datapine

NOVEMBER 19, 2019

Social BI indicates the process of gathering, analyzing, publishing, and sharing data, reports, and information. Discovery and documentation serve as key features in collaborative BI. Using related data, content, and the business context behind findings, users can add their own knowledge to the results of business intelligence.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

Ontotext

DECEMBER 1, 2023

Krasimira touched upon the ways knowledge graphs can harness unstructured data and enhance it with semantic metadata. She also shared the architecture behind the vision of building useful semantic search, valuable insights platform, and powerful knowledge discovery environment.

Metadata 78

Metadata Sales Consulting Enterprise 78

Ontotext

AUGUST 19, 2020

Inevitably, the information that could and needed to be expressed by metadata increased in complexity. Metadata started including descriptions and source information. The consequence is that information becomes understood by both machine and human users. More useful organization of information.

Metadata 59

Metadata Knowledge Discovery Cost-Benefit Data Governance 59

Ontotext

DECEMBER 30, 2019

As 2019 comes to an end, we at Ontotext are taking stock of the most fascinating things we have done to empower knowledge management and knowledge discovery this year. In 2019, Ontotext open-sourced the front-end and engine plugins of GraphDB to make the development and operation of knowledge graphs easier and richer.

Knowledge Discovery 52

Knowledge Discovery Publishing Technology Enterprise 52

Ontotext

APRIL 6, 2023

Another important standard in terms of logistics and supply chain management is EPCIS, which is enabled by IoT technologies and provides real-time tracking information. By using knowledge graphs, companies can gain a more holistic view of their operations, make better-informed decisions and optimize their processes.

Manufacturing 83

Manufacturing Cost-Benefit Knowledge Discovery Optimization 83

Ontotext

MARCH 8, 2023

A graph solution allows us to create a connection layer that facilitates consistent aggregation and ingestion of diverse information types from sources, internal or external, to the organization. However, this information is typically stored in disparate locations, often hidden within departmental documents or applications.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Ontotext

SEPTEMBER 15, 2020

There are several characteristics of the knowledge graph that make this possible: The formal semantics of the RDF standards stack, and the use of ontologies , allows data and metadata of different types to be represented in a KG in such a way that they can be analyzed and interpreted together, without ambiguity, clashes or loss of information.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Ontotext

AUGUST 26, 2021

The second Ontotext webinar Graph Analytics on Company Data and News focuses on the power of cognitive graph analytics to create links between various datasets and to lead to powerful knowledge discovery.

Knowledge Discovery 52

Knowledge Discovery Analytics Enterprise Optimization 52

Ontotext

OCTOBER 28, 2021

often want to find information about a particular medical product, for example, if any serious adverse reactions have been reported for it. FROCKG (Fact Checking for Large Enterprise Knowledge Graphs) is a Eurostars-2 project that aims to develop efficient approaches to ensure the veracity of facts contained in enterprise knowledge graphs.

Visualization 52

Visualization Interactive Knowledge Discovery Dashboards 52

TDAN

JUNE 15, 2022

“Information is the oil of the 21st century, and analytics is the combustion engine,” says Peter Sondergaard, former Global Head of Research at Gartner. And he has a point. Given that the global big data market is forecast to be valued at $103 billion in 2027, it’s worth noticing. As the amount of data generated […].

Data mining 98

Data mining Forecasting Big Data Marketing 98

Data Science 101

OCTOBER 31, 2019

Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). It is used to extract information from the raw data in databases… “ Overview. The foremost step of this process is to possess relevant domain knowledge regarding the problem at hand.

Data mining 77

Data mining KDD Data Science Forecasting 77

Ontotext

APRIL 4, 2019

Milena Yankova : We help the BBC and the Financial Times to model the knowledge available in various documents so they can manage it. The BBC keeps information on every show, every actor, every athlete, about all the content that the BBC has ever produced for its departments. He needs to know what information this data carry.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

A/B testing is used widely in information technology companies to guide product development and improvements. References [1] Henning Hohnhold, Deirdre O'Brien, Diane Tang, Focus on the Long-Term: It's better for Users and Business , Proceedings 21st Conference on Knowledge Discovery and Data Mining, 2015. [2]

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

datapine

NOVEMBER 19, 2019

Social BI indicates the process of gathering, analyzing, publishing, and sharing data, reports, and information. Discovery and documentation serve as key features in collaborative BI. With the help of collaborative methods, workers are able to share information such as why certain events are unfolding in a particular way and so on.

