The API and Libraries for Language / Text and Data
Topic-Mapper™ is a specialized solution for language processing: language in form of text or data (i.e. values). Topic-Mapper™ imports the data directly into the holosemantic data space. So the data directly stimulates the holosemantic ai-one™ net.
With the ai-one™ Topic-Mapper API, developers can build intelligent text applications that deliver sense-making and learning capabilities for semantic discovery, knowledge collaboration, sentiment analysis, and classification. AI and learning are inherent to the technology and the API gives developers commands they need to “build a learning machine” with the attributes critical to their application.
- provides semantic analysis and matching for text
- straightforward and flexible API for inherent semantic associative search and phonetic analysis
- human language independent
- requires only basic structuring of input text
- ongoing “teaching” via user defined contexts
Description of the ai-one Topic-Mapper SDK:
- .NET 3.5 CLR wrapper (dll) around ai-one™ core Text library (out-of-process COM server)
- Small footprint instantiation (<700k)
- API documentation
- Developers guide
- Code examples
- Sample RESTful API WebService (C#)
- BrainBoard workbench application for rapid proof of concept development
SDK License for Development, Prototyping & Testing
Topic-Mapper is ideal for internal IT teams to build machine learning applications to mine unstructured data. It is a “must have” tool for any IT department that wants to quickly and easily build intelligent applications. The system takes less than a day to learn.
Common use cases for building custom applications using Topic-Mapper include:
- Knowledge management systems using semantic search and retrieval. For example, finding related patent filings or PubMed articles.
- Mining unstructured text documents to find similar concepts or ideas. ai-BrainDocs is an eDiscovery application and new business built on Topic-Mapper. It enables legal departments to scan documents for different ideas that use the same words — something that can’t be done using other search, semantic or statistical approaches such as keyword searches, LSI, LSA, LDA, etc.
- Auto-tagging and classifying text (either documents or social media feeds).
- Comparing the content of multiple information sources.
ai-one builds prototypes for customers upon request. Please contact Olin Hyde for more information on pricing, terms and conditions.
OEM Agreement and Embedded Distribution License
When a product or service is developed and provided to customers using Topic-Mapper, an OEM Distribution license is required. Such license terms and amounts are flexible and subject to a definitive agreement.