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What is NetOwl TextMiner?

NetOwl TextMiner combines the renowned NetOwl Extractor with Elasticsearch to provide a cutting-edge text analytics platform. This software leverages the comprehensive capabilities of NetOwl, making it ideal for executing "what if" scenarios, engaging in discovery processes, supporting rapid investigations, and conducting in-depth research. By integrating all the text analytics tools from the NetOwl Extractor—such as entity extraction, relationship and event extraction, sentiment analysis, text categorization, and geotagging—TextMiner offers a robust text mining solution. The outcomes produced by the Extractor are efficiently stored within Elasticsearch, which enhances the system with a variety of intelligent search and analytical functions. The collaboration between Elasticsearch and NetOwl guarantees swift and scalable real-time text analysis, making it suitable for managing Big Data projects. Additionally, TextMiner features a user-friendly web interface that can be easily customized to meet diverse analytical requirements, allowing users to quickly extract the most pertinent insights from large text collections. This flexibility not only improves user experience but also facilitates more specialized analyses across different fields, catering to the unique needs of various industries.

What is NetOwl NameMatcher?

NetOwl NameMatcher, celebrated for its superior performance in the MITRE Multicultural Name Matching Challenge, offers exceptional accuracy, rapid processing, and scalability in its name matching solutions. Utilizing a cutting-edge machine learning framework, NetOwl adeptly addresses the complex challenges associated with fuzzy name matching. Traditional techniques like Soundex, edit distance, and rule-based systems frequently struggle with precision, leading to an abundance of false positives, and recall issues that result in false negatives, particularly when faced with the varied fuzzy name matching scenarios mentioned earlier. In contrast, NetOwl adopts a data-driven, machine learning-based probabilistic approach to overcome these name matching challenges effectively. It autonomously develops advanced, probabilistic name matching rules from vast real-world datasets containing multi-ethnic name variants. Additionally, NetOwl implements specialized matching models designed for different entity types, including individuals, organizations, and geographical locations. To enhance its functionality, NetOwl incorporates automatic detection of name ethnicity, which significantly boosts its adaptability to the complexities inherent in multicultural name matching. This holistic strategy not only elevates accuracy but also ensures dependable performance across a wide array of applications. Consequently, organizations relying on precise name matching can greatly benefit from the innovative solutions provided by NetOwl.

Media

Media

Integrations Supported

ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SolrCommerce
Tableau

Integrations Supported

ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SolrCommerce
Tableau

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

NetOwl

Date Founded

1996

Company Location

United States

Company Website

www.netowl.com/text-mining

Company Facts

Organization Name

NetOwl

Date Founded

1996

Company Location

United States

Company Website

www.netowl.com/name-matching-software

Categories and Features

Text Analytics

Not specified

Text Mining

Not specified

Categories and Features

Data Quality

Not specified

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