Results 71 to 80 of about 5,797,629 (324)
End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures [PDF]
Annual Meeting of the Association for Computational Linguistics, 2016 We present a novel end-to-end neural model to extract entities and relations between them. Our recurrent neural network based model captures both word sequence and dependency tree substructure information by stacking bidirectional tree-structured LSTM ...
Makoto Miwa, Mohit Bansal
semanticscholar +1 more source
Application of Public Knowledge Discovery Tool (PKDE4J) to Represent Biomedical Scientific Knowledge
Frontiers in Research Metrics and Analytics, 2018 In today’s era of information explosion, extracting entities and their relations in large-scale, unstructured collections of text to better represent knowledge has emerged as a daunting challenge in biomedical text mining.
Min Song +4 more
doaj +1 more source
Using Neural Networks for Relation Extraction from Biomedical Literature
, 2020 Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems.
A Koike +34 more
core +1 more source
Graph Adaptation Network with Domain-Specific Word Alignment for Cross-Domain Relation Extraction
Sensors, 2020 Cross-domain relation extraction has become an essential approach when target domain lacking labeled data. Most existing works adapted relation extraction models from the source domain to target domain through aligning sequential features, but failed to ...
Zhe Wang +5 more
doaj +1 more source
Latent Relational Model for Relation Extraction
, 2019 Analogy is a fundamental component of the way we think and process thought. Solving a word analogy problem, such as mason is to stone as carpenter is to wood, requires capabilities in recognizing the implicit relations between the two word pairs. In this paper, we describe the analogy problem from a computational linguistics point of view and explore ...
Gaetano Rossiello +3 more
openaire +2 more sources
A Machine Learning Filter for the Slot Filling Task
Information, 2018 Slot Filling, a subtask of Relation Extraction, represents a key aspect for building structured knowledge bases usable for semantic-based information retrieval.
Kevin Lange Di Cesare +3 more
doaj +1 more source
Semantic Enhanced Distantly Supervised Relation Extraction via Graph Attention Network
Information, 2020 Distantly Supervised relation extraction methods can automatically extract the relation between entity pairs, which are essential for the construction of a knowledge graph.
Xiaoye Ouyang, Shudong Chen, Rong Wang
doaj +1 more source
Kernelized Hashcode Representations for Relation Extraction
, 2019 Kernel methods have produced state-of-the-art results for a number of NLP tasks such as relation extraction, but suffer from poor scalability due to the high cost of computing kernel similarities between natural language structures.
Cecchi, Guillermo +5 more
core +1 more source
IEEE AccessRelation extraction is a Natural Language Processing task that aims to extract relationships from textual data. It is a critical step for information extraction.
Anushka Swarup +4 more
doaj +1 more source
Cross-relation Cross-bag Attention for Distantly-supervised Relation Extraction
, 2018 Distant supervision leverages knowledge bases to automatically label instances, thus allowing us to train relation extractor without human annotations.
Liu, Liyuan +7 more
core +1 more source