Abstract: A method for text mining from one or more tables is provided. The method includes the steps of: receiving one or more tables, the tables having one or more table labels, and one or more cells to be processed, transforming each of the cells into cell vector representations; encoding the one or more cell vector representations with a sequential 2D model; obtaining one or more table-level vector representations by summarising the semantics of the cell vector representations by an image classification model; and mapping the output of to an output vector which represents the probability of each of the table labels.

Abstract: Methods, systems, and non-transitory media for training a chemical entity recognition system to extract chemical compounds from a patent document and determine a relevance of the chemical compounds to the patent document are disclosed. A method includes obtaining patent documents from patent databases, normalizing each patent document into a unified format, and generating a chemical patent corpus. The chemical patent corpus includes chemical entities, each having relevancy annotations that indicate a relevance to the patent document from which the chemical entity is extracted.

Abstract: Methods, systems, and non-transitory media for training a chemical entity recognition system to extract chemical compounds from a patent document and determine a relevance of the chemical compounds to the patent document are disclosed. A method includes obtaining patent documents from patent databases, normalizing each patent document into a unified format, and generating a chemical patent corpus. The chemical patent corpus includes chemical entities, each having relevancy annotations that indicate a relevance to the patent document from which the chemical entity is extracted.