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Description
NetOwl NameMatcher, recognized for its excellence in the MITRE Multicultural Name Matching Challenge, delivers unparalleled accuracy, speed, and scalability in name matching solutions. By employing an innovative machine learning framework, NetOwl effectively tackles the intricate challenges of fuzzy name matching. Conventional methods like Soundex, edit distance, and rule-based systems often face significant issues with precision, leading to false positives, and recall, resulting in false negatives, when confronting the diverse fuzzy name matching scenarios outlined previously. In contrast, NetOwl leverages a data-driven, machine learning-based probabilistic strategy to address these name matching difficulties. It automatically generates sophisticated, probabilistic name matching rules from extensive, real-world multi-ethnic name variant datasets. Furthermore, NetOwl employs distinct matching models tailored to various entity types, such as individuals, organizations, and locations. To add to its capabilities, NetOwl also integrates automatic detection of name ethnicity, enhancing its adaptability to the complexities of multicultural name matching. This comprehensive approach ensures a higher level of accuracy and reliability in diverse applications.
Description
The core of our matching software, matchit®, is intentionally crafted to achieve outcomes that emulate human perception on a large scale, all while eliminating the need for preprocessing. By leveraging Artificial Intelligence, a unique phonetic algorithm, specialized lexicons, and a contextual scoring engine, matchit effectively addresses the common errors, inconsistencies, and hurdles associated with contact and business data management. Traditional matching systems typically require users to establish matching criteria, which consist of various functions and standard fuzzy algorithms to generate an alphanumeric match key. This match key is essential for comparing two records and ultimately identifying matches. In contrast to these conventional methods, matchit goes beyond a mere single comparison of match keys; it assesses records in a contextual manner, performing multiple comparisons and individually scoring them to evaluate the similarity across all pertinent elements of your data. This comprehensive approach not only enhances accuracy but also significantly improves the overall matching process.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Alteryx
No
Apache Spark
No
ArcGIS
Yes
Elasticsearch
Yes
Google Maps
Yes
Hadoop
No
IBM Cloud
Yes
Kibana
Yes
MarkLogic
Yes
Palantir Apollo
Yes
Integrations
Alteryx
Yes
Apache Spark
Yes
ArcGIS
No
Elasticsearch
No
Google Maps
No
Hadoop
Yes
IBM Cloud
No
Kibana
No
MarkLogic
No
Palantir Apollo
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
NetOwl
Founded
1996
Country
United States
Website
www.netowl.com/name-matching-software
Vendor Details
Company Name
360Science
Founded
2016
Country
United States
Website
www.360science.com/data-quality-solutions/the-matching-engine/
Product Features
Data Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
No
Product Features
Data Cleansing
Address/ZIP Code Cleaning
No
Charting
No
Data Consolidation / ETL
No
Data Mapping
No
Multi Data Format Support
No
Phone/Email Validation
No
Raw Data Ingestion
No
Sample Testing
No
Validation / Matching / Reconciliation
No
