Learning to rank for quantity consensus queries

By Somnath Banerjee, Soumen Chakrabarti, Ganesh Ramakrishnan. 2009

30 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Information Retrieval & Search

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Subhro Roy
2. Dan Roth
3. Partha P. Talukdar
4. Tim Vieira
5. Koby Crammer
6. Lei Wang
7. William W. Cohen
8. Mohit Bansal

In Information Systems

1. Dan Roth
2. Subhro Roy
3. Koby Crammer
4. Tim Vieira
5. Partha P. Talukdar
6. Wei Dang Lu
7. Zhipeng Xie
8. Shichao Sun

In Information Retrieval & Search

1. Dan Roth
2. Koby Crammer
3. Subhro Roy
4. Tim Vieira
5. Partha P. Talukdar

Citations in the corpus

• Reasoning about Quantities in Natural Language (2015, methodology): “We then use these capabilities to further develop algorithms to assist reasoning in the context of the aforementioned tasks.”
• New Regularized Algorithms for Transductive Learning (2009, methodology): “Adsorption [1] is a general algorithmic framework for transductive learning where the learner is often given a small set of labeled examples and a very large set of unlabeled examples.”