Graph Based Recommendations using “How-To” Guides Dataset by Marcel Caraciolo.
From the post:
In this post I’d like to introduce another approach for recommender engines using graph concepts to recommend novel and interesting items. I will build a graph-based how-to tutorials recommender engine using the data available on the website SnapGuide (By the way I am a huge fan and user of this tutorials website), the graph database Neo4J and the graph traversal language Gremlin.
What is SnapGuide ?
Snapguide is a web service for anyone who wants to create and share step-by-step “how to guides”. It is available on the web and IOS app. There you can find several tutorials with easy visual instructions for a wide array of topics including cooking, gardening, crafts, projects, fashion tips and more. It is free and anyone is invitide to submit guides in order to share their passions and expertise with the community. I have extracted from their website for only research purposes the corpus of tutorials likes. Several users may like the tutorial and this signal can be quite useful to recommend similar tutorials based on what other users liked. Unfortunately I can’t provide the dataset for download but the code you can follow below for your own data set.
An excellent tutorial that walks you through the creation of graph based recommendations, from acquiring the data to posting queries to it.
The SnapGuide site looks like another opportunity for topic map related tutorial material.