Company Filing History:
Years Active: 2017-2019
Title: Svetlana Levitan: Innovator in Data Mining Technologies
Introduction
Svetlana Levitan is a prominent inventor based in Skokie, IL (US), known for her contributions to data mining technologies. With a total of five patents to her name, she has made significant advancements in the field, particularly in the area of mining association rules.
Latest Patents
One of her latest patents focuses on mining association rules in the map-reduce framework. In this innovative process, each iteration involves a cluster of computing systems where mapper nodes receive a split of transaction data. Each mapper node scans the split to count the absolute support value of each candidate itemset for the current search levels. The candidate itemsets and their support values are then passed to reducer nodes in the cluster. The number of reducer nodes is determined adaptively based on the number of candidate itemsets and the maximum available resource nodes in the cluster. Each reducer node combines the absolute support values of each candidate itemset and identifies frequent itemsets using a minimum support threshold. For each frequent itemset found, the reducer node creates association rules that satisfy a minimum confidence threshold and exports all discovered frequent itemsets and association rules to a file system for storage.
Career Highlights
Svetlana Levitan is currently employed at International Business Machines Corporation, commonly known as IBM. Her work at IBM has allowed her to explore and develop innovative solutions in data mining and analytics.
Collaborations
Throughout her career, Svetlana has collaborated with notable colleagues, including Damir Spisic and Jing-Yun Shyr. These collaborations have contributed to her success and the advancement of her projects.
Conclusion
Svetlana Levitan's work in data mining technologies has established her as a key innovator in her field. Her patents reflect her commitment to advancing technology and improving data analysis processes.