title: Tongan men talk when the language (talanoa) and context (faikava) are Tongan

authors: Vaka, Sione

subjects: Tongan

abstract: In Tongan society, Tongan males have the authority, while Tongan females hold the senior ranks in society. Other roles and responsibilities, including father, leader, provider, protector, negotiator, communicator, mentor and so forth, are also expected of Tongan males. Tongan men understand that these roles and responsibilities are to be performed effectively and held in high regard as they represent their father, grandfather, family, kāinga, village, and the Kingdom of Tonga.  Despite the many tasks assumed by Tongan males, they are struggling to communicate, and have difficulty disclosing sensitive matters. Moving to New Zealand also introduces new challenges with a new environment, culture, technology, language, and ways of living. This paper focuses on talanoa with Tongan men around smoking in a faikava setting in Auckland. The information discussed in this chapter was generated by four different faikava groups that were hold at local churches in the Auckland area. During the talanoa, the men also discussed their roles and responsibilities and how these influenced their decisions.

text: Tongan men talk when the language (talanoa) and context (faikava) are Tongan In Tongan society, Tongan males have the authority, while Tongan females hold the senior ranks in society. Other roles and responsibilities, including father, leader, provider, protector, negotiator, communicator, mentor and so forth, are also expected of Tongan males. Tongan men understand that these roles and responsibilities are to be performed effectively and held in high regard as they represent their father, grandfather, family, kāinga, village, and the Kingdom of Tonga.  Despite the many tasks assumed by Tongan males, they are struggling to communicate, and have difficulty disclosing sensitive matters. Moving to New Zealand also introduces new challenges with a new environment, culture, technology, language, and ways of living. This paper focuses on talanoa with Tongan men around smoking in a faikava setting in Auckland. The information discussed in this chapter was generated by four different faikava groups that were hold at local churches in the Auckland area. During the talanoa, the men also discussed their roles and responsibilities and how these influenced their decisions.

year: 2017

title: Concept-based Text Clustering

authors: Huang, Lan

subjects: clustering

abstract: Thematic organization of text is a natural practice of humans and a crucial task for today's vast repositories. Clustering automates this by assessing the similarity between texts and organizing them accordingly, grouping like ones together and separating those with different topics. Clusters provide a comprehensive logical structure that facilitates exploration, search and interpretation of current texts, as well as organization of future ones. Automatic clustering is usually based on words. Text is represented by the words it mentions, and thematic similarity is based on the proportion of words that texts have in common. The resulting bag-of-words model is semantically ambiguous and undesirably orthogonal|it ignores the connections between words. This thesis claims that using concepts as the basis of clustering can significantly improve effectiveness. Concepts are defined as units of knowledge. When organized according to the relations among them, they form a concept system. Two concept systems are used here: WordNet, which focuses on word knowledge, and Wikipedia, which encompasses world knowledge. We investigate a clustering procedure with three components: using concepts to represent text; taking the semantic relations among them into account during clustering; and learning a text similarity measure from concepts and their relations. First, we demonstrate that concepts provide a succinct and informative representation of the themes in text, exemplifying this with the two concept systems. Second, we define methods for utilizing concept relations to enhance clustering by making the representation models more discriminative and extending thematic similarity beyond surface overlap. Third, we present a similarity measure based on concepts and their relations that is learned from a small number of examples, and show that it both predicts similarity consistently with human judgement and improves clustering. The thesis provides strong support for the use of concept-based representations instead of the classic bag-of-words model.

text: Concept-based Text Clustering Thematic organization of text is a natural practice of humans and a crucial task for today's vast repositories. Clustering automates this by assessing the similarity between texts and organizing them accordingly, grouping like ones together and separating those with different topics. Clusters provide a comprehensive logical structure that facilitates exploration, search and interpretation of current texts, as well as organization of future ones. Automatic clustering is usually based on words. Text is represented by the words it mentions, and thematic similarity is based on the proportion of words that texts have in common. The resulting bag-of-words model is semantically ambiguous and undesirably orthogonal|it ignores the connections between words. This thesis claims that using concepts as the basis of clustering can significantly improve effectiveness. Concepts are defined as units of knowledge. When organized according to the relations among them, they form a concept system. Two concept systems are used here: WordNet, which focuses on word knowledge, and Wikipedia, which encompasses world knowledge. We investigate a clustering procedure with three components: using concepts to represent text; taking the semantic relations among them into account during clustering; and learning a text similarity measure from concepts and their relations. First, we demonstrate that concepts provide a succinct and informative representation of the themes in text, exemplifying this with the two concept systems. Second, we define methods for utilizing concept relations to enhance clustering by making the representation models more discriminative and extending thematic similarity beyond surface overlap. Third, we present a similarity measure based on concepts and their relations that is learned from a small number of examples, and show that it both predicts similarity consistently with human judgement and improves clustering. The thesis provides strong support for the use of concept-based representations instead of the classic bag-of-words model.

year: 2011

title: An Interactive User Management System for Multilingual Documents: A case study of the Pei Jones collection

authors: Cader, Papitha

subjects: Greenstone Digital Library

abstract: Can general purpose DL software architecture be designed to provide a flexible environment that supports both the management and end-user roles through a single unified web interface? In particular we take the collected correspondence of the Māori scholar Dr. Pei Jones and undertake case study of how this approach can be applied in a practical way.

text: An Interactive User Management System for Multilingual Documents: A case study of the Pei Jones collection Can general purpose DL software architecture be designed to provide a flexible environment that supports both the management and end-user roles through a single unified web interface? In particular we take the collected correspondence of the Māori scholar Dr. Pei Jones and undertake case study of how this approach can be applied in a practical way.

year: 2012