Business Intelligence 20

Business Intelligence Knowledge Discovery Unstructured Data Software 20

Ontotext

MAY 18, 2020

These are the so-called supercomputers, led by a smart legion of researchers and practitioners in the fields of data-driven knowledge discovery. The project is coordinated by the Institute of Information Systems of the HES-SO Valais-Wallis, Sierre, Switzerland. Information source: H2020 grant for Computational Pathology ].

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Because individual observations have so little information, statistical significance remains important to assess. In this post we explore how and why we can be “ data-rich but information-poor ”. This means that each observation has little information, and we need a lot of observations to make reliable statements.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Ontotext

AUGUST 10, 2023

It’s a small, if complex, thing that quietly facilitates your ability to communicate and access information across various platforms. Interestingly, SIM cards share a striking similarity with another technology that’s gaining popularity, that of knowledge graphs. Haven’t heard of knowledge graphs?

Technology 52

Technology Knowledge Discovery Interactive Enterprise 52

FineReport

JULY 16, 2021

With the advancement of information construction, enterprises have accumulated massive data base. Companies employ BI systems to deliver right information to right person at the right time with a right format. BI software integrates useful BI tools to present clear and informative interfaces by easy dragging and dropping.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

Ontotext

JULY 29, 2021

KGs bring the Semantic Web paradigm to the enterprises, by introducing semantic metadata to drive data management and content management to new levels of efficiency and breaking silos to let them synergize with various forms of knowledge management. Ultimately, for the latest reincarnation of the field: the knowledge graph. What is it?

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

Ontotext

FEBRUARY 19, 2020

The term “knowledge graph” (KG) has been gaining popularity for quite a while now. Today, as the number of decision-makers recognizing the importance of more dynamic, contextually aware and intelligent information architectures is growing, so is the number of companies with solutions based on knowledge graphs.

Modeling 90

Modeling Knowledge Discovery Data Quality Visualization 90

Ontotext

APRIL 27, 2021

Typical of healthcare use cases, this required pulling together concepts from genomics, proteomics, metabolomics, disease conditions, drug products, scientific literature and various biomedical ontologies, integrated information from a variety of open datasets.

Knowledge Discovery 59

Knowledge Discovery Unstructured Data Insurance Testing 59

The Unofficial Google Data Science Blog

JULY 22, 2020

Since so many users were given the feature in earlier epochs, there’s a lot of information being left on the table if you were to ignore these epochs. Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining. So combining data from epochs is attractive. Henne, and Dan Sommerfield.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Ontotext

FEBRUARY 21, 2024

RAG and Ontotext offerings: a perfect synergy RAG is an approach for enhancing an existing large language model (LLM) with external information provided as part of the input prompt, or grounding context. So we can easily integrate the information from both textual documents and structured RDF entities into an LLM-driven application.

Knowledge Discovery 64

Knowledge Discovery Technology Metadata Data-driven 64

Domino Data Lab

MAY 20, 2021

The electrotopological state: Structure information at the atomic level for molecular graphs. Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. The unreasonable effectiveness of data. IEEE Intelligent Systems, 24(2), 8–12. link] Hall, L., Mohney, B., & Kier, L. Japkowicz, N.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Domino Data Lab

JUNE 15, 2021

Add a manifest file, which contains meta information about what exactly is included in your JAR file. This facilitates knowledge discovery, handover, and regulatory compliance, and allows the individual data scientists to focus on work that accelerates research and speeds model deployment. You can use the Java jar command.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

These decisions are often business-critical, so it is essential for data scientists to understand and improve the regressions that inform them. In our model, $theta$ doesn’t depend directly on $x$ — all the information in $x$ is captured in $t$. To make sure, and to improve our priors using information from nearby bins, we can smooth.

KDD 40

KDD Testing Machine Learning Modeling 40

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

In this post we explore why some standard statistical techniques to reduce variance are often ineffective in this “data-rich, information-poor” realm. Another way to think about this is that the purpose of stratification is to use side information to group observations which are more similar within strata than between strata.

Experimentation 40

Experimentation Metrics Statistics Measurement 40

Ontotext

AUGUST 31, 2023

The growth of large language models drives a need for trusted information and capturing machine-interpretable knowledge, requiring businesses to recognize the difference between a semantic knowledge graph and one that isn’t—if they want to leverage emerging AI technologies and maintain a competitive edge.

Modeling 64

Modeling Optimization Knowledge Discovery Enterprise 64