E-Commerce recommender demo with real-time data and a graph database

Overview

🔍 E-Commerce recommender demo 🔍

license build

Follow @memgraphdb Discord

This is a simple stream setup that uses Memgraph to ingest real-time data from a simulated online store. Data is streamed via Redpanda and Pulsar.

Data model

ecommerce-model

Usage

Prerequisites

You will need:

Running the app

1. First, remove possibly running containers:

docker-compose rm -fs

2. Build all the needed images:

docker-compose build

3. Start the Redpanda and Apache Pulsar services:

docker-compose up -d core

4. Start the data stream:

docker-compose up stream

5. Start Memgraph:

docker-compose up memgraph-mage

Creating the streams in Memgraph

1. First, we will create a stram for consuming product views:

CREATE PULSAR STREAM views
TOPICS views
TRANSFORM ecommerce.view
SERVICE_URL "pulsar://pulsar:6650";

2. Another stream is needed to consume product review:

CREATE KAFKA STREAM ratings
TOPICS ratings
TRANSFORM ecommerce.rating
BOOTSTRAP_SERVERS "redpanda:29092";

3. Now, we can start the streams:

START ALL STREAMS;

4. Check if the streams are running correctly:

SHOW STREAMS;

Generating recommendations

You can generate a product recommendation by running:

MATCH (u:User {id: "1"})-[r:RATED]-(p:Product)
      -[other_r:RATED]-(other:User)
WITH other.id AS other_id,
     avg(r.rating-other_r.rating) AS similarity,
     count(*) AS similar_user_count,
     u.id AS user
ORDER BY similarity
LIMIT 10
WITH collect(other_id) AS similar_user_set, user
MATCH (some_product: Product)-[fellow_rate:RATED]-(fellow_user:User)
WHERE fellow_user.id IN similar_user_set
WITH some_product, avg(fellow_rate.rating) AS prediction_score, user
RETURN some_product.name AS Name, prediction_score, user
ORDER BY prediction_score DESC;
Owner
g-despot
Developer @ Memgraph | Computer Science Graduate
g-despot
A library of Recommender Systems

A library of Recommender Systems This repository provides a summary of our research on Recommender Systems. It includes our code base on different rec

MilaGraph 980 Jan 05, 2023
[ICDMW 2020] Code and dataset for "DGTN: Dual-channel Graph Transition Network for Session-based Recommendation"

DGTN: Dual-channel Graph Transition Network for Session-based Recommendation This repository contains PyTorch Implementation of ICDMW 2020 (NeuRec @ I

Yujia 25 Nov 17, 2022
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

QRec is a Python framework for recommender systems (Supported by Python 3.7.4 and Tensorflow 1.14+) in which a number of influential and newly state-of-the-art recommendation models are implemented.

Yu 1.4k Dec 27, 2022
Mutual Fund Recommender System. Tailor for fund transactions.

Explainable Mutual Fund Recommendation Data Please see 'DATA_DESCRIPTION.md' for mode detail. Recommender System Methods Baseline Collabarative Fiilte

JHJu 2 May 19, 2022
Codes for AAAI'21 paper 'Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation'

DHCN Codes for AAAI 2021 paper 'Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation'. Please note that the default link

Xin Xia 124 Dec 14, 2022
This library intends to be a reference for recommendation engines in Python

Crab - A Python Library for Recommendation Engines

Marcel Caraciolo 85 Oct 04, 2021
Self-supervised Graph Learning for Recommendation

SGL This is our Tensorflow implementation for our SIGIR 2021 paper: Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian,and Xing

151 Dec 20, 2022
It is a movie recommender web application which is developed using the Python.

Movie Recommendation 🍿 System Watch Tutorial for this project Source IMDB Movie 5000 Dataset Inspired from this original repository. Features Simple

Kushal Bhavsar 10 Dec 26, 2022
Bert4rec for news Recommendation

News-Recommendation-system-using-Bert4Rec-model Bert4rec for news Recommendation

saran pandian 2 Feb 04, 2022
Incorporating User Micro-behaviors and Item Knowledge 59 60 3 into Multi-task Learning for Session-based Recommendation

MKM-SR Incorporating User Micro-behaviors and Item Knowledge into Multi-task Learning for Session-based Recommendation Paper data and code This is the

ciecus 38 Dec 05, 2022
The implementation of the submitted paper "Deep Multi-Behaviors Graph Network for Voucher Redemption Rate Prediction" in SIGKDD 2021 Applied Data Science Track.

DMBGN: Deep Multi-Behaviors Graph Networks for Voucher Redemption Rate Prediction The implementation of the accepted paper "Deep Multi-Behaviors Graph

10 Jul 12, 2022
NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs.

NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in

420 Jan 04, 2023
Spotify API Recommnder System

This project will access your last listened songs on Spotify using its API, then it will request the user to select 5 favorite songs in that list, on which the API will proceed to make 50 recommendat

Kevin Luke 1 Dec 14, 2021
A movie recommender which recommends the movies belonging to the genre that user has liked the most.

Content-Based-Movie-Recommender-System This model relies on the similarity of the items being recommended. (I have used Pandas and Numpy. However othe

Srinivasan K 0 Mar 31, 2022
Recommendation System to recommend top books from the dataset

recommendersystem Recommendation System to recommend top books from the dataset Introduction The recom.py is the main program code. The dataset is als

Vishal karur 1 Nov 15, 2021
reXmeX is recommender system evaluation metric library.

A general purpose recommender metrics library for fair evaluation.

AstraZeneca 258 Dec 22, 2022
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems

RecSim NG, a probabilistic platform for multi-agent recommender systems simulation. RecSimNG is a scalable, modular, differentiable simulator implemented in Edward2 and TensorFlow. It offers: a power

Google Research 110 Dec 16, 2022
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph

Jointly Learning Explainable Rules for Recommendation with Knowledge Graph

57 Nov 03, 2022
Cross-Domain Recommendation via Preference Propagation GraphNet.

PPGN Codes for CIKM 2019 paper Cross-Domain Recommendation via Preference Propagation GraphNet. Citation Please cite our paper if you find this code u

Information Retrieval Group, Wuhan University, China 20 Dec 15, 2022
Recommender System Papers

Included Conferences: SIGIR 2020, SIGKDD 2020, RecSys 2020, CIKM 2020, AAAI 2021, WSDM 2021, WWW 2021

RUCAIBox 704 Jan 06, 2023