BMCBI
2008
13 years 4 months ago
2008
Background: Relationships between entities such as genes, chemicals, metabolites, phenotypes and diseases in MEDLINE are often directional. That is, one may affect the other in a ...
BMCBI
2008
13 years 4 months ago
2008
Background: The Clinical E-Science Framework (CLEF) project has built a system to extract clinically significant information from the textual component of medical records in order...
EMNLP
2006
13 years 5 months ago
2006
We present an approach for the joint extraction of entities and relations in the context of opinion recognition and analysis. We identify two types of opinion-related entities -- ...
ACL
2006
13 years 5 months ago
2006
This paper proposes a novel composite kernel for relation extraction. The composite kernel consists of two individual kernels: an entity kernel that allows for entity-related feat...
ACL
2006
13 years 5 months ago
2006
Shortage of manually labeled data is an obstacle to supervised relation extraction methods. In this paper we investigate a graph based semi-supervised learning algorithm, a label ...
NAACL
2007
13 years 5 months ago
2007
Relation extraction is the task of finding semantic relations between entities from text. The state-of-the-art methods for relation extraction are mostly based on statistical lea...
LREC
2008
13 years 6 months ago
2008
The IDEX system is a prototype of an interactive dynamic Information Extraction (IE) system. A user of the system expresses an information request in the form of a topic descripti...
LREC
2008
13 years 6 months ago
2008
Relation extraction is the task of finding pre-defined semantic relations between two entities or entity mentions from text. Many methods, such as feature-based and kernel-based m...
EMNLP
2007
13 years 6 months ago
2007
This paper proposes a tree kernel with contextsensitive structured parse tree information for relation extraction. It resolves two critical problems in previous tree kernels for r...
COLING
2008
13 years 6 months ago
2008
We propose a new integrated approach based on Markov logic networks (MLNs), an effective combination of probabilistic graphical models and firstorder logic for statistical relatio...