DR. KI TAE KIM, D.C.
Chiropractic at Bascom Ave, San Jose, CA

License number
California DC27786
Category
Chiropractic
Type
Chiropractor
Address
Address
206 N Bascom Ave STE A, San Jose, CA 95128
Phone
(408) 975-9606
(408) 975-9616 (Fax)

Personal information

See more information about KI TAE KIM at radaris.com
Name
Address
Phone
Ki Kim
827 S Berendo St APT 402, Los Angeles, CA 90005
Ki Kim
920 S Nutwood St APT 82, Anaheim, CA 92804
Ki Kim
4009 Calle Sonora Oeste UNIT 2, Laguna Woods, CA 92637
(949) 910-2524

Professional information

See more information about KI TAE KIM at trustoria.com
Ki Kim Photo 1
Ki Kim - San Jose, CA

Ki Kim - San Jose, CA

Work:
Samsung Semiconductor Inc
Manager Associate
Samsung Semiconductor Inc Samsung Semiconductor Inc
Senior Financial Analyst
Bankruptcy Model, Cash
Financial Analyst
BR Consulting - Mesa, AZ
Investment Research Analyst
I&S BUSINESS CONSULTING - Seoul, KR
Project Consultant
MERRILL LYNCH - Oakland, CA
Intern at Private Client Banking Group
Education:
Cornell University - Ithaca, NY
Master of Eng in OR&IE
Columbia University - New York, NY
Master of Arts in Statistics
Yonsei University - Seoul, KR
Bachelors in Business Administration


Ki Tae Kim Photo 2
Ki Tae Kim, San Jose CA

Ki Tae Kim, San Jose CA

Specialties:
Chiropractor
Address:
206 N Bascom Ave, San Jose, CA 95128


Ki T Kim Photo 3
Dr. Ki T Kim, San Jose CA - DC (Doctor of Chiropractic)

Dr. Ki T Kim, San Jose CA - DC (Doctor of Chiropractic)

Specialties:
Chiropractic
Address:
206 N Bascom Ave SUITE A, San Jose 95128
(408) 975-9606 (Phone), (408) 975-9616 (Fax)
Languages:
English


Ki Kim Photo 4
Unsupervised Message Clustering

Unsupervised Message Clustering

US Patent:
2012023, Sep 20, 2012
Filed:
Mar 18, 2011
Appl. No.:
13/051299
Inventors:
KI YEUN KIM - San Jose CA, US
LEI DUAN - San Jose CA, US
SEOKKYUNG CHUNG - San Jose CA, US
Assignee:
MICROSOFT CORPORATION - Redmond WA
International Classification:
G06F 17/30
US Classification:
707737, 707E17089
Abstract:
Unsupervised clustering can be used for organization of micro-blog or other short length messages into message clusters. Messages can be compared with existing clusters to determine a similarity score. If at least one similarity score is greater than a threshold value, a message can be added to an existing message cluster. If a message is not similar to an existing cluster, the message can be compared against criteria for starting a new message cluster.