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» Kernel-based relation extraction from investigative data
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EMNLP
2010
13 years 4 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
ECAI
2006
Springer
13 years 11 months ago
Semantic Tree Kernels to Classify Predicate Argument Structures
Recent work on Semantic Role Labeling (SRL) has shown that syntactic information is critical to detect and extract predicate argument structures. As syntax is expressed by means of...
Alessandro Moschitti, Bonaventura Coppola, Daniele...
SAC
2011
ACM
12 years 10 months ago
Towards discovering criminal communities from textual data
In many criminal cases, forensically collected data contain valuable information about a suspect’s social networks. An investigator often has to manually extract information fro...
Rabeah Al-Zaidy, Benjamin C. M. Fung, Amr M. Youss...
COLT
2003
Springer
14 years 17 days ago
Learning from Uncertain Data
The application of statistical methods to natural language processing has been remarkably successful over the past two decades. But, to deal with recent problems arising in this ï¬...
Mehryar Mohri
VLDB
2007
ACM
144views Database» more  VLDB 2007»
14 years 1 months ago
A Relational Approach to Incrementally Extracting and Querying Structure in Unstructured Data
There is a growing consensus that it is desirable to query over the structure implicit in unstructured documents, and that ideally this capability should be provided incrementally...
Eric Chu, Akanksha Baid, Ting Chen, AnHai Doan, Je...