Hancheng Ge

from Bellevue, WA

Age ~39

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Hancheng Ge Phones & Addresses

Bellevue, WA
Seattle, WA
College Station, TX

Work

Company: Texas a&m university Jun 2009 Position: Graduate research assistant

Education

Degree: Bachelor of Engineering School / High School: Beijing Jiaotong University Specialities: Automation

Skills

Transportation Engineering • Synchro • Python • Data Mining • Machine Learning • C++ • Sql • Mysql • Big Data • Hadoop • Mapreduce • Programming • Sas Programming • Jmp • Vissim • Javascript • Information Retrieval • Latex • Labview • Matlab • Transportation Planning • R

Languages

English • Mandarin

Industries

Higher Education

Resumes

Applied Scientist, Amazon Ads

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Location:

2500 Hwy 190 east, Livingston, TX

Industry:

Higher Education

Work:

Texas A&M University since Jun 2009
Graduate Research Assistant

Education:

Beijing Jiaotong University
Bachelor of Engineering, Automation Texas A&M University
Master of Science, Transportation

Skills:

Transportation Engineering
Synchro
Python
Data Mining
Machine Learning
C++
Sql
Mysql
Big Data
Hadoop
Mapreduce
Programming
Sas Programming
Jmp
Vissim
Javascript
Information Retrieval
Latex
Labview
Matlab
Transportation Planning
R

Languages:

English
Mandarin

Publications

Us Patents

Mapping Products Between Different Taxonomies

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US Patent:

20160078507, Mar 17, 2016

Filed:

Oct 17, 2014

Appl. No.:

14/517505

Inventors:

Gurudatta Horantur Shivaswamy - Saratoga CA, US
Hancheng Ge - College Station TX, US
Lili Yuan - San Jose CA, US

International Classification:

G06Q 30/06
G06F 17/30

Abstract:

Techniques for mapping item listings from a first taxonomy to a second taxonomy are described. In an example embodiment, item listings from a first database storing a first taxonomy and item listings from a second database storing a second taxonomy are obtained. Then, for each of the obtained item listings, a plurality of features is extracted, including at least one feature related to an image associated with the item listing and at least one feature related to text associated with the item listing. Then a mapping between item listings in the first taxonomy and item listings in the second taxonomy is created based on the plurality of features extracted by the feature extraction component, wherein the mapping identifies which item listings in the first taxonomy correlate to a same product as which item listings in the second taxonomy.