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Introduction to Rosoka’s Natural Language Processing (NLP)
Data is one of the most important resources for any organization. It’s what drives organizational growth and informs business decisions.
Businesses have more than just spreadsheets to analyze. Often times, the information needed to inform decisions is found in reports, emails and other types of documents that are not listed in a structured spreadsheet. The complex part is making sense of it all.
Natural language processing (NLP) is the solution. Through NLP, data and insights are fused together, resulting in informed analytics that empower organizations to make better decisions all while saving significant time and resources.
Natural Language Processing: A Quick Overview
Natural language processing (NLP) allows computers to be able to interpret human language largely the way humans do. Chances are, you have interacted with NLP in your everyday life; perhaps with chat bots, GPS devices or voice-recognition digital assistants. All of these solutions use various types of NLP, which can range from optical character recognition (OCR), machine learning (ML), voice-to-text translation, and sentiment analysis; just to name a few.
Through NLP, human language is broken into pieces and assigned meaning that the computer can understand. As a result, computers can then analyze our language much like humans do: via context, grammar, and meaning.
NLP solves problems that we would otherwise not be able to solve due to limited resources and time. For example, NLP enables businesses to utilize customer data to improve their performance and increase revenue, while government organizations can leverage NLP to inform national security and intelligence missions.
Rosoka: Next Generation Natural Language Processing Software
Successful NLP solutions not only help businesses make better decisions, but they also save time and resources. At Rosoka, we are proud to provide portable, scalable, and multilingual NLP solutions to a variety of organizations, ranging from government and intelligence groups, to law enforcement agencies, healthcare companies and financial institutions.
Our solutions allow organizations to gain insights from large volumes of unstructured data, or text written in natural language, from any text source. Rosoka automatically extracts the most important entities to the mission at hand and determines their relationships to one another. The results are analogous to employing a team of junior analysts, with instant and consistent results.
“Connecting the who and the what with the when and the where.”
As turnkey extraction solutions, you can be up and running in as little as 10 minutes. Plus, you can deploy our solutions across any language, platform, application, device, or cloud.
Rosoka Server is our complete NLP solution that supports custom processing workflows and load-balancing for true scalability. It includes all of our multilingual entity, relationship, and geospatial extraction features. Like all Rosoka solutions, the extraction can be modified to support industry-specific needs. This type of deployment is perfect for large organizations that have the need to continuously process large amounts of data and who employ a team of analysts who may or may not have access to the same data.
Rosoka SDK is the solution you need to integrate our extraction engine into any third-party app, software, or platform. For developers, Rosoka SDK enables you to develop your own unique solution that features all of our analytics capabilities.
Rosoka Studio enables you to modify or create everything from entity types and relationship definitions to extraction rules and lexicons. Plus, it features an easy-to-use interface as well as simplified importing and exporting. This product allows organizations to fine-tune our extraction engine to meet their industry-specific goals.
Rosoka Text Analytics (RTA) was built to allow i2 users to perform unstructured text analytics. RTA enables analysts to move faster by immediately processing the text inside imported documents from any source and language. Analysts are able to custom curate extraction results using the simplified and intuitive interface. Plus, analysts can uncover relationships across documents with one click.
Rosoka GeoGravy takes geographic location identification to the next level. It bridges the gap between text data and geospatial metadata so data can be organized by location. The result is accurate geocoordinate tagging across formats.
Rosoka solutions enable you to identify over 3 dozen entity types and 500+ relationship types using a multilingual platform featuring over 200 languages. Plus, it’s all available right out of the box. With Rosoka, you’ll have immediate access to the clear, actionable insights you need to make informed decisions.
Learn More About Rosoka’s Natural Language Processing Software
Want to dive deeper into Rosoka’s NLP solutions? We’ve compiled some of our best resources here, so you can learn more about our solutions and how they might work for you.
NLP in Everyday Life: An Overview
NLP is the process behind everyday tasks such as asking Siri to call a friend. It’s also used by search engines to find images and by translation services such as Google Translate. While NLP may sound like a far-off technology, it’s a process already happening behind the scenes, in places we may not realize.
Rosoka NLP vs. spaCy NLP
All organizations can indeed benefit from NLP. However, you must choose the right NLP software for your needs. In this guide, we compare and contrast two of the most popular NLP solutions, Rosoka NLP and spaCy NLP.
Types of Natural Language Processing Techniques
There are many different NLP techniques, from named entity recognition to aspect mining. All of these techniques can provide unique insights when it comes to your data. Which techniques are right for you? This article discusses the various techniques to help you gain a better understanding of what NLP can do for your organization.
Whitepaper: Parserless Extraction: Using a Multidimensional Transient State Vector Machine
Rosoka does not use the classic mathematical model of a sender and receiver of information. Instead, we implement the “third-party listener” model to uncover more information hidden beneath the surface of communication or shared context. Learn more about parserless extraction inside this whitepaper.
Whitepaper: Analyzing Newswire and Social Media Data Using Multi-Vector Sentiment Analysis
Many NLP solutions available only provide one measure of sentiment when analyzing the written text on the internet. Rosoka utilizes multiple sentiment vectors to provide in-depth information about language.
In this study, we tested four sentiment vectors and sentiment measure (S-M) by comparing two different document sets: one featuring news articles and the other featuring tweets from Twitter.
Whitepaper: Accuracy Metrics for Entity Extraction
The common accuracy metrics used to evaluate entity extraction software such as precision, recall, and F-measure are indeed useful, but also limited. At Rosoka, we believe that entity extraction systems should be evaluated based on the accuracy of output, how easily errors can be detected, and the level of effort required to make improvements to the system.
Reach Out to Schedule Your Demo Today
Ready to take advantage of the power of natural language processing within your organization? If so, the Rosoka team is here to help. For answers to your questions or to schedule a demo today, reach out to us by calling 703-391-0381.