Peopleconnect, Inc.

Ang Sun

Xin Wang

Hakan Kardes

Siddharth Agrawal

Lin Chen

Deepak Konidena

Micah Huff

Andrew Kellberg

A novel entity resolution approach for the organization entity domain can be implemented in the MapReduce framework with low memory requirements so that it may scale to large scale datasets. A new clustering approach, sClust, significantly improves the recall of the pairwise classifier.

Graph-based organization entity resolution

Finding connected components in a graph is a well-known problem in a wide variety of application areas such as social network analysis, data mining, image processing, and etc. We present an efficient and scalable approach to find all the connected components in a given graph. We compare our approach with the state-of-the-art on a real-world graph. We also demonstrate the viability of our approach on a massive graph with &#x2dc;6B nodes and &#x2dc;92B edges on an 80-node Hadoop cluster. To the best of our knowledge, this is the largest graph publicly used in such an experiment.

Fast and scalable connected component computation

Growing community of inventors

Bellevue, WA, United States of America

Ang Sun