Motivation: Text mining is increasingly used to manage the accelerating pace of the
biomedical literature. Many text mining applications depend on accurate named entity …

Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of
the training data and updates the parameters in an online fashion. This learning framework …

The biomedical community makes extensive use of text mining technology. In the past
several years, enormous progress has been made in develo** tools and methods, and the …

This paper presents a review of state‐of‐the‐art approaches to automatic extraction of
biomolecular events from scientific texts. Events involving biomolecules such as genes …

Extracting opinion expressions from text is usually formulated as a token-level sequence
labeling task tackled using Conditional Random Fields (CRFs). CRFs, however, do not …

Motivation: Discovering useful associations between biomedical concepts has been one of
the main goals in biomedical text-mining, and understanding their biomedical contexts is …

To process data like text and speech, Natural Language Processing (NLP) is a valuable tool.
As on of NLP's upstream tasks, sequence labeling is a vital part of NLP through techniques …

Natural language processing is a useful processing technique of language data, such as
text and speech. Sequence labeling represents the upstream task of many natural language …

This paper proposes a method for handwritten Chinese/Japanese text (character string)
recognition based on semi-Markov conditional random fields (semi-CRFs). The high-order …

Named entity recognition (NER), which focuses on the extraction of semantically meaningful
named entities and their semantic classes from text, serves as an indispensable component …