NetOwl NameMatcher 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.
NetOwl NameMatcher Alternatives
Web APIs by Melissa
Looking for fast, easy solutions to protect your entire data lifecycle? Look no further. Melissa’s Web APIs offer a range of capabilities to keep your customer data clean, verified, and enriched. Our solutions work throughout the entire data lifecycle – whether in real time, at point of entry or in batch.
• Global Address: Verify & standardize addresses in 240+ countries & territories with postal authority certified coding & premise-level geocoding.
• Global Email: Verify email mailboxes, syntax, spelling & domains in real time to ensure they are deliverable.
• Global Name: Verify, standardize & parse person & business names with intelligent recognition of millions of first & last names.
• Global Phone: Verify phone as active, identify line type, & return geographic details, dominant language & carrier for 200+ countries.
• Global IP Locator: Gain a geolocation of an input IP address with lat & long, proxy info, city, region & country.
• Property (U.S. & Canada): Return comprehensive property & mortgage info for 140+ million U.S. properties.
• Personator (U.S. & Canada): USPS® CASS/DPV certified address checking, name parsing & genderizing, phone & email verification are all easily performed with this API.
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DataBuck
Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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NetOwl Extractor
NetOwl Extractor provides exceptionally precise, rapid, and scalable entity extraction across various languages through the use of AI-driven natural language processing and machine learning techniques. This named entity recognition tool can be utilized both on-site and in the cloud, facilitating a wide range of Big Data Text Analytics applications. Supporting over 100 distinct entity types, NetOwl presents a comprehensive semantic ontology for entity extraction that surpasses conventional named entity extraction tools. Its offerings encompass individuals, numerous organization categories (such as corporations and government entities), diverse geographic locations (including nations and cities), as well as addresses, artifacts, phone numbers, and titles. This extensive named entity recognition (NER) serves as a crucial basis for more sophisticated relationship and event extraction processes. The software is applicable across various sectors, including Business, Finance, Politics, Homeland Security, Law Enforcement, Military, National Security, and Social Media, making it a versatile choice for organizations seeking in-depth textual analysis. Furthermore, its adaptability to different environments ensures that users can effectively harness its capabilities to meet their specific needs.
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Melissa Data Quality Suite
Industry experts estimate that as much as 20 percent of a business's contact information may be inaccurate, leading to issues such as returned mail, costs for address corrections, bounced emails, and inefficient marketing and sales endeavors. To address these challenges, the Data Quality Suite offers tools to standardize, verify, and correct contact information including postal addresses, email addresses, phone numbers, and names, ensuring effective communication and streamlined business processes. It boasts the capability to verify, standardize, and transliterate addresses across more than 240 countries, while also employing advanced recognition technology to identify over 650,000 ethnically diverse first and last names. Furthermore, it allows for the authentication of phone numbers and geo-data, ensuring that mobile numbers are active and reachable. The suite also validates domain names, checks syntax and spelling, and even conducts SMTP tests for comprehensive global email verification. By utilizing the Data Quality Suite, organizations of any size can ensure their data is accurate and up-to-date, facilitating effective communication with customers through various channels including postal mail, email, and phone calls. This comprehensive approach to data quality can significantly enhance overall business efficiency and customer engagement.
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Integrations
Company Details
Company:
NetOwl
Year Founded:
1996
Headquarters:
United States
Website:
www.netowl.com/name-matching-software
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
In Person
Customer Support
Business Hours
Online Support
NetOwl NameMatcher Features and Options
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