Synaptica’s Text Analytics Platform (TAP) is text analytics and auto-categorization made simple. Fully integrated with Synaptica’s KMS enterprise taxonomy management system, TAP is a text analytics and auto-categorization module for the analysis and classification of structured and unstructured information.
Simple UI helps taxonomists become fluent in categorization without having to learn esoteric syntax.
Complexity and productivity are improved through a no-silo approach.
Categorization rules are transparent and easy to edit. The no-black-box principle helps users understand auto-categorization and refine indexing rules.
Synaptica’s Text Analytics solutions start with your enterprise taxonomy. Text analytics use your organization’s vocabularies to automatically apply metadata to corporate content for knowledge management.
Categorization enables an enterprise to sort and rank content based on what it is about. TAP indexes, classifies, and applies metadata to content using authoritative concepts and named entities defined within enterprise taxonomies in the Knowledge Organization System (KOS). The tagging process leverages the semantic definitions and structure of the KOS to contextualize the meaning of the words and phrases found in documents. Aboutness algorithms rank the most relevant concepts and names within individual documents and across collections. Generalization algorithms group content into broad categories while salience algorithms identify what sets particular documents apart from the rest.
Document Sections allow users to quickly and flexibly define document type templates by specifying tags, text, and other document markers to improve weighted relevancy ranking.
Document sections provide context for found concepts and allow for the application of weights to score these concepts appropriately. The output is a clearly defined list of concepts, where they appear, and a document section score.