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JCIT
2010
149views more  JCIT 2010»
8 years 6 months ago
People Summarization by Combining Named Entity Recognition and Relation Extraction
The two most important tasks in entity information summarization from the Web are named entity recognition and relation extraction. Little work has been done toward an integrated ...
Xiaojiang Liu, Nenghai Yu
WWW
2011
ACM
8 years 7 months ago
From actors, politicians, to CEOs: domain adaptation of relational extractors using a latent relational mapping
We propose a method to adapt an existing relation extraction system to extract new relation types with minimum supervision. Our proposed method comprises two stages: learning a lo...
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuk...
COLING
2010
8 years 7 months ago
Boosting Relation Extraction with Limited Closed-World Knowledge
This paper presents a new approach to improving relation extraction based on minimally supervised learning. By adding some limited closed-world knowledge for confidence estimation...
Feiyu Xu, Hans Uszkoreit, Sebastian Krause, Hong L...
COLING
2010
8 years 7 months ago
Entity-Focused Sentence Simplification for Relation Extraction
Relations between entities in text have been widely researched in the natural language processing and informationextraction communities. The region connecting a pair of entities (...
Makoto Miwa, Rune Sætre, Yusuke Miyao, Jun-i...
COLING
2010
8 years 7 months ago
Exploiting Background Knowledge for Relation Extraction
Relation extraction is the task of recognizing semantic relations among entities. Given a particular sentence supervised approaches to Relation Extraction employed feature or kern...
Yee Seng Chan, Dan Roth
EMNLP
2010
8 years 9 months ago
Collective Cross-Document Relation Extraction Without Labelled Data
We present a novel approach to relation extraction that integrates information across documents, performs global inference and requires no labelled text. In particular, we tackle ...
Limin Yao, Sebastian Riedel, Andrew McCallum
EMNLP
2009
8 years 9 months ago
Convolution Kernels on Constituent, Dependency and Sequential Structures for Relation Extraction
This paper explores the use of innovative kernels based on syntactic and semantic structures for a target relation extraction task. Syntax is derived from constituent and dependen...
Truc-Vien T. Nguyen, Alessandro Moschitti, Giusepp...
ACL
2009
8 years 9 months ago
Composite Kernels For Relation Extraction
The automatic extraction of relations between entities expressed in natural language text is an important problem for IR and text understanding. In this paper we show how differen...
Frank Reichartz, Hannes Korte, Gerhard Paass
ACL
2009
8 years 9 months ago
Multi-Task Transfer Learning for Weakly-Supervised Relation Extraction
Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few see...
Jing Jiang
IPM
2008
159views more  IPM 2008»
8 years 12 months ago
Exploring syntactic structured features over parse trees for relation extraction using kernel methods
Extracting semantic relationships between entities from text documents is challenging in information extraction and important for deep information processing and management. This ...
Min Zhang, Guodong Zhou, AiTi Aw
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