Now showing items 1-4 of 4

  • Thumbnail

    A Cold-start Hybrid Context Recommendation System for Casual Restaurant 

    Pimchanok Patumchat; พิมพ์ชนก ปทุมชาติ; Worapol Pongpech; วรพล พงษ์เพ็ชร; National Institute of Development Administration. School of Applied Statistics; Worapol Pongpech; วรพล พงษ์เพ็ชร (National Institute of Development Administration, 13/8/2021)

    Recommendation systems are used in a variety of industries. The goal of these systems is to identify satisfying selections of items for users. Traditional approaches are classified into several methods, such as Collaborative Filtering and Content-based Filtering. However, significant problems such as scalability, data sparsity, and cold-start are still observed. In this paper, we focused on the cold-start problem for new users. We introduced a hybrid-approach by combining demographic and similarity age functions, together with machine learning ...
  • Thumbnail

    Proximal Policy Optimization on Casual Restaurant Raw Material Stock 

    Nutthawat Ekthammanit; ณัฐวัฒน์ เอกธรรมนิตย์; Worapol Pongpech; วรพล พงษ์เพ็ชร; National Institute of Development Administration. School of Applied Statistics; Worapol Pongpech; วรพล พงษ์เพ็ชร (National Institute of Development Administration, 13/8/2021)

    This research focuses on the Proximal Policy Optimization Algorithm (PPO) of Reinforcement Learning to make a forecasting model of raw material stock in restaurants.  The restaurant's daily raw material stock ordered and the number of raw material stock used fluctuates daily. The unused raw material stock is left as wasted material. It caused fermentation and produced methane gas that rises to destroy ozone into the atmosphere. This research investigated a One-Attribute Model and a Multi-Attribute Model. The dataset used in this research is ...
  • Thumbnail

    SEQUENTIAL MODEL-BASED OPTIMIZATION FOR NATURAL LANGUAGE PROCESSING DATA PIPELINE SELECTION AND OPTIMIZATION 

    Piyadanai Arntong; ปิยะดนัย อานทอง; Worapol Pongpech; วรพล พงษ์เพ็ชร; National Institute of Development Administration. School of Applied Statistics; Worapol Pongpech; วรพล พงษ์เพ็ชร (National Institute of Development Administration, 7/1/2022)

    Natural language processing (NLP) aims to analyze a large amount of natural language data. The NLP computes textual data via a set of data processing elements which is sequentially connected to a path data pipeline. Several data pipelines exist for a given set of textual data with various degrees of model accuracy. Instead of trying all the possible paths, such as random search or grid search to find an optimal path, we utilized the Bayesian optimization to search along with the space of hyper-parameters learning. In this study, we proposed a ...
  • Thumbnail

    Using Video Analytic to Improve Customer Service Process Efficiency 

    Puttipong Chanchaem; พุฒิพงศ์ จันทร์แจ่ม; Worapol Pongpech; วรพล พงษ์เพ็ชร; National Institute of Development Administration. School of Applied Statistics; Worapol Pongpech; วรพล พงษ์เพ็ชร (National Institute of Development Administration, 13/8/2021)

    There are many ways to evaluate the customers' service processes efficiency of the casual dining restaurant. One of which is the service speed measured by the amount of time a customer spends waiting for service during each service period. Currently, the object detection system based on deep learning techniques is constantly evolving and high accuracy. In general, restaurants are equipped with more CCTV to apply that information to the employee's service detection techniques. This research aims to develop and improve customer service by monitoring ...