Pinpoint high-value unstructured data
Keep the human in command
Patented matching that uses your business and domain language to get the data you need for AI, ML, RPA, BI, Research, Talent, and BAU applications
Index, measure, curate, filter, match, classify, and label unstructured text data automatically
For Data Scientists, Data Analysts, BI and Operations Specialists, Researchers, SMEs, Talent Professionals, and IT
“DataScava perfectly complements existing approaches to unlocking the value of unstructured text data – by helping companies to model higher-level intents and purposes behind the labeling and classification of data – by defining the abstract topics and themes that represent their own business and subject matter expertise – and by applying both to big data sets real-time.”
-Scott Spangler, Chief Data Scientist, IBM Distinguished Engineer, Author “Mining the Talk: Unlocking the Business Value in Unstructured Information”
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Our Three Methods
DataScava is tuned to your business and generates value-added metadata about raw text for use in other systems and charting
Tailored Topics Taxonomies
(TTT)
Models features and topics within heterogeneous text using specialized taxonomies you can select, create, edit, or import to define business language and domain expertise, allowing for the highly customized vocabulary and logic necessary for complex document processing.
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Domain-Specific Language Processing
(DSLP)
DSLP is an alternative or adjunct to NLP and incorporates domain-specific knowledge into the language processing pipeline. It indexes text at the file level to generate weighted topic scores and other metadata, surfacing relevant textual files from large datasets.
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Weighted Topic Scoring
(WTS)
Accurately measures and matches topics according to user-defined score thresholds and labels documents into appropriate cohesive categories using heuristic techniques tailored to a specific business purpose, enabling a true human-machine partnership in an ever-changing environment.
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How It Works
Our customizable indexer uses company-specific language you can see, define, and control
Use DataScava to curate quality training data sets to unleash AI and optimize ML models; identify BI or Research data; filter emails, inquiries, or tickets for service desks or RPA; mine notes, news, reports, contracts, or transcripts; identify skills for People Analytics or Talent Acquisition; and more.
Our practical, easy-to-use toolset lets you capture the business ontologies that provide the critical bridge between unstructured data analysis using standard data science techniques and the human expertise that gives your business its competitive edge.
Encode Your Organization’s Priorities
A Weighted Topic Scoring File Match
DataScava enables a more data-centric approach to business applications, with topic models which reflect the primary areas of focus, flexible topic scoring to encode your organization’s priorities, and customized text processing that mirrors the way people actually communicate in the industry.
Our sophisticated algorithm assigns weights to topics based on their importance and relevance within the domain. This advanced scoring function you control based on your interests, priorities, and intents enables you to focus on the most critical topics and discard noise, leading to better insights.
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How It’s Different
DataScava ensures cross-collaboration between technical and non-technical people
- It’s explainable, transparent, and provable.
- Uses TTT, DSLP, WTS (not NLP or Semantics) to find what you’re looking for, not what it infers.
- Offers pre-built editable taxonomies for the financial and IT domains.
- Works top-down through your corpus at the file level, not the sentence level.
- Generates sortable metadata to summarize textual content in a numerical format.
- Measures color-coded topics, highlights key terms in on-topic files, and filters out irrelevant ones.
- Encapsulates your business language and domain expertise in your software on an ongoing basis.
