Efficient access to chemical information contained in scientific literature, patents, technical
reports, or the web is a pressing need shared by researchers and patent attorneys from …

Relational facts are an important component of human knowledge, which are hidden in vast
amounts of text. In order to extract these facts from text, people have been working on …

Recently, prompt-tuning has achieved promising results for specific few-shot classification
tasks. The core idea of prompt-tuning is to insert text pieces (ie, templates) into the input and …

Neural models have achieved remarkable success on relation extraction (RE) benchmarks.
However, there is no clear understanding which type of information affects existing RE …

Witten and Frank's textbook was one of two books that 1 used for a data mining class in the
Fall of 2001. The book covers all major methods of data mining that produce a knowledge …

Decision trees have become one of the most powerful and popular approaches in
knowledge discovery and data mining; it is the science of exploring large and complex …

Neural models optimized for tree-based problems are of great value in tasks like SQL query
extraction and program synthesis. On sequence-structured data, transformers have been …

Recommender systems improve access to relevant products and information by making
personalized suggestions based on previous examples of a user's likes and dislikes. Most …

As deep learning models are applied to increasingly diverse problems, a key bottleneck is
gathering enough high-quality training labels tailored to each task. Users therefore turn to …

Abstract Web Data Extraction is an important problem that has been studied by means of
different scientific tools and in a broad range of applications. Many approaches to extracting …