Search Results for author:
Found 11 papers, 6 papers with code
Understanding transit ridership in an equity context through a comparison of statistical and machine learning algorithms
Building an accurate model of travel behaviour based on individuals' characteristics and built environment attributes is of importance for policy-making and transportation planning.
ADPTriage: Approximate Dynamic Programming for Bug Triage
In this study, we develop a Markov decision process (MDP) model for an online bug triage task.
S-DABT: Schedule and Dependency-Aware Bug Triage in Open-Source Bug Tracking Systems
We further incorporate the schedule of developers in our formulation to have a more comprehensive model for this multifaceted problem.
Text Classification for Predicting Multi-level Product Categories
In our experiments, we investigate the generalizability of the trained models to the products of other online retailers, the dynamic masking of infeasible subcategories for pretrained language models, and the benefits of incorporating product titles in multiple languages.
Auto Response Generation in Online Medical Chat Services
These services have become gradually popular over the years with the advent of necessary technological infrastructure.
DABT: A Dependency-aware Bug Triaging Method
In software engineering practice, fixing a bug promptly reduces the associated costs.
A Deep Reinforcement Learning Approach for the Meal Delivery Problem
We consider a meal delivery service fulfilling dynamic customer requests given a set of couriers over the course of a day.
Predicting the Number of Reported Bugs in a Software Repository
We observe that LSTM is effective when considering long-run predictions whereas Random Forest Regressor enriched by exogenous variables performs better for predicting the number of bugs in the short term.
Does chronology matter in JIT defect prediction? A Partial Replication Study
In this work, we aim to investigate the effect of code change properties on JIT models over time.
Moving from Cross-Project Defect Prediction to Heterogeneous Defect Prediction: A Partial Replication Study
Our main goal is to extend prior research and explore the feasibility of HDP and finally to compare its performance with that of its predecessor, Cross-Project Defect Prediction.
nTreeClus: a Tree-based Sequence Encoder for Clustering Categorical Series
This paper proposes a new Model-based approach for clustering sequence data, namely nTreeClus.
