in interest as a consequence of the increasing availability of manually annotated training data in major languages such as English and French. However, these approaches are not practical for most minority languages, where appropriate training data is either non-existent or not publically available. Furthermore, before developing a part-of-speech tagging system, a suitable tagset is required for that language. In this thesis, we make the following contributions to bridge this gap:

Firstly, we propose a method for diacritic restoration based on naive Bayes classifiers that act at word-level. Classifications are based on a rich set of features, extracted automatically from training data in the form of diacritically marked text. This method requires no additional resources, which makes it language independent. The algorithm was evaluated on one language, namely Māori, and an accuracy exceeding 99% was observed.

Secondly, we present our work on creating one of the necessary resources for the development of a part-of-speech tagging system in Māori, that of a suitable tagset. The tagset described was developed in accordance with the EAGLES guidelines for morphosyntactic annotation of corpora, and was the result of in-depth analysis of the Māori grammar.

year: 2012