Data & AI
Knowledge Mining, AI, ML, Cognitive Services
Customer is a non-profit organization has championed the mission to help make better health decisions since 1975. It develops searchable health content for patient education, for health insurers, for care management companies, for hospitals, and for the public through the internet.
This organization partners with hospitals, electronic medical record (EMR) providers, and health websites to provide up-to-date, evidence-based information. Its various search platforms service internal content developers, clinicians, and external clients. The company has been facing the painful challenges:
- Outdated Search Experience: Search filters are incomplete, provide inconsistent search experience, and uncalled for ever-changing categories.
- Content Relationship: Difficulty in finding related content, inconsistent taxonomy mapping, limited clinical relationship
- Content Visibility: Lack of visibility in status (draft/prod) and content type (text, image, video)
The company’s executives sought to replace its search platforms with a new unified system supporting self-service health content inventory search and discovery to elevate customer experience and improve business efficiency.
WinWire developed and implemented a Knowledge Mining solution by leveraging the latest Azure components such as Azure Cognitive Search, Video Indexer and Text Analytics for Health resulting in an advanced, unified, self-service search platform.
- Analyze existing search platforms all semi-structured and unstructured data sources
- Create the overall solution architecture for the new search platform. The intent is to achieve accurate results when compared with the existing search platforms
- Implement the solution using Azure Cognitive services, video indexers, and D3 charts to display search results and their relations in a knowledge-graph form
- Analyze utilization of Text Analytics for Health for additional insights and semi-automatic content creation
- Develop custom skills to read data from different sources and feed it into various indexers
- Demonstrate context-aware search capabilities
- Consolidate numerous search platforms into one, resulting in significant search time saved by internal users and by subscribers
- Improved search results relevancy
- Improved customer experience
- A better platform for external users (clinicians, clients) to find related data either in text, images, and videos