Hybrid Distance-based, CNN and Bi-LSTM System for Dictionary Expansion

Dictionaries like Wordnet can help in a variety of Natural Language Processing applications by providing additional morphological data. They can be used in Digital Humanities research, building knowledge graphs and other applications. Creating dictionaries from large corpora of texts written in a natural language is a task that has not been a primary focus of research, as other tasks have dominated the field (such as chat-bots), but it can be a very useful tool in analysing texts. Even in the case of contemporary texts, categorizing the words according to their dictionary entry is a complex task, and for less conventional texts (in old or less researched languages) it is even harder to solve this problem automatically. Our task was to create a software that helps in expanding a dictionary containing word forms and tagging unprocessed text. We used a manually created corpus for training and testing the model. We created a combination of Bidirectional Long-Short Term Memory networks, convolutional networks and a distancebased solution that outperformed other existing solutions. While manual post-processing for the tagged text is still needed, it significantly reduces the amount of it

Exploring the historical consciousness of university students regarding the imagined future

Dissertation (MEd (General))--University of Pretoria, 2022.Historical consciousness is not an interpretation of the past but can be seen as the manner in which the past is tied to the present to provide a futuristic perspective. In recent decades, many university students in South Africa may have seen themselves through various lenses of inequality and marginalisation due to South Africa’s troubled past and the legacy it has left. Student-led protests and campaigns such as #FeesMustFall and #RhodesMustFall have highlighted a renewed historical consciousness that university students may have and how they may imagine the future based on the past. Using a qualitative interpretivist approach, this study aimed to explore how official and unofficial historical encounters with the past affect the way in which university students imagine the future. The university students in this study were first-year students who had recently completed their schooling in South Africa and now wished to study education at a tertiary institution in the hope of becoming future teachers. Using a descriptive case study research methodology, data for this study was obtained from a pre-existing 2018 study that used open-ended surveys disseminated to first-year students. One of the twelve questions that made up the open-ended survey was analysed for this study using non-probability purposive sampling. Of the 800 open-ended surveys that were collected in the initial study, I made use of 155 surveys for this study using an inductive data analysis method and open coding. Based on the historical consciousness of the first-year participants, my hope was that a variety of themes would emerge from the data. This provided insight as to whether the youth of South Africa were attempting to model for themselves a future different from the past based on their historical consciousness. While many students romanticised the imagined future, there was also a sense of doom and despair amongst students when imagining the future although some students felt that perhaps the future would be good. Furthermore, the future was imagined through a realist lens in that the students acknowledged that there was work to be done for South Africa to have a bright future. The findings from this study also sought to contribute to the broader field of history and historical consciousness at South African universities and internationally. I also attempted to explore the historical consciousness of university students regarding the imagined future.Humanities EducationMEd (General)Unrestricte