P5_beauty_base Open-source Pre-trained Model for Beauty Product Recommendation - Precise Recommendation of Quality Beauty Products for Unified Tasks

P5 Beauty Base

Developed by makitanikaze

P5 is a pre-trained model that unifies recommendation system tasks as text-to-text generation tasks, specifically designed for the beauty domain.

Large Language Model

Transformers

EnglishOpen Source License:MIT #Sequential Recommendation #Explanation Generation #Text-to-Text Generation

Downloads 122

Release Time : 12/20/2022

Model Overview

This model transforms recommendation tasks into language processing tasks, enabling unified handling of various functions such as sequential recommendation, direct recommendation, and explanation generation.

Model Features

Unified Recommendation Paradigm

Unifies different types of recommendation tasks as text-to-text generation tasks

Multi-Task Processing

Simultaneously supports three core recommendation system tasks: sequential recommendation, direct recommendation, and explanation generation

Personalized Prompts

Achieves customized recommendations for different users through personalized prompts

Model Capabilities

Sequential recommendation

Direct recommendation

Explanation generation

Text-to-text generation

Use Cases

E-commerce Recommendation

User Purchase History Analysis

Predicts the next likely product to purchase based on the user's historical purchase sequence

Improves recommendation accuracy and user conversion rate

New Product Recommendation

Selects the most suitable product from a candidate pool to recommend to the user

Helps users discover new products of interest

Product Explanation Generation

Product Feature Description

Generates explanatory descriptions of products based on keywords

Helps users better understand product features

🚀 P5 (Beauty Base)

Recommendation as Language Processing: A Unified Pretrain, Personalized Prompt & Predict Paradigm

This project focuses on sequential recommendation, direct recommendation, explanation generation, and text2text - generation, offering innovative solutions in the field of recommendation systems.

🚀 Quick Start

You can try out the model using the following examples:

Sequential Recommendation

I find the purchase history list of user_823 : 
5255 -> 3001 -> 3771 -> 2973 
I wonder what is the next item to recommend to the user . Can you help me decide ?

Direct Recommendation

Pick the most suitable item from the following list and recommend to user_182 : 
5871 , 3575 , 6355 , 3665 , 7968 , 1054 , 11837 , 9031 , 2643 , 3125 , 11476 , 1529 , 6300 , 11755 , 9410 , 1578 , 5953 , 5042 , 10881 , 2221 , 11286 , 10458 , 2081 , 3722 , 10581 , 5879 , 1780 , 7411 , 5202 , 2082 , 82 , 8131 , 77 , 8097 , 1053 , 9946 , 1341 , 4508 , 2613 , 629 , 4869 , 9833 , 7076 , 6178 , 6679 , 6650 , 472 , 8821 , 4005 , 4184 , 2866 , 4988 , 10759 , 6358 , 4137 , 790 , 5390 , 9330 , 3691 , 2667 , 5620 , 11982 , 4799 , 10062 , 4278 , 4530 , 7944 , 10225 , 1766 , 6657 , 11371 , 305 , 1091 , 7144 , 1869 , 744 , 295 , 91 , 6947 , 9290 , 2977 , 11206 , 1677 , 7812 , 1159 , 1128 , 8762 , 5795 , 8061 , 9639 , 6161 , 2142 , 8124 , 5316 , 10425 , 12097 , 476 , 5710 , 1802 , 8969

Explanation Generation

Based on the feature word shampoo , generate an explanation for user_837 about this product : Dove Nourishing Oil Shampoo, 25.4 Ounce

✨ Features

Sequential Recommendation: Provide item recommendations based on the user's historical purchase sequence.
Direct Recommendation: Select the most suitable item from a given list for a user.
Explanation Generation: Generate product - related explanations for users based on feature words.
Text2Text Generation: Perform various text - to - text generation tasks.

📦 Installation

No installation steps were provided in the original document.

📚 Documentation

Model Information

Property	Details
Model Type	P5 (Beauty Base)
Training Data	amazon_us_reviews
Evaluation Metrics	NDCG, HR, MAE, BLUE, ROUGE

Model Visualization

model image

📄 License

This project is licensed under the MIT license.

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