Access Innovations, Inc. and dataCloud, LLC have teamed up to create Topic Seeker™, a semantics-based solution for big data. Topic Seeker analyzes text-based content and organizes it by topic, allowing publishers and other organizations to see changing trends in their respective fields, develop conference tracks based on current topic relevance, and many other applications.
“Analytics today are focused on numbers,” explains Jeffrey Gordon, CEO of dataCloud, LLC. “Topic Seeker enhances that experience by analyzing the language associated with the numerical data. By incorporating a taxonomy or ontology into big data analysis, we can decode market trends with greatly increased specificity. For example, it’s easy to look at the numbers and see that sales of a certain product are declining, but those numbers don’t provide any qualitative assessment of a customer’s sentiment about the product. Leveraging Topic Seeker to analyze the words those customers are using improves your understanding of the market for that product.”
Using data visualization techniques, Topic Seeker provides a rapid-fire solution for organizations facing the challenge of ever-growing amounts of information. Topic Seeker works via an API that ingests, processes, delivers, and visualizes metadata in near real-time. Topic Seeker’s algorithm allows for nearly 20 visualization options, n-gram paper clustering, and topic domain correlation mapping.
“Working together on this project is exciting for us,” says Bob Kasenchak, Director of Business Development for Access Innovations, Inc. “The combination of hard-core coding for big data, semantic analysis of text, and visualization techniques has resulted in a powerful system. The possibilities for implementation are huge in a wide variety of industries.”
Access Innovations and dataCloud look forward to further refinement of Topic Seeker and are excited to present its possibilities to current users and prospective new clients.