Comparative Study of Loss Functions in Personal Identification for Smartwatch Data: Examining Accuracy of Loss Functions in Personal Identification using Outlier Detection with Auto-encoders on Data from Smartwatches

Smartwatches are equipped with sensors that allow continuous monitoring of physiological and physical activities, making them ideal sources of data for data analysis. However, accurately identifying individuals based on smartwatch data can be challenging due to the presence of outliers. Hence, outlier detection techniques play a crucial part in...

Correspondence Between Perplexity Scores and Human Evaluation of Generated TV-Show Scripts

In recent years many new text generation models have been developed while evaluation of text generation remains a considerable challenge.  Currently, the only metric that is able to fully capture the quality of a generated text is human evaluation, which is expensive and time consuming. One of the most used intrinsic...

Who said that? Comparing performance of TF-IDF and fastText to identify authorship of short sentences

Authorship identification is often applied to large documents, but less so to short, everyday sentences. The ability of identifying who said a short line could provide help to chatbots or personal assistants. This research compares performance of TF-IDF and fastText when identifying authorship of short sentences, by applying these feature...

Is Wikipedia succeeding in reducing gender bias?: Assessing the development of gender bias in word embeddings from Wikipedia

Large text corpora used for creating word embeddings (vectors which represent word meanings) often contain a stereotypical gender bias. This unwanted bias is then also present in the word embeddings and in downstream applications in the field of natural language processing. To prevent and reduce this, more knowledge about the gender bias is...