Abstract. Relation extraction is a part of Information Extraction and an established task in Natural Language Processing. This paper presents an overview of the main directions of research and recent advances in the field. It reviews various techniques used for relation extraction including knowledge-based, supervised and self-supervised methods. We also men-tion applications of relation extraction and identify current trends in the way the field is developing
With the accelerating growth of big data, especially in the healthcare area, information extraction ...
In this dissertation, we study computational models for classification and application of natural la...
In this thesis, we study the importance of background knowledge in relation extraction systems. We n...
Relation extraction is a subtask of information extraction where semantic relationships are extract...
Relation extraction has been considered as one of the most popular topics nowadays, thanks for its c...
Thesis (Ph.D.)--University of Washington, 2012The ability to automatically convert natural language ...
The relation extraction task which aims to identify the relationship between a specified pair of wor...
© 2012 Dr. WillyThe purpose of relation extraction is to identify novel pairs of entities which are ...
This bachelor's thesis deals with relation extraction. Explains basic knowledge, that is necessary f...
International audienceIn this paper we present the main kernel approaches to the problem of relation...
A vast amount of usable electronic data is in the form of unstructured text. The relation extraction...
Most work on ontology learning from text relies on unsupervised methods for relation extraction insp...
Being able to find relevant information about prominent entities quickly is the main reason to use a...
Semantic relations between concepts or entities exist in textual documents, keywords or key phrases,...
Text analytics in the business domain is a growing field in research and practical applications. We ...
With the accelerating growth of big data, especially in the healthcare area, information extraction ...
In this dissertation, we study computational models for classification and application of natural la...
In this thesis, we study the importance of background knowledge in relation extraction systems. We n...
Relation extraction is a subtask of information extraction where semantic relationships are extract...
Relation extraction has been considered as one of the most popular topics nowadays, thanks for its c...
Thesis (Ph.D.)--University of Washington, 2012The ability to automatically convert natural language ...
The relation extraction task which aims to identify the relationship between a specified pair of wor...
© 2012 Dr. WillyThe purpose of relation extraction is to identify novel pairs of entities which are ...
This bachelor's thesis deals with relation extraction. Explains basic knowledge, that is necessary f...
International audienceIn this paper we present the main kernel approaches to the problem of relation...
A vast amount of usable electronic data is in the form of unstructured text. The relation extraction...
Most work on ontology learning from text relies on unsupervised methods for relation extraction insp...
Being able to find relevant information about prominent entities quickly is the main reason to use a...
Semantic relations between concepts or entities exist in textual documents, keywords or key phrases,...
Text analytics in the business domain is a growing field in research and practical applications. We ...
With the accelerating growth of big data, especially in the healthcare area, information extraction ...
In this dissertation, we study computational models for classification and application of natural la...
In this thesis, we study the importance of background knowledge in relation extraction systems. We n...