Essays about: "Wikipedia data"
Showing result 1 - 5 of 40 essays containing the words Wikipedia data.
-
1. Multilingual Text Robots for Abstract Wikipedia – Using Grammatical Framework to generate multilingual articles on Swedish localities
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : The vast amount of Wikipedia articles and languages has resulted in a high cost of Wikipedia, i.e. the required time and dedication for making every article available in every language. READ MORE
-
2. Mitigating Unintended Bias in Toxic Comment Detection using Entropy-based Attention Regularization
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The proliferation of hate speech is a growing challenge for social media platforms, as toxic online comments can have dangerous consequences also in real life. There is a need for tools that can automatically and reliably detect hateful comments, and deep learning models have proven effective in solving this issue. READ MORE
-
3. Generating Wikipedia Articles with Grammatical Framework : A Case Study
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Natural language generation is a method used to produce understandable texts in human languages from data [1]. Grammatical Framework is a grammar formalism and a functional programming language using a nonstatistical approach to build natural language applications. READ MORE
-
4. Topical Classification of Images in Wikipedia : Development of topical classification models followed by a study of the visual content of Wikipedia
University essay from Linköpings universitet/DatorseendeAbstract : With over 53 million articles and 11 million images, Wikipedia is the greatest encyclopedia in history. The number of users is equally significant, with daily views surpassing 1 billion. Such an enormous system needs automation of tasks to make it possible for the volunteers to maintain. READ MORE
-
5. Synthetic data generation for domain adaptation of a retriever-reader Question Answering system for the Telecom domain : Comparing dense embeddings with BM25 for Open Domain Question Answering
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Having computer systems capable of answering questions has been a goal within Natural Language Processing research for many years. Machine Learning systems have recently become increasingly proficient at this task with large language models obtaining state-of-the-art performance. READ MORE