Syntactica Products
All of these producst can be quickly customized to meet your business requirements.
- Automated Entity Extraction - Automated Entity Extraction Product performs text-mining functions on text documents. Entities such as people, dates, locations, terms and products are automatically identified, and indexed.
- Job Scheduler - The Syntactica text mining eXist-based Job Scheduler allows customers to enter URL s into a website, that will be automatically indexed into metadata repositories.
- UIMA Interfaces - The Syntactica text-mining architecture allows any Apache UIMA components to be seamlessly integrated into a text-mining pipeline application.
- XQuery Reporting - The Syntactica text-mining architecture allows document analytis and reports to be performed using w3c XQuery standards.
- Native XML Database - The Syntactica text-mining architecture uses native XML databases for fast storage and retrieval of complex, unstructured data. The Syntactica staff is a contributor to the eXist Database Open Source Project.
- Document Summarization - The Syntactica text-mining tools quickly summarize highly complex and lengthy documents to create short document summaries.
- Mashup Enablement--The Syntactica text-mining architecture allows free-form text to play a role in repurposing of documents into new mashups. Examples include timeline and spacial maps.
- RSS/Atom Harvester - The Syntactica text-mining system reads RSS and Atom feeds and automatically harvests text documents stored in these feeds.
- RDF Extraction - The Syntactica text-mining applications can be configured to support w3c RDF formats as well as other XML markup and XML metadata formats.
In addition, development work is near completion on the following products:
- Latent Semantic Analysis - The Syntactica text-mining architecture uses complex mathematical operations on large data sets to enable automated document classification.
- Automatic Document Classification - The Syntactica text-mining architecture uses a family of tools to automatically classify documents based on semantic content.