Learning strategies for story comprehension: a reinforcement learning approach

By Eugene Grois, David C. Wilkins. 2005

6 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Natural Language Processing, Reinforcement Learning

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. C. Burges
2. Matthew Richardson
3. Erin Renshaw
4. Peter Clark
5. Eric P. Xing
6. Mohit Bansal
7. Mrinmaya Sachan
8. Jianfeng Gao

In Information Systems

1. Matthew Richardson
2. Erin Renshaw
3. C. Burges

In Natural Language Processing

1. Matthew Richardson
2. Erin Renshaw
3. C. Burges
4. Peter Clark
5. Eric P. Xing
6. Mrinmaya Sachan
7. Antoine Bordes
8. Mohit Bansal

In Reinforcement Learning

1. Matthew Richardson
2. Erin Renshaw
3. C. Burges

Citations in the corpus

• MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text (2013, methodology): “This dataset spurred several research efforts, for example using reinforcement learning (Grois and Wilkins, 2005), named entity resolution (Harabagiu et al., 2003) and mapping questions and answers to logical form (Wellner et al., 2006).”