Papers by Ana Appel
Improving Out-of-Scope Detection in Intent Classification by Using Embeddings of the Word Graph Space of the Classes (2020.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods for intent classification use one-class classification or inverse dictionary. |
| Approach: | They propose to represent class labels as a vector space where word graphs are mapped . they use inverse dictionary to take in account inter-class similarities provided by repeated occurrences . |
| Outcome: | The proposed method beats the state-of-the-art method in the Larson dataset by about 31 percentage points. |
Using Meta-Knowledge Mined from Identifiers to Improve Intent Recognition in Conversational Systems (2021.acl-long)
Copied to clipboard
Claudio Pinhanez, Paulo Cavalin, Victor Henrique Alves Ribeiro, Ana Appel, Heloisa Candello, Julio Nogima, Mauro Pichiliani, Melina Guerra, Maira de Bayser, Gabriel Malfatti, Henrique Ferreira
| Challenge: | a recent study shows that meta-knowledge embedded in intent identifiers improves intent recognition in conversational systems . a meta-learning approach is used to classify sentences into discrete sets of classes . classification is a key part of professional conversational system implementations . |
| Approach: | They use meta-knowledge embedded in intent identifiers to improve intent recognition . authors found that meta-knowledge improved accuracy in conversational systems . |
| Outcome: | The meta-knowledge enabled improved intent recognition in conversational systems . the meta-learning improved the false acceptance rate in two thirds of the chatbots . |