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MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.
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Search engine and data mining applications and ClueWeb datasets.
The Lemur Project develops search engines, browser toolbars, text analysis tools, and data resources that support research and development of information retrieval and textmining software, including the Indri search engine in C++, the Galago search engine research framework in Java, the RankLib learning to rank library, ClueWeb09 and ClueWeb12 datasets and the Sifaka data mining application.
Wikipedia Concept Association Map (WCAM) is new approach for textual knowledge representation and understanding. All concepts and associations are stored in a graph database for better performance and easy distribution.
MiningFlow is an environment created for textmining experiments. It helps a textmining analyst to compose several web services in order to create an full experiment. The environment uses semantic aproach to support the design task.
Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.
Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.