Search

Rohit M Namjoshi

from Austin, TX
Age ~67

Rohit Namjoshi Phones & Addresses

  • 10702 Winchelsea Dr, Austin, TX 78750 (512) 249-1394 (512) 996-8708
  • 12612 Grierson Trl, Austin, TX 78732 (512) 266-6641 (512) 266-9218
  • Bastrop, TX
  • Walcott, IA
  • Cedar Park, TX
  • Travis, TX
  • 10702 Winchelsea Dr, Austin, TX 78750 (512) 762-3422

Work

Position: Precision Production Occupations

Education

Degree: Graduate or professional degree

Skills

Software Engineering • Agile Methodologies • Strategy • SaaS • Architecture • Product Management

Languages

一点点普通话

Industries

Computer Software

Resumes

Resumes

Rohit Namjoshi Photo 1

Rohit Namjoshi

View page
Location:
Austin, Texas Area
Industry:
Computer Software
Skills:
Software Engineering
Agile Methodologies
Strategy
SaaS
Architecture
Product Management
Languages:
一点点普通话

Business Records

Name / Title
Company / Classification
Phones & Addresses
Rohit Namjoshi
DIRECTOR
1709 EAST 18TH CONDOMINIUM ASSOCIATION
1709 E 18 St, Austin, TX 78702
Rohit M Namjoshi
Governing, Governing Person
CURCIO VENTURES, INC
Business Services at Non-Commercial Site
10911 Country Knls, Austin, TX 78750
10702 Winchelsea Dr, Austin, TX 78750
Rohit Namjoshi
Director Information Technology
Vertive, LLC
Management Consulting Services
3721 Executive Ctr Dr, Austin, TX 78731
7719 Wood Holw Dr, Austin, TX 78731
(512) 342-8378

Publications

Us Patents

Attribute Based Association Rule Mining

View page
US Patent:
7433879, Oct 7, 2008
Filed:
Jun 17, 2004
Appl. No.:
10/870360
Inventors:
Nirad Sharma - Austin TX, US
Rohit Namjoshi - Austin TX, US
David Franke - Austin TX, US
Assignee:
Versata Development Group, Inc. - Austin TX
International Classification:
G06F 17/30
US Classification:
707101, 707 6, 707 5, 707 3
Abstract:
A data processing system processes data sets (such as low-resolution transaction data) into high-resolution data sets by mapping generic information into attribute-based specific information that is stored in a database. The extracting frequent pattern information from the database using frequent pattern growth techniques, a compact frequent pattern tree data structure efficiently holds frequent pattern information for multiple transactions having one or more items in each transaction. Frequent pattern data is transformed for ease of use with rule generation algorithms by removing redundant information (such as part group items) or by consolidating items corresponding to a part group and replacing those items with a proxy item for purposes of power set generation.
Rohit M Namjoshi from Austin, TX, age ~67 Get Report