powerful extraction
& classification tools
Identify actionable insights to drive better decisions
text classification
Text classification enables natural language processing to sift through
massive datasets to extract specific information needed to meet an objective.
Each of the use cases described on this page are forms of text classification, and vary based on the project's objective.
Entities of all kinds - commercial, governmental, non-profit and others - use text classification to automate tasks like tracking brands and consumer preferences; improving customer support services; moderating content; improving search results; and tracking public opinion, to name a few.
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Intent analysis trains a natural language processing engine to look for clues within text or speech that signal a desire or objective. Once an intent is understood, it can be classified in order to apply an appropriate response.
WebChartAI is perfect for creating datasets that teach natural language processing applications to accurately identify intent.
intent analysis
automation that accurately
interprets desires or objectives
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text extraction
Label discrete classes of data within unstructured text for projects like named entity recognition, topic classification and others.
WebChartAi's extraction tools combine powerful functional with ease of use.
Label an unlimited number of classes within a text data object, including nested labels to assign multiple tags to be same text.
Tags appear in both a traditional button array and a hover-cloud for rapid labeling.
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dictionaries
& word lists
Classify words and meanings in order to normalize usage in automation applications
A word list is a collection of words relevant to a topic. For example, a security agency might build a word list of terms used by threat agents that refer to planned operations for monitoring purposes.
A dictionary is a collection of meanings associated with a word. For example, an NLP application trained to monitor for illegal drugs would include bliss in its dictionary as a meaning for Fentanyl.
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intent variation & utterance collection
Intent variation is understanding what someone wants, while utterance collection is understanding all the different ways someone may ask for it.
Intent variation defines all possible meanings of a query. For example, "warranty question" could mean buying
a new warranty, entering a claim on an existing warranty, or clarifying a warranty's terms, to name a few.
Utterance collection is defining all the ways intent is expressed, such as "I'd like to buy a warranty" vs. "how do I purchase a new warranty?".
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Both utterance collection and intent variation play an important role in enabling natural language processing to add automation to tasks like chatbot responses, customer service interactions and other business processes.
Over 15 million minutes of audio and 50 million documents
have been processed using WebChartAI's workflow tools.
sentiment analysis
accurately interpreting attitudes, emotions and opinions
Sentiment analysis helps natural language processing accurately interpret a target audience's attitudes, emotions and opinions.
Accessibility to large collections of data via social media monitoring and data mining makes sentiment analysis one of the most widely-used - and important - classification techniques available.
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content moderation & spam detection
interpret and classify content for appropriateness and spam detection
Content moderation and spam detection applications use natural language processing to classify objectionable text-based content.
WebChartAI is used to create training datasets for content moderation and spam detection automation.
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text summarization
summarize text based on situational
needs, reader types or access rights
Text summarization uses natural language processing to identify key words, phrases and sentences within a body of text and preserves them within a condensed version of the original.
WebChartAI's workflow tools are used to manually summarize bodies of text in order to generate training data for model building and improvement.
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language detection
identify languages in speech and text-based
interactions for workflow-based automation
Language detection enables natural language processing to add automation to workflows where multiple languages are used.
It's often used as a first layer of data processing prior to the use of other techniques, such as sentiment analysis.
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verbatim transcribing
highly accurate transcription with rapid
turn-around for custom model tuning
Over 40 million minutes of audio have been transcribed by over 20,000 transcriptionists in the last ten years on platforms developed and owned by WebChartAi - WebChartMD for health related transcribing (webchartmd.com) and Xelex Digital for non-health (xelexdigital.com).
WebChartAI's robust workflow was designed for high-volume verbatim transcribing. Custom model tuning projects of 500 - 1000 audio hours can be verbatim transcribed and returned with 48 hours if required.
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