Semantic similarity detection is a fundamental task in natural language understanding.
Adding topic information has been useful for previous feature-engineered semantic similarity …

Bidirectional Encoder Representations from Transformers (BERT) and BERT-based
approaches are the current state-of-the-art in many natural language processing (NLP) …

Increasing amounts of freely available data both in textual and relational form offers
exploration of richer document representations, potentially improving the model …

In the era of social networking platforms, user-generated content is flooding every second on
online social media platforms like Facebook. So observing and identifying many contents …

The wide spread of fake news and its negative impacts on society has attracted a lot of
attention to fake news detection. In existing fake news detection methods, particular attention …

Text Classification is the most essential and fundamental problem in Natural Language
Processing. While numerous recent text classification models applied the sequential deep …

We present a memory-augmented approach to condition an autoregressive language model
on a knowledge graph. We represent the graph as a collection of relation triples and retrieve …

Introduction Science educators use writing assignments to assess competencies and
facilitate learning processes such as conceptual understanding or reflective thinking. Writing …

Computer-based analysis of preservice teachers' written reflections could enable
educational scholars to design personalized and scalable intervention measures to support …

The goal of this paper is to provide an overview of the methods that allow text
representations with a focus on embeddings for text of different lengths, specifically on works …