Term Representation

Term representation focuses on developing effective numerical encodings of words or phrases to capture their semantic meaning and relationships for various downstream tasks. Current research emphasizes improving these representations by incorporating contextual information from large language models, leveraging hierarchical structures within data, and addressing biases in ranked lists through novel fairness metrics. These advancements are crucial for improving applications such as entity matching, personalized search, and biomedical knowledge graph construction, ultimately leading to more accurate and unbiased results in diverse fields.