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DRR
2003
13 years 9 months ago
Information retrieval for OCR documents: a content-based probabilistic correction model
The difficulty with information retrieval for OCR documents lies in the fact that OCR documents comprise of a significant amount of erroneous words and unfortunately most informat...
Rong Jin, ChengXiang Zhai, Alexander G. Hauptmann
NIPS
2004
13 years 9 months ago
Instance-Based Relevance Feedback for Image Retrieval
High retrieval precision in content-based image retrieval can be attained by adopting relevance feedback mechanisms. These mechanisms require that the user judges the quality of t...
Giorgio Giacinto, Fabio Roli
WWW
2008
ACM
14 years 8 months ago
Query-sets: using implicit feedback and query patterns to organize web documents
In this paper we present a new document representation model based on implicit user feedback obtained from search engine queries. The main objective of this model is to achieve be...
Barbara Poblete, Ricardo A. Baeza-Yates
ACL
2007
13 years 9 months ago
Sparse Information Extraction: Unsupervised Language Models to the Rescue
Even in a massive corpus such as the Web, a substantial fraction of extractions appear infrequently. This paper shows how to assess the correctness of sparse extractions by utiliz...
Doug Downey, Stefan Schoenmackers, Oren Etzioni
ECIR
2009
Springer
14 years 5 months ago
Risk-Aware Information Retrieval
Probabilistic retrieval models usually rank documents based on a scalar quantity. However, such models lack any estimate for the uncertainty associated with a document’s rank. Fu...
Jianhan Zhu, Jun Wang, Michael J. Taylor, Ingemar ...