title: Information seeking retrieval, reading and storing behaviour of library users

authors: Turner, Kristine

subjects: computer science

abstract: In the interest of digital libraries, it is advisable that designers be aware of the potential behaviour of the users of such a system. There are two distinct parts under investigation, the interaction between traditional libraries involving the seeking and retrieval of relevant material, and the reading and storage behaviours ensuing. Through this analysis, the findings could be incorporated into digital library facilities. There has been copious amounts of research on information seeking leading to the development of behavioural models to describe the process. Often research on the information seeking practices of individuals is based on the task and field of study. The information seeking model, presented by Ellis et al. (1993), characterises the format of this study where it is used to compare various research on the information seeking practices of groups of people (from academics to professionals). It is found that, although researchers do make use of library facilities, they tend to rely heavily on their own collections and primarily use the library as a source for previously identified information, browsing and interloan. It was found that there are significant differences in user behaviour between the groups analysed. When looking at the reading and storage of material it was hard to draw conclusions, due to the lack of substantial research and information on the topic. However, through the use of reading strategies, a general idea on how readers behave can be developed. Designers of digital libraries can benefit from the guidelines presented here to better understand their audience.

text: Information seeking retrieval, reading and storing behaviour of library users In the interest of digital libraries, it is advisable that designers be aware of the potential behaviour of the users of such a system. There are two distinct parts under investigation, the interaction between traditional libraries involving the seeking and retrieval of relevant material, and the reading and storage behaviours ensuing. Through this analysis, the findings could be incorporated into digital library facilities. There has been copious amounts of research on information seeking leading to the development of behavioural models to describe the process. Often research on the information seeking practices of individuals is based on the task and field of study. The information seeking model, presented by Ellis et al. (1993), characterises the format of this study where it is used to compare various research on the information seeking practices of groups of people (from academics to professionals). It is found that, although researchers do make use of library facilities, they tend to rely heavily on their own collections and primarily use the library as a source for previously identified information, browsing and interloan. It was found that there are significant differences in user behaviour between the groups analysed. When looking at the reading and storage of material it was hard to draw conclusions, due to the lack of substantial research and information on the topic. However, through the use of reading strategies, a general idea on how readers behave can be developed. Designers of digital libraries can benefit from the guidelines presented here to better understand their audience.

year: 1997-06

title: Locally weighted naive Bayes

authors: Frank, Eibe

subjects: computer science

abstract: Despite its simplicity, the naive Bayes classifier has surprised machine learning researchers by exhibiting good performance on a variety of learning problems. Encouraged by these results, researchers have looked to overcome naive Bayes' primary weakness—attribute independence—and improve the performance of the algorithm. This paper presents a locally weighted version of naive Bayes that relaxes the independence assumption by learning local models at prediction time. Experimental results show that locally weighted naive Bayes rarely degrades accuracy compared to standard naive Bayes and, in many cases, improves accuracy dramatically. The main advantage of this method compared to other techniques for enhancing naive Bayes is its conceptual and computational simplicity.

text: Locally weighted naive Bayes Despite its simplicity, the naive Bayes classifier has surprised machine learning researchers by exhibiting good performance on a variety of learning problems. Encouraged by these results, researchers have looked to overcome naive Bayes' primary weakness—attribute independence—and improve the performance of the algorithm. This paper presents a locally weighted version of naive Bayes that relaxes the independence assumption by learning local models at prediction time. Experimental results show that locally weighted naive Bayes rarely degrades accuracy compared to standard naive Bayes and, in many cases, improves accuracy dramatically. The main advantage of this method compared to other techniques for enhancing naive Bayes is its conceptual and computational simplicity.

year: 2003-04

title: A socio-demographic profile of Māori living in Australia

authors: Kukutai, Tahu

subjects: demography

abstract: This report provides a comprehensive demographic and socio-economic profile of the Māori population in Australia using data from the 2011 Australia Census of Population and Housing. The purpose is to provide an evidence base with which to inform future policy approaches with respect to Māori in Australia. It focuses on five key areas: 

Population size and composition; 
Identity and culture; 
Year of arrival and citizenship; 
Education and work; 
Lone parenting and unpaid childcare. 

Comparisons are undertaken with Māori in the 2006 Australia Census, as well as with two reference groups: the total Australia population and migrant non-Māori New Zealanders. Where appropriate, we also distinguish Māori migrants born in New Zealand and Māori born in Australia. This captures important differences within the Māori population in Australia that have been under-examined in previous studies.

text: A socio-demographic profile of Māori living in Australia This report provides a comprehensive demographic and socio-economic profile of the Māori population in Australia using data from the 2011 Australia Census of Population and Housing. The purpose is to provide an evidence base with which to inform future policy approaches with respect to Māori in Australia. It focuses on five key areas: 

Population size and composition; 
Identity and culture; 
Year of arrival and citizenship; 
Education and work; 
Lone parenting and unpaid childcare. 

Comparisons are undertaken with Māori in the 2006 Australia Census, as well as with two reference groups: the total Australia population and migrant non-Māori New Zealanders. Where appropriate, we also distinguish Māori migrants born in New Zealand and Māori born in Australia. This captures important differences within the Māori population in Australia that have been under-examined in previous studies.

year: 2013-06