title: A distributed alerting service for open digital library software

authors: Hinze, Annika

subjects: computer science

abstract: Alerting for Digital Libraries (DL) is an important and useful feature for the library users. To date, two independent services and a few publisher-hosted proprietary services have been developed. Here, we address the problem of integrating alerting as functionality into open source software for distributed digital libraries. DL software is one application out of many that constitute so-called meta-software: software where its installation determines the properties of the actual running system (here: the Digital Library system). For this type of application, existing alerting solutions are insufficient; new ways have to be found for supporting a fragmented network of distributed digital library servers. We propose the design and usage of a distributed Directory Service. This paper also introduces our hybrid approach using two networks and a combination of different distributed routing strategies for event filtering.

text: A distributed alerting service for open digital library software Alerting for Digital Libraries (DL) is an important and useful feature for the library users. To date, two independent services and a few publisher-hosted proprietary services have been developed. Here, we address the problem of integrating alerting as functionality into open source software for distributed digital libraries. DL software is one application out of many that constitute so-called meta-software: software where its installation determines the properties of the actual running system (here: the Digital Library system). For this type of application, existing alerting solutions are insufficient; new ways have to be found for supporting a fragmented network of distributed digital library servers. We propose the design and usage of a distributed Directory Service. This paper also introduces our hybrid approach using two networks and a combination of different distributed routing strategies for event filtering.

year: 2005

title: Promoting statistical thinking in year 12 multilingual classrooms: a collaborative study

authors: Sharma, Sashi

abstract: There are challenges making connections between language use and mathematics in mathematics education. A lack of connections between the two domains can have negative consequences on student learning and performance. The challenges in statistics classrooms, where language and contexts are important as a medium of instruction, have received little scrutiny. This article reports on collaborative research carried out in three largely Pasifika-dominated year 12 classes. Specifically, we explored the language resources and strategies that appear to enhance the statistical understanding of Pasifika students. Findings from the teacher reflection aspect of the study indicated that some strategies to incorporate student language and communicative resources in their learning worked better than others. Teachers may need to re-evaluate their teaching practices, especially if part of their population is learning English as a second language.

text: Promoting statistical thinking in year 12 multilingual classrooms: a collaborative study There are challenges making connections between language use and mathematics in mathematics education. A lack of connections between the two domains can have negative consequences on student learning and performance. The challenges in statistics classrooms, where language and contexts are important as a medium of instruction, have received little scrutiny. This article reports on collaborative research carried out in three largely Pasifika-dominated year 12 classes. Specifically, we explored the language resources and strategies that appear to enhance the statistical understanding of Pasifika students. Findings from the teacher reflection aspect of the study indicated that some strategies to incorporate student language and communicative resources in their learning worked better than others. Teachers may need to re-evaluate their teaching practices, especially if part of their population is learning English as a second language.

year: 2023-01-01

title: A hybrid architecture for labelling bilingual Māori-English tweets

authors: Trye, David

subjects: borrowing

abstract: Most large-scale language detection tools perform poorly at identifying Māori text. Moreover, rule-based and machine learning-based techniques devised specifically for the Māori-English language pair struggle with interlingual homographs. We develop a hybrid architecture that couples Māori-language orthography with machine learning models in order to annotate mixed Māori-English text. This architecture is used to label a new bilingual Twitter corpus at both the token (word) and tweet (sentence) levels. We use the collected tweets to show that the hybrid approach outperforms existing systems with respect to language detection of interlingual homographs and overall accuracy. We also evaluate its performance on out-of-domain data. Two interactive visualisations are provided for exploring the Twitter corpus and comparing errors across the new and existing techniques. The architecture code and visualisations are available online, and the corpus is available on request.

text: A hybrid architecture for labelling bilingual Māori-English tweets Most large-scale language detection tools perform poorly at identifying Māori text. Moreover, rule-based and machine learning-based techniques devised specifically for the Māori-English language pair struggle with interlingual homographs. We develop a hybrid architecture that couples Māori-language orthography with machine learning models in order to annotate mixed Māori-English text. This architecture is used to label a new bilingual Twitter corpus at both the token (word) and tweet (sentence) levels. We use the collected tweets to show that the hybrid approach outperforms existing systems with respect to language detection of interlingual homographs and overall accuracy. We also evaluate its performance on out-of-domain data. Two interactive visualisations are provided for exploring the Twitter corpus and comparing errors across the new and existing techniques. The architecture code and visualisations are available online, and the corpus is available on request.

year: 2022