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Articles 1 - 4 of 4
Full-Text Articles in Business Intelligence
Aspect-Based Sentiment Analysis Of Movie Reviews, Samuel Onalaja, Eric Romero, Bosang Yun
Aspect-Based Sentiment Analysis Of Movie Reviews, Samuel Onalaja, Eric Romero, Bosang Yun
SMU Data Science Review
This study investigates a comparison of classification models used to determine aspect based separated text sentiment and predict binary sentiments of movie reviews with genre and aspect specific driving factors. To gain a broader classification analysis, five machine and deep learning algorithms were compared: Logistic Regression (LR), Naive Bayes (NB), Support Vector Machine (SVM), and Recurrent Neural Network Long-Short-Term Memory (RNN LSTM). The various movie aspects that are utilized to separate the sentences are determined through aggregating aspect words from lexicon-base, supervised and unsupervised learning. The driving factors are randomly assigned to various movie aspects and their impact tied to …
Enhanced Data Science Methods For Freight Optimization At Kelly-Moore Paints, Lance Dacy, Reannan Mcdaniel, Shawn Jung
Enhanced Data Science Methods For Freight Optimization At Kelly-Moore Paints, Lance Dacy, Reannan Mcdaniel, Shawn Jung
SMU Data Science Review
Kelly-Moore Paints is a paint manufacturing company founded in San Carlos, California in 1946 by William Kelly and William Moore. It has stores located in California, Texas, Oklahoma, and Nevada. They currently own 11 42’ trailers, contract 4 distinct drivers, and service 44 stores Monday-Thursday from its Texas Distribution and Manufacturing Center in Hurst, TX. Given that transportation costs are typically the highest in the supply chain costs, this study will employ data science techniques to ensure the transportation routing, store ordering mechanism, and trailer utilization are at the best efficiency possible given the current ordering patters of the stores. …
Automated Analysis Of Rfps Using Natural Language Processing (Nlp) For The Technology Domain, Sterling Beason, William Hinton, Yousri A. Salamah, Jordan Salsman
Automated Analysis Of Rfps Using Natural Language Processing (Nlp) For The Technology Domain, Sterling Beason, William Hinton, Yousri A. Salamah, Jordan Salsman
SMU Data Science Review
Much progress has been made in text analysis, specifically within the statistical domain of Term Frequency (TF) and Inverse Document Frequency (IDF). However, there is much room for improvement especially within the area of discovering Emerging Trends. Emerging Trend Detection Systems (ETDS) depend on ingesting a collection of textual data and TF/IDF to identify new or up-trending topics within the Corpus. However, the tremendous rate of change and the amount of digital information presents a challenge that makes it almost impossible for a human expert to spot emerging trends without relying on an automated ETD system. Since the U.S. Government …
Price Optimization For Revenue Maximization At Scale, Nikhil Gupta, Massimiliano Moro, Kailey A. Ayala, Bivin Sadler
Price Optimization For Revenue Maximization At Scale, Nikhil Gupta, Massimiliano Moro, Kailey A. Ayala, Bivin Sadler
SMU Data Science Review
This study presents a novel approach to price optimization in order to maximize revenue for the distribution market of non-perishable products. Data analysis techniques such as association mining, statistical modeling, machine learning, and an automated machine learning platform are used to forecast the demand for products considering the impact of pricing. The techniques used allow for accurate modeling of the customer’s buying patterns including cross effects such as cannibalization and the halo effect. This study uses data from 2013 to 2019 for Super Premium Whiskey from a large distributor of alcoholic beverages. The expected demand and the ideal pricing strategy …