title: Learning collocations with FLAX apps

authors: Yu, Alex

subjects: computer science

abstract: The rise of Mobile Assisted Language Learning has brought a new dimension and dynamic into language classes. Game-like apps have become a particularly effective way to promote self-learning to young learners outside classroom. This paper describes a system called FLAX that allows teachers to automatically generate a variety of collocation games from a con-temporary collocation database built from Wikipedia text. These games are fun to play and mimic traditional classroom activities such as Collocation Matching, Collocation Guessing, Collocation Dominoes, and Related Words. The apps can be downloaded onto Android devices from the Google Play store, and exercises are automatically updated whenever new materials are added by teachers through a web-based interface on the FLAX server. Teachers have used these games to provide supplementary material for several Massive Open Online courses (MOOC) in Law discipline.

text: Learning collocations with FLAX apps The rise of Mobile Assisted Language Learning has brought a new dimension and dynamic into language classes. Game-like apps have become a particularly effective way to promote self-learning to young learners outside classroom. This paper describes a system called FLAX that allows teachers to automatically generate a variety of collocation games from a con-temporary collocation database built from Wikipedia text. These games are fun to play and mimic traditional classroom activities such as Collocation Matching, Collocation Guessing, Collocation Dominoes, and Related Words. The apps can be downloaded onto Android devices from the Google Play store, and exercises are automatically updated whenever new materials are added by teachers through a web-based interface on the FLAX server. Teachers have used these games to provide supplementary material for several Massive Open Online courses (MOOC) in Law discipline.

year: 2016

title: Company formation in the Te Aroha mining district in the 1930s

authors: Hart, Philip

abstract: During the early years of the Depression, a few investors sought to form companies to rework almost every portion of the Te Aroha Mining District. Some flotations failed, and even when companies were formed very little work was done. A wide variety of people were promoters and investors, very few of whom had any mining knowledge or access to capital. Competition for ground and low commercial morality led to conflicts and exaggerated claims (notably that Te Aroha’s lodes were linked to Karangahake and Waihi). The Mines Department, anxious to prevent misinformation about these ventures being used to extract money from the gullible and also anxious to defend the industry from harm, was concerned about fraudulent assays and misleading reports from self-proclaimed ‘experts’. All these under-capitalized ventures quickly failed, for what little development took place quickly revealed the poverty of the ore.
These syndicates and companies are dealt with chronologically.

text: Company formation in the Te Aroha mining district in the 1930s During the early years of the Depression, a few investors sought to form companies to rework almost every portion of the Te Aroha Mining District. Some flotations failed, and even when companies were formed very little work was done. A wide variety of people were promoters and investors, very few of whom had any mining knowledge or access to capital. Competition for ground and low commercial morality led to conflicts and exaggerated claims (notably that Te Aroha’s lodes were linked to Karangahake and Waihi). The Mines Department, anxious to prevent misinformation about these ventures being used to extract money from the gullible and also anxious to defend the industry from harm, was concerned about fraudulent assays and misleading reports from self-proclaimed ‘experts’. All these under-capitalized ventures quickly failed, for what little development took place quickly revealed the poverty of the ore.
These syndicates and companies are dealt with chronologically.

year: 2016

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