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» Extracting and Ranking Product Features in Opinion Documents
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TREC
2008
13 years 9 months ago
IIT Kharagpur at TREC 2008 Blog Track
This paper describes our opinion retrieval system for TREC 2008 blog track. We focused on five different aspects of the system. The first module is focussed on extracting the blog...
Robin Anil, Sudeshna Sarkar
RULEML
2004
Springer
14 years 1 months ago
Rule Learning for Feature Values Extraction from HTML Product Information Sheets
The Web is now a huge information repository with a rich semantic structure that, however, is primarily addressed to human understanding rather than automated processing by a compu...
Costin Badica, Amelia Badica
CICLING
2011
Springer
12 years 11 months ago
Ranking Multilingual Documents Using Minimal Language Dependent Resources
This paper proposes an approach of extracting simple and effective features that enhances multilingual document ranking (MLDR). There is limited prior research on capturing the co...
G. S. K. Santosh, N. Kiran Kumar, Vasudeva Varma
CIKM
2008
Springer
13 years 9 months ago
A random walk on the red carpet: rating movies with user reviews and pagerank
Although PageRank has been designed to estimate the popularity of Web pages, it is a general algorithm that can be applied to the analysis of other graphs other than one of hypert...
Derry Tanti Wijaya, Stéphane Bressan
EMNLP
2007
13 years 9 months ago
Enhancing Single-Document Summarization by Combining RankNet and Third-Party Sources
We present a new approach to automatic summarization based on neural nets, called NetSum. We extract a set of features from each sentence that helps identify its importance in the...
Krysta Marie Svore, Lucy Vanderwende, Christopher ...