For a long time, universities worked off a simple idea: knowledge was scarce. You paid for tuition, showed up to lectures, ...

Investors need a new framework for evaluating opportunities in the emerging Intelligence Economy ("Intellinomics"). Semantic ...

As AI adapts and learns, its value to KM becomes more apparent. AI offers remarkable capabilities to avoid data silos, improve search relevance, handle multimodal information sources, and uncover ...

txtai is an all-in-one AI framework for semantic search, LLM orchestration and language model workflows. The key component of txtai is an embeddings database, which is a union of vector indexes ...

Traditional methods of linking large language models (LLMs) to knowledge bases via the semantic similarity search often fall short of capturing complex relational dynamics. To address these ...

Build AI into your enterprise content and knowledge management platform with 5 APIs that help you base your AI on enterprise ...

A new semantic-driven search tool built on a ROS Package Knowledge Graph delivers over 21% higher accuracy than traditional methods, helping ...

Imagine you are on a treasure hunt in a vast library with no catalog—typing random words into a search bar and hoping to stumble upon the exact book ...

Among new treasures freely available online today for the first time are 60,000 pre-and-post famine names for family ...

However, the SIoT has the characteristics of both the IoT and the Semantic Web environment, and the corresponding semantic data present many new data features. In this article, we analyze the ...

Unsupervised word embeddings provide rich linguistic and conceptual information about words. However, they may provide weak information about domain specific semantic relations for certain tasks such ...

The Semantic Web is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable. This can be ...