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eBay ShopBot: Graph-powered Conversational Commerce

Ajinkya Kale of eBay discusses their use of Neo4j as a backend to the AI technology in eBay's virtual shopping assistant: eBay ShopBot. The team discusses how they used Neo4j as a probabilistic graph model to drive conversations based upon their Knowledge Graph. They also touch upon the key learnings for deployment and scalability in Google Cloud Platform, and touch upon the application oriented learnings of using Neo4j for a year in production. 


Role of Spark in transforming eBay’s Enterprise Data Platform

eBay has one of the most mature Enterprise Data Platform’s in the industry with over 200PBs of data stored in Hadoop and Teradata Warehouses. On average 30 TB of transactional and behavioral data is extracted on a daily basis and thousands of metrics are computed, analyzed and monitored for decision making and detecting anomalies. eBay has embarked on an ambitious project to transform the batch oriented ETL processes which could take 24 to 48 hour for metric computation to near real time infrastructure based on Kafka for messaging, Spark Streaming for stream processing and Spark SQL for data preparation.


Needle in the Haystack—User Behavior Anomaly Detection for Information Security

Salesforce recently invented and deployed a real-time, scalable, terabyte data-level and low false positive personalized anomaly detection system. Anomaly detection on user in-app behavior at terabyte-data scale is extremely challenging because traditional techniques like clustering methods suffer serious production performance issues.


Maintaining Simplicity in a Log Based System

FashionTrade uses relies heavily on Kafka based logs for distribution of data. This talk expounds the conceptual and implementation details of several approaches to typical challenges in log and event based setups, including schema changes, staleness, decoupling and mixing asynchronous with synchronous dependencies.