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» Rigorous Result for the CHKNS Random Graph Model
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COLING
2010
13 years 3 months ago
FactRank: Random Walks on a Web of Facts
Fact collections are mostly built using semi-supervised relation extraction techniques and wisdom of the crowds methods, rendering them inherently noisy. In this paper, we propose...
Alpa Jain, Patrick Pantel
CVPR
2010
IEEE
14 years 4 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
EMNLP
2007
13 years 10 months ago
Lexical Semantic Relatedness with Random Graph Walks
Many systems for tasks such as question answering, multi-document summarization, and information retrieval need robust numerical measures of lexical relatedness. Standard thesauru...
Thad Hughes, Daniel Ramage
LREC
2010
199views Education» more  LREC 2010»
13 years 10 months ago
A Random Graph Walk based Approach to Computing Semantic Relatedness Using Knowledge from Wikipedia
Determining semantic relatedness between words or concepts is a fundamental process to many Natural Language Processing applications. Approaches for this task typically make use o...
Ziqi Zhang, Anna Lisa Gentile, Lei Xia, José...
GCB
1997
Springer
77views Biometrics» more  GCB 1997»
14 years 20 days ago
Statistics of large scale sequence searching
Motivation: Database search programs such as FASTA, BLAST or a rigorous Smith–Waterman algorithm produce lists of database entries, which are assumed to be related to the query....
Rainer Spang, Martin Vingron