Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
NetOwl TextMiner merges the acclaimed NetOwl Extractor with Elasticsearch to deliver an innovative text analytics solution. This software harnesses the full spectrum of NetOwl's functionalities, making it perfect for conducting "what if" analyses, performing discovery tasks, facilitating quick-response investigations, and carrying out thorough research. By incorporating all the text analytics features of the NetOwl Extractor—including entity extraction, relationship and event extraction, sentiment analysis, text categorization, and geotagging—TextMiner presents a comprehensive text mining platform. The results generated by the Extractor are stored within Elasticsearch, which offers a range of intelligent search and analytical capabilities. The synergy between Elasticsearch and NetOwl ensures rapid and scalable real-time text analysis suited for handling Big Data. Furthermore, the user-friendly web-based interface of TextMiner can be easily configured to accommodate various analytical needs, enabling users to swiftly access only the most valuable insights from extensive text datasets. This adaptability not only enhances usability but also allows for more tailored analysis across multiple domains.
API Access
Has API
No
API Access
Has API
Yes
Integrations
ArcGIS
Yes
Elasticsearch
Yes
Google Maps
Yes
IBM Cloud
Yes
Kibana
Yes
MarkLogic
Yes
Palantir Apollo
Yes
SolrCommerce
Yes
Tableau
Yes
Integrations
ArcGIS
Yes
Elasticsearch
Yes
Google Maps
Yes
IBM Cloud
Yes
Kibana
Yes
MarkLogic
Yes
Palantir Apollo
Yes
SolrCommerce
Yes
Tableau
Yes
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
Yes
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
Yes
Webinars
No
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
NetOwl
Founded
1996
Country
United States
Website
www.netowl.com/name-matching-software
Vendor Details
Company Name
NetOwl
Founded
1996
Country
United States
Website
www.netowl.com/text-mining
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
Text Mining
Boolean Queries
No
Document Filtering
No
Graphical Data Presentation
No
Language Detection
No
Predictive Modeling
No
Sentiment Analysis
No
Summarization
No
Tagging
No
Taxonomy Classification
No
Text Analysis
No
Topic Clustering
No