With the rise of online marketplaces, sellers can easily grow their business by offering their products to a larger number of people. However, this comes with the risk of endangering their reputation, brand trust and profits due to counterfeiting issues.
This talk will present a highly scalable approach able to timely query marketplaces via Web scrapers, analyze and classify the obtained data using ML algorithms and summarize the results through visualizations.
Join us during this Journey to learn how to identify counterfeit products and discover the underlying technical challenges.
13. ANALYSIS
What is a relevant content?
What is a legal/illegal content?
Relevance Detection
14. ANALYSIS
What is a relevant content?
What is a legal/illegal content?
Relevance Detection
manual
text analysis
image features
15. ANALYSIS
What is a relevant content?
What is a legal/illegal content?
Relevance Detection
rule-based
manual
text analysis
feature analysis
manual
text analysis
image features
17. Takeaways
● Counterfeiting is a growing problem
● Python and Machine Learning can help
● Manual intervention is still needed
● The approach can be applied to other scenarios
What’s next?
● More data, more questions to answer
○ Evolutionary analysis
○ Comparative analysis