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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

So, there must be a strategy regarding who, what, when, where, why, and how is the organization’s content to be indexed, stored, accessed, delivered, used, and documented. Labeling, indexing, ease of discovery, and ease of access are essential if end-users are to find and benefit from the collection. Do not forget the negations.

Strategy 267
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Advancing Automatic Knowledge Extraction with PubMiner AI

Ontotext

Using PubMiner AI as a blueprint enables any skilled data scientist with basic knowledge of semantic technologies (knowledge graphs, RDF, SPARQL, ontologies, and semantic models) to build a targeted workflow that can extract intricate relations between biomedical entities from scientific literature.

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How Pharma Companies Can Scale Up Their Knowledge Discovery with Semantic Similarity Search 

Ontotext

First of all, this solution is able to ingest large amounts of various documents in various formats and to automatically extract and classify pairs of questions and answers. From this processed data a knowledge graph (KG) is created. Then it returns the top 10 most similar Q&A pairs from the database.

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Understanding Social And Collaborative Business Intelligence

datapine

Discovery and documentation serve as key features in collaborative BI. This kind of analysis leads to feedback that can aid in improving the decision-making process, letting companies document the best practices and monitor the data that’s the most useful in this scenario. However, collaborative BI helps in changing that.

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Ontotext Marketing Gets a Boost from Knowledge Graph Powered LLMs

Ontotext

We expose this classified content by flexible semantic faceted search with the help of metaphacts’ knowledge graph platform metaphactory. These steps help pave the way to integrate the knowledge graph with large language models (LLMs) and provide state-of-the-art knowledge discovery and exploration.

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Enrich your serverless data lake with Amazon Bedrock

AWS Big Data

Organizations are collecting and storing vast amounts of structured and unstructured data like reports, whitepapers, and research documents. End-users often struggle to find relevant information buried within extensive documents housed in data lakes, leading to inefficiencies and missed opportunities.

Data Lake 115
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Understanding Social And Collaborative Business Intelligence

datapine

Discovery and documentation serve as key features in collaborative BI. This kind of analysis leads to feedback that can aid in improving the decision-making process, letting companies document the best practices and monitor the data that’s the most useful in this scenario. However, collaborative BI helps in changing that.