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» Word Importance Discrimination Using Context Information
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CICLING
2005
Springer
14 years 29 days ago
Name Discrimination by Clustering Similar Contexts
It is relatively common for different people or organizations to share the same name. Given the increasing amount of information available online, this results in the ever growing...
Ted Pedersen, Amruta Purandare, Anagha Kulkarni
CVPR
2007
IEEE
14 years 9 months ago
Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data
A popular approach to problems in image classification is to represent the image as a bag of visual words and then employ a classifier to categorize the image. Unfortunately, a si...
Liu Yang, Rong Jin, Caroline Pantofaru, Rahul Sukt...
COLING
2010
13 years 2 months ago
Robust Measurement and Comparison of Context Similarity for Finding Translation Pairs
In cross-language information retrieval it is often important to align words that are similar in meaning in two corpora written in different languages. Previous research shows tha...
Daniel Andrade, Tetsuya Nasukawa, Jun-ichi Tsujii
ACL
2012
11 years 9 months ago
Improving Word Representations via Global Context and Multiple Word Prototypes
Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
Eric H. Huang, Richard Socher, Christopher D. Mann...
ACL
2006
13 years 8 months ago
Discriminative Pruning of Language Models for Chinese Word Segmentation
This paper presents a discriminative pruning method of n-gram language model for Chinese word segmentation. To reduce the size of the language model that is used in a Chinese word...
Jianfeng Li, Haifeng Wang, Dengjun Ren, Guohua Li