Chinese named entity recognition has been widely used in many fields, such as species
recognition in marine information, and so on. Compared with the standard named entity …

To solve the problem of unclear entity boundaries and low recognition accuracy in Chinese
text, we construct the crop dataset and propose a Bert‐binary‐based entity link method …

Abstract Named Entity Recognition is a system that extracts entity names such as Persons
(PS), Locations (LC), and Organizations (OG) that can have a unique meaning from a …

The proposed model is developed to minimize the loss of information in incomplete data
including missing data. The first step is to transform the learning data to compensate for the …

Abstract Knowledge Graph has gradually become one of core drivers advancing the Internet
and AI in recent years, while there is currently no normal knowledge graph in the field of …

Recently, studies about bilingual word embedding have been gaining much attention.
However, bilingual word embedding with Korean is not actively pursued due to the difficulty …

The most of the IR focus on the method for searching the document, so the keyword-based
IR system is not able to reflect the feature information of the image. In order to overcome …

Abstract Recent approaches to Relation Extraction methods mostly tend to be limited to
mention level relation extractions. These types of methods, while featuring high …

While the number of companion animals is rapidly increasing due to growing interest in pets,
it is still not easy to find disease-related information when a companion animal is sick. In this …

Abstract Multi-Task Learning (MTL) is a training method that trains a single neural network
with multiple tasks influences each other. In this paper, we compare performance of MTL …