Named Entity Recognition (NER) is a key component in NLP systems for question
answering, information retrieval, relation extraction, etc. NER systems have been studied …

Insider threats, as one type of the most challenging threats in cyberspace, usually cause
significant loss to organizations. While the problem of insider threat detection has been …

Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …

Motivation Text mining has become an important tool for biomedical research. The most
fundamental text-mining task is the recognition of biomedical named entities (NER), such as …

Motivation In biomedical research, chemical is an important class of entities, and chemical
named entity recognition (NER) is an important task in the field of biomedical information …

Anomaly detection in hyperspectral images (HSIs) faces various levels of difficulty due to the
high dimensionality, redundant information and deteriorated bands. To address these …

Background Previous state-of-the-art systems on Drug Name Recognition (DNR) and
Clinical Concept Extraction (CCE) have focused on a combination of text “feature …

Drug-Named Entity Recognition (DNER) for biomedical literature is a fundamental facilitator
of Information Extraction. For this reason, the DDIExtraction2011 (DDI2011) and …

Distributed vector representations or embeddings map variable length text to dense fixed
length vectors as well as capture prior knowledge which can transferred to downstream …

Abstract In the Internet of Things (IoT) ecosystem, devices will predominate, using it in a
manner similar to how people used it. Devices will cooperating in a multicast network to …