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Incremental Machine Learning for Linked Data Event Streams

Towards AI

Last Updated on February 13, 2023 by Editorial Team Author(s): Samuel Van Ackere Originally published on Towards AI. The potential of using incremental machine learning becomes more and more apparent when working on fast-moving Linked Data Event Streams (LDES). LDES workbench in Apache NIFI (Image by the author.)

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Linked Data Event Streams and TimescaleDB for Real-time Timeseries Data Management

Towards AI

Last Updated on March 1, 2023 by Editorial Team Author(s): Samuel Van Ackere Originally published on Towards AI. This allows data to be linked and connected to other data sources using unique identifiers (URIs). First, a data flow must be configured to ingest a Linked Data Event Stream into PostgreSQL.

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Saldor: The Web Scraper for AI

Marktechpost

The quantity and quality of data directly impact the efficacy and accuracy of AI models. Getting accurate and pertinent data is one of the biggest challenges in the development of AI. LLMs require current, high-quality internet data to address certain issues. It is challenging to compile data from the internet.

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Building cars in a changing world: Audi’s Integrated Approach with IBM Planning Analytics

IBM Journey to AI blog

It was equally important that this infrastructure contained consistent metadata and data structures across all entities, preventing data redundancy and streamlining processes. The primary goal in adopting a planning and analytics solution was to link data and processes across departments.

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This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines

Marktechpost

Modeling the underlying academic data as an RDF knowledge graph (KG) is one efficient method. This makes standardization, visualization, and interlinking with Linked Data resources easier. As a result, scholarly KGs are essential for converting document-centric academic material into linked and automatable knowledge structures.

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Multilingual Named Entity Recognition for Knowledge Graphs: Supporting 70+ Languages with Precision

Bitext

In the era of data-driven decision-making, Knowledge Graphs (KGs) have emerged as pivotal tools for structuring, organizing, and interconnecting vast amounts of information. From enhancing search engine capabilities to powering AI-driven insights, KGs rely heavily on extracting, interpreting, and linking data elements with precision.

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Meet David AI: The Data Marketplace for AI

Marktechpost

Improving AI is complicated by data, as the amount of training data required for each new model release has increased significantly. This burden is further worsened by the growing problem of finding useful, compliant data in the open domain. Meet David AI , the artificial intelligence data marketplace.