activity
20182020
most citedOptimize Cash Collection: Use Machine learning to Predicting Invoice Payment

2 citations · 4 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL2020

Using Meta-Knowledge Mined from Identifiers to Improve Intent Recognition in Neuro-Symbolic Algorithms

Claudio Pinhanez, Paulo Cavalin, Victor Ribeiro +8

In this paper we explore the use of meta-knowledge embedded in intent identifiers to improve intent recognition in conversational systems. As evidenced by the analysis of thousands…

cs.LG20202 cited

Predicting Account Receivables with Machine Learning

Ana Paula Appel, Gabriel Louzada Malfatti, Renato Luiz de Freitas Cunha +2

Being able to predict when invoices will be paid is valuable in multiple industries and supports decision-making processes in most financial workflows. However, due to the complexi…

cs.LG20192 cited

Optimize Cash Collection: Use Machine learning to Predicting Invoice Payment

Ana Paula Appel, Victor Oliveira, Bruno Lima +3

Predicting invoice payment is valuable in multiple industries and supports decision-making processes in most financial workflows. However, the challenge in this realm involves deal…

cs.LG2018

Using link and content over time for embedding generation in Dynamic Attributed Networks

Ana Paula Appel, Renato L. F. Cunha, Charu C. Aggarwal +1

In this work, we consider the problem of combining link, content and temporal analysis for community detection and prediction in evolving networks. Such temporal and content-rich n…

cs.CL2018

Combining Textual Content and Structure to Improve Dialog Similarity

Ana Paula Appel, Paulo Rodrigo Cavalin, Marisa Affonso Vasconcelos +1

Chatbots, taking advantage of the success of the messaging apps and recent advances in Artificial Intelligence, have become very popular, from helping business to improve customer…

cs.SI2018

A Social Network Analysis Framework for Modeling Health Insurance Claims Data

Ana Paula Appel, Vagner F. de Santana, Luis G. Moyano +2

Health insurance companies in Brazil have their data about claims organized having the view only for providers. In this way, they loose the physician view and how they share patien…