title: “My Home Is My Castle”: Defiance of the commercial homestay host in tourism

authors: McIntosh, Alison J.

subjects: commercial home

abstract: The intrinsic nature of small tourism business provision has rarely been captured in previous literature, but it has recently gained momentum within scholarly discourse exploring the role of the “home” in tourism and hospitality. This article contributes an examination of the commercial homestay host in New Zealand with a particular focus on the hosts’ personal relationship with their “commercial home.” The article reports the findings of in-depth interviews conducted with commercial homestay hosts in New Zealand. Findings allude to the tyranny of the homestay hosts in their tourism hosting role, their oppressive social need, self-marginalization, and distinctive identity—one that is notably defiant of other commercial hospitality and tourism business norms. In contrast, previous studies rarely showcase the personal perspectives, conscious defiance, or marginalization of commercial hospitality provision. Consequences for understanding the tourism and hospitality phenomenon of commercial home hosting are thus discussed.

text: “My Home Is My Castle”: Defiance of the commercial homestay host in tourism The intrinsic nature of small tourism business provision has rarely been captured in previous literature, but it has recently gained momentum within scholarly discourse exploring the role of the “home” in tourism and hospitality. This article contributes an examination of the commercial homestay host in New Zealand with a particular focus on the hosts’ personal relationship with their “commercial home.” The article reports the findings of in-depth interviews conducted with commercial homestay hosts in New Zealand. Findings allude to the tyranny of the homestay hosts in their tourism hosting role, their oppressive social need, self-marginalization, and distinctive identity—one that is notably defiant of other commercial hospitality and tourism business norms. In contrast, previous studies rarely showcase the personal perspectives, conscious defiance, or marginalization of commercial hospitality provision. Consequences for understanding the tourism and hospitality phenomenon of commercial home hosting are thus discussed.

year: 2011-09

title: Random Relational Rules

authors: Anderson, Grant

subjects: relational data mining

abstract: In the field of machine learning, methods for learning from single-table data have received much more attention than those for learning from multi-table, or relational data, which are generally more computationally complex. However, a significant amount of the world's data is relational. This indicates a need for algorithms that can operate efficiently on relational data and exploit the larger body of work produced in the area of single-table techniques.

This thesis presents algorithms for learning from relational data that mitigate, to some extent, the complexity normally associated with such learning. All algorithms in this thesis are based on the generation of random relational rules. The assumption is that random rules enable efficient and effective relational learning, and this thesis presents evidence that this is indeed the case. To this end, a system for generating random relational rules is described, and algorithms using these rules are evaluated. These algorithms include direct classification, classification by propositionalisation, clustering, semi-supervised learning and generating random forests.

The experimental results show that these algorithms perform competitively with previously published results for the datasets used, while often exhibiting lower runtime than other tested systems. This demonstrates that sufficient information for classification and clustering is retained in the rule generation process and that learning with random rules is efficient.

Further applications of random rules are investigated. Propositionalisation allows single-table algorithms for classification and clustering to be applied to the resulting data, reducing the amount of relational processing required. Further results show that techniques for utilising additional unlabeled training data improve accuracy of classification in the semi-supervised setting. The thesis also develops a novel algorithm for building random forests by makingefficient use of random rules to generate trees and leaves in parallel.

text: Random Relational Rules In the field of machine learning, methods for learning from single-table data have received much more attention than those for learning from multi-table, or relational data, which are generally more computationally complex. However, a significant amount of the world's data is relational. This indicates a need for algorithms that can operate efficiently on relational data and exploit the larger body of work produced in the area of single-table techniques.

This thesis presents algorithms for learning from relational data that mitigate, to some extent, the complexity normally associated with such learning. All algorithms in this thesis are based on the generation of random relational rules. The assumption is that random rules enable efficient and effective relational learning, and this thesis presents evidence that this is indeed the case. To this end, a system for generating random relational rules is described, and algorithms using these rules are evaluated. These algorithms include direct classification, classification by propositionalisation, clustering, semi-supervised learning and generating random forests.

The experimental results show that these algorithms perform competitively with previously published results for the datasets used, while often exhibiting lower runtime than other tested systems. This demonstrates that sufficient information for classification and clustering is retained in the rule generation process and that learning with random rules is efficient.

Further applications of random rules are investigated. Propositionalisation allows single-table algorithms for classification and clustering to be applied to the resulting data, reducing the amount of relational processing required. Further results show that techniques for utilising additional unlabeled training data improve accuracy of classification in the semi-supervised setting. The thesis also develops a novel algorithm for building random forests by makingefficient use of random rules to generate trees and leaves in parallel.

year: 2008

title: Portfolio of compositions

authors: Hoadley, Benjamin Russell

subjects: New Zealand composition

abstract: The music in this portfolio of original compositions is steeped in the Western tradition of tonal music. The pieces were written while also pursuing a professional career as a bassoonist touring internationally and performing a wide variety of western art music, from Renaissance to contemporary. I have responded to these influences consciously and unconsciously in my music. The overarching focus of this composition portfolio is to provide an answer to the question — to what extent do musical influences impact on the compositions of an international touring performer?

Underpinning the portfolio is the fact that the pieces were all written in New Zealand during periods of intense reflection and study. While I am constantly collecting ideas and inspiration for my music while travelling, I consolidate and realise these ideas only when I am home.

I identify with being a New Zealand composer, with cosmopolitan influences on my music reflecting the global influences on New Zealand’s culture and art. Working closely with composers performing their music has also informed my composition. I mention Gillian Whitehead in particular, whose music I have performed widely.

The two outer pieces in the portfolio, Huia and Manaia 4 are the most directly associated with New Zealand in their subject matter. Other pieces have foreign themes, from my nocturnal impressions of New York in Night Music to the Ancient Greece of Ostrakon to the West African poetry of Four Songs.

All of the pieces were written for professional musicians to perform, including the Auckland Philharmonia Orchestra and the Sydney Omega Ensemble. Having these outstanding performers in mind while writing, and interacting with these musicians during the composition process, has informed my writing.

text: Portfolio of compositions The music in this portfolio of original compositions is steeped in the Western tradition of tonal music. The pieces were written while also pursuing a professional career as a bassoonist touring internationally and performing a wide variety of western art music, from Renaissance to contemporary. I have responded to these influences consciously and unconsciously in my music. The overarching focus of this composition portfolio is to provide an answer to the question — to what extent do musical influences impact on the compositions of an international touring performer?

Underpinning the portfolio is the fact that the pieces were all written in New Zealand during periods of intense reflection and study. While I am constantly collecting ideas and inspiration for my music while travelling, I consolidate and realise these ideas only when I am home.

I identify with being a New Zealand composer, with cosmopolitan influences on my music reflecting the global influences on New Zealand’s culture and art. Working closely with composers performing their music has also informed my composition. I mention Gillian Whitehead in particular, whose music I have performed widely.

The two outer pieces in the portfolio, Huia and Manaia 4 are the most directly associated with New Zealand in their subject matter. Other pieces have foreign themes, from my nocturnal impressions of New York in Night Music to the Ancient Greece of Ostrakon to the West African poetry of Four Songs.

All of the pieces were written for professional musicians to perform, including the Auckland Philharmonia Orchestra and the Sydney Omega Ensemble. Having these outstanding performers in mind while writing, and interacting with these musicians during the composition process, has informed my writing.

year: 2016