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» Reducing Wrong Labels in Distant Supervision for Relation Ex...
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ACL
2012
11 years 7 months ago
Reducing Wrong Labels in Distant Supervision for Relation Extraction
In relation extraction, distant supervision seeks to extract relations between entities from text by using a knowledge base, such as Freebase, as a source of supervision. When a s...
Shingo Takamatsu, Issei Sato, Hiroshi Nakagawa
ACL
2009
13 years 2 months ago
Distant supervision for relation extraction without labeled data
Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that ...
Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafs...
AAAI
2012
11 years 7 months ago
Ontological Smoothing for Relation Extraction with Minimal Supervision
Relation extraction, the process of converting natural language text into structured knowledge, is increasingly important. Most successful techniques use supervised machine learni...
Congle Zhang, Raphael Hoffmann, Daniel S. Weld
EMNLP
2010
13 years 2 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
ICAISC
2010
Springer
13 years 6 months ago
Canonical Correlation Analysis for Multiview Semisupervised Feature Extraction
Hotelling’s Canonical Correlation Analysis (CCA) works with two sets of related variables, also called views, and its goal is to find their linear projections with maximal mutual...
Olcay Kursun, Ethem Alpaydin