A brief survey of text mining: Classification, clustering and extraction techniques

M Allahyari, S Pouriyeh, M Assefi, S Safaei… - arxiv preprint arxiv …, 2017 - arxiv.org
The amount of text that is generated every day is increasing dramatically. This tremendous
volume of mostly unstructured text cannot be simply processed and perceived by computers …

Information retrieval and text mining technologies for chemistry

M Krallinger, O Rabal, A Lourenco, J Oyarzabal… - Chemical …, 2017 - ACS Publications
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 …

[BOOK][B] Handbook of natural language processing

N Indurkhya, FJ Damerau - 2010 - taylorfrancis.com
The Handbook of Natural Language Processing, Second Edition presents practical tools
and techniques for implementing natural language processing in computer systems. Along …

[HTML][HTML] Bidirectional RNN for medical event detection in electronic health records

AN Jagannatha, H Yu - Proceedings of the conference. Association …, 2016 - ncbi.nlm.nih.gov
Sequence labeling for extraction of medical events and their attributes from unstructured text
in Electronic Health Record (EHR) notes is a key step towards semantic understanding of …

[PDF][PDF] Biomedical named entity recognition using conditional random fields and rich feature sets

B Settles - Proceedings of the international joint workshop on …, 2004 - aclanthology.org
As the wealth of biomedical knowledge in the form of literature increases, there is a rising
need for effective natural language processing tools to assist in organizing, curating, and …

[BOOK][B] Representation learning for natural language processing

Z Liu, Y Lin, M Sun - 2023 - library.oapen.org
This book provides an overview of the recent advances in representation learning theory,
algorithms, and applications for natural language processing (NLP), ranging from word …

Literature mining for the biologist: from information retrieval to biological discovery

LJ Jensen, J Saric, P Bork - Nature reviews genetics, 2006 - nature.com
For the average biologist, hands-on literature mining currently means a keyword search in
PubMed. However, methods for extracting biomedical facts from the scientific literature have …

[BOOK][B] Ontology learning from text: methods, evaluation and applications

P Buitelaar, P Cimiano, B Magnini - 2005 - books.google.com
This volume brings together ontology learning, knowledge acquisition and other related
topics. It presents current research in ontology learning, addressing three perspectives. The …

Comparative experiments on learning information extractors for proteins and their interactions

R Bunescu, R Ge, RJ Kate, EM Marcotte… - Artificial intelligence in …, 2005 - Elsevier
OBJECTIVE:: Automatically extracting information from biomedical text holds the promise of
easily consolidating large amounts of biological knowledge in computer-accessible form …

GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text

Q Zhu, X Li, A Conesa, C Pereira - Bioinformatics, 2018 - academic.oup.com
Motivation Best performing named entity recognition (NER) methods for biomedical literature
are based on hand-crafted features or task-specific rules, which are costly to produce and …