Your next storefront visitor may not be a person at all. It may be a large language model (LLM) deciding whether to recommend ...

These third-party projects greatly expand the ways agents and LLMs can draw on facts, documents, and conversations to deliver ...

While AI holds the promise of radically transforming KM, human oversight takes on intensified responsibilities for ensuring the knowledge provided is accurate, timely, and relevant as well as guarding ...

Abstract: Applied to search, question answering, and semantic web of close-or-open domain, knowledge graph (KG) is known for its incompleteness subject to the rapid knowledge growing pace. Inspired by ...

Abstract: The challenge of knowledge graph construction from unstructured text is a fundamental challenge in knowledge representation, especially in cases of informal text and narrative, such as that ...

The term “knowledge graph” has been around since 1972, but its current definition can be traced back to Google in 2012. This was followed by similar announcements from companies such as Airbnb, Amazon ...

To gain competitive advantage from gen AI, enterprises need to be able to add their own expertise to off-the-shelf systems. Yet standard enterprise data stores aren't a good fit to train large ...

From learning the history of search to distinguishing entities vs. keywords, truly understand what entities are so you can achieve more targeted search traffic. There is a lot of confusion about how ...

For all its benefits in optimizing processes and informing decision-making in businesses, generative AI’s credibility for real use cases is hindered by a lack of accuracy, transparency and ...