# Comparative Analysis of SAAS Model and NPC Integration for Enhancing VR Shopping Experiences
## 3 Methodology
### Data Collection on Shopping  
This study will focus on collecting and standardizing text-based data related to online shopping actions from several freely available datasets. Our goal is to gather comprehensive and diverse data that precisely reflect authentic user purchasing behaviors and patterns. We will integrate datasets such as the Amazon Product Dataset and Amazon Customer Reviews (Amazon Reviews), together with other relevant open datasets listed in Table 1.  
Sample Data:  
The sample data include user interactions and reviews from the Amazon datasets, which are primarily text-based and provide a wealth of information on user preferences and behaviors. Below is a sample of the data fields from these datasets:  
* Amazon Product Dataset Description: This dataset contains information about products listed on Amazon, including titles, descriptions, categories, and related products. Data Type: Textual data related to product information. Sample Data \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Dataset Name** & **Description** & **Source** & **Number of Records** & **Data Type** \\ \hline \multirow{2}{*}{Amazon Product Dataset} & Metadata about products available on Amazon, including product descriptions, categories, and prices & \multirow{2}{*}{Amazon} & \multirow{2}{*}{\(\sim\)9 million products} & Text \\ \hline \multirow{2}{*}{Amazon Customer Reviews} & Reviews written by Amazon customers, including ratings, product IDs, and review texts & & \\ \hline \multirow{2}{*}{Retail Dataset} & IoT-based smart shopping cart data used for frequent itemset mining & Sensors (Basel, Switzerland) [42] & \multirow{2}{*}{16,469} & \multirow{2}{*}{Transactional} \\ \hline \multirow{2}{*}{Shopping Intention at AI-Powered Retail Stores} & Data on consumer intentions in AI-powered automated retail stores & Journal of Retailing and Consumer Services [43] & \multirow{2}{*}{1250 respondents} & \multirow{2}{*}{Survey} \\ \hline \multirow{2}{*}{Clickstream Data} & Predicts online shopping behavior using clickstream data & Expert Systems with Applications [44] & \multirow{2}{*}{Multiple sessions} & \multirow{2}{*}{Clickstream} \\ \hline \multirow{2}{*}{Shopping Queries Dataset} & Large-scale dataset for improving product search & ArXiv [45] & \multirow{2}{*}{130,000 queries} & \multirow{2}{*}{Text} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The Comparison of Open Shopping Datasets. \"product_id\"; \"B00 YD545 CC\", \"product_type\": \"Electronics\", \"product_description\": \"A high-quality, portable speaker with excellent sound quality.\", \"price\": 49.99 ]
* Amazon Customer Reviews Description: This dataset includes customer reviews for products on Amazon, capturing user opinions, ratings, and review text. Data Type: Textual data related to user reviews. Sample Data { \"user_id\": \"A3R5 OBKS/OM2 IR\", \"review_id\": \"R2G29 SF5K3M22\", \"product_id\": \"B00 YD545 CC\", \"rating\": 5, \"review\": \"Excellent sound quality and very portable!\", \"timestamp\": \"2019-01-02\" ]
* Retail Dataset Description: IoT-based smart shopping cart data used for frequent itemset mining. Data Type: Transactional data capturing shopping behavior. Sample Data { \"transactionID\": \"T12345\", \"items\": [\"OxiClean Versatile Stain Remover\", \"Tide Pods Laundry Detergent\"], \"timestamp\": \"2022-01-15 08:45:00\" ]
* Shopping Intention at AI-Powered Retail Stores Description: Data on consumer intentions in AI-powered automated retail stores. Data Type: Survey data capturing shopping intentions. Sample Data { \"respondentID\": \"R56789\", \"intention\": \"Purchase\", \"productCategory\": \"Laundry\", \"timestamp\": \"2022-01-15 10:00:00\" ]
* Clickstream Data Description: Predicts online shopping behavior using clickstream data. Data Type: Clickstream data capturing user interactions on e-commerce websites.