We wished there was more space at our stand so that everyone interested could watch and hear the speakers. Yuri Svirid, CEO, talked about topic modeling and how AI could be utilized to explore different topics and subjects that books cover. This technology can help automate book indexing or create descriptions and annotations for digital books.
Second part was related to the contextual search Proof-of-Concept that Nikolai Karelin, Head of AI delivered from the stage. As a Proof-of-Concept Silk Data engineers analyzed Wikipedia and represented its entire text corpse as a navigable map with dots (topics), connections between them and subject areas they build, based on their semantic proximity.
Semantic search technology can help revolutionize the way knowledge workers look for information and study different subjects. AI and machine learning based algorithms can analyze large volumes of texts and extract meaning of separate fragments, explore topics and how they are related to each other and to a user’s context. This can have a dramatic influence on many industries, including publishing – where businesses are in search of new ways to improve reading, learning, information processing and sharing experience. You can learn more about semantic maps and the new technology here.
