title: An ethnographic study of technical support workers: why we didn't build a tech support digital library

authors: Cunningham, Sally Jo

subjects: computer science

abstract: In this paper we describe the results of an ethnographic study of the information behaviourss of university technical support workers and their information needs. The study looked at how the group identified, located and used information from a variety of sources to solve problems arising in the course of their work. The results of the investigation are discussed in the context of the feasibility of developing a potential information base that could be used by all members of the group. Whilst a number of their requirements would easily be fulfilled by the use of a digital library, other requirements would not. The paper illustrates the limitations of a digital library with respect to the information behaviourss of this group of subjects and focuses on why a digital library would not appear to be the ideal support tool for their work.

text: An ethnographic study of technical support workers: why we didn't build a tech support digital library In this paper we describe the results of an ethnographic study of the information behaviourss of university technical support workers and their information needs. The study looked at how the group identified, located and used information from a variety of sources to solve problems arising in the course of their work. The results of the investigation are discussed in the context of the feasibility of developing a potential information base that could be used by all members of the group. Whilst a number of their requirements would easily be fulfilled by the use of a digital library, other requirements would not. The paper illustrates the limitations of a digital library with respect to the information behaviourss of this group of subjects and focuses on why a digital library would not appear to be the ideal support tool for their work.

year: 2001

title: Text categorization using compression models

authors: Frank, Eibe

abstract: Text categorization, or the assignment of natural language texts to predefined categories based on their content, is of growing importance as the volume of information available on the internet continues to overwhelm us. The use of predefined categories implies a “supervised learning” approach to categorization, where already-classified articles—which effectively define the categories—are used as “training data” to build a model that can be used for classifying new articles that comprise the “test data.” This contrasts with “unsupervised” learning, where there is no training data and clusters of like documents are sought amongst the test articles. With supervised learning, meaningful labels (such as
keyphrases) are attached to the training documents, and appropriate labels can be assigned automatically to test documents depending on which category they fall into.

text: Text categorization using compression models Text categorization, or the assignment of natural language texts to predefined categories based on their content, is of growing importance as the volume of information available on the internet continues to overwhelm us. The use of predefined categories implies a “supervised learning” approach to categorization, where already-classified articles—which effectively define the categories—are used as “training data” to build a model that can be used for classifying new articles that comprise the “test data.” This contrasts with “unsupervised” learning, where there is no training data and clusters of like documents are sought amongst the test articles. With supervised learning, meaningful labels (such as
keyphrases) are attached to the training documents, and appropriate labels can be assigned automatically to test documents depending on which category they fall into.

year: 2000

title: The art of dialogue with indigenous communities in the new biotechnology world

authors: Hudson, Maui

subjects: biotechnology

abstract: Te Hau Mihi Ata is a research project that aims to negotiate spaces for and develop processes of dialogue that allow for a deeper level of interaction between mtauranga Māori (Māori indigenous knowledge) and science. Over a two-year period a series of facilitated exchanges or wnanga were held focusing on areas of new technology (assisted reproductive technologies, life technologies, and future food technologies) that involved Māori scientists and people with expertise in mtauranga Māori. These dialogue events were designed to explore, through the challenge of considering new biotechnologies, the similarities and differences that emerge from approaching these issues from different knowledge paradigms. This paper will outline the key project findings from this series of exchanges including the barriers and facilitators to the dialogue process and knowledge exchange as well as discuss how participants created connections between scientific discourse and indigenous knowledge frameworks.

text: The art of dialogue with indigenous communities in the new biotechnology world Te Hau Mihi Ata is a research project that aims to negotiate spaces for and develop processes of dialogue that allow for a deeper level of interaction between mtauranga Māori (Māori indigenous knowledge) and science. Over a two-year period a series of facilitated exchanges or wnanga were held focusing on areas of new technology (assisted reproductive technologies, life technologies, and future food technologies) that involved Māori scientists and people with expertise in mtauranga Māori. These dialogue events were designed to explore, through the challenge of considering new biotechnologies, the similarities and differences that emerge from approaching these issues from different knowledge paradigms. This paper will outline the key project findings from this series of exchanges including the barriers and facilitators to the dialogue process and knowledge exchange as well as discuss how participants created connections between scientific discourse and indigenous knowledge frameworks.

year: 2012