Ontotext

MARCH 4, 2020

Pharma has deep roots in human history with centuries of folk pharmaceutical knowledge offering a hit-and-miss range of natural remedies. From this processed data a knowledge graph (KG) is created.

Knowledge Discovery 52

Knowledge Discovery Manufacturing Finance Technology 52

KDnuggets

FEBRUARY 15, 2022

Public understanding of AI applications usually goes through a phase shift, from "it cannot be done" to "of course, a computer can do it". KDnuggets Originals Data Science

Knowledge Discovery 59

Knowledge Discovery IT Data Science 59

TDAN BI

JUNE 15, 2022

Big Data Blogs Big Data News, Articles, & Education Business Intelligence Blogs Business Intelligence News, Articles, & Education Data Blogs Data Education Data Strategy Blogs Data Strategy News, Articles, & Education Data Topics data mining knowledge discovery lau use cases

Data mining 82

Data mining Knowledge Discovery Forecasting Marketing 82

Ontotext

APRIL 4, 2019

We apply Artificial Intelligence techniques to understand the value locked in this data so we can extract knowledge that can benefit people. Milena Yankova : Our work is focused on helping companies make sense of their own knowledge. Some of this knowledge is locked and the company cannot access it. into structured knowledge that can be processed by machines. ” Then this knowledge can be downloaded from the network. Source: Economy.bg.

Knowledge Discovery 64

Knowledge Discovery Testing Enterprise Metrics 64

Data Science 101

DECEMBER 11, 2019

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Topics of interest include artificial intelligence, big data, data analytics, data science, data mining, deep learning, knowledge graphs, machine learning, relational databases and statistical methods.

KDD 72

KDD Knowledge Discovery Data mining Statistics 72

DataFloq

FEBRUARY 10, 2021

Business Analytics synergizes the strengths of various sciences including data mining, knowledge discovery, machine learning, pattern recognition, statistics, neurocomputing, and artificial intelligence. Business Analytics has evolved a lot. Business Analytics was designed for addressing the need for deriving intelligence out of ‘data’, which is nowadays referred to affectionately by many as the ‘crude oil’ or ‘gold ore’ of modern times.

Business Analytics 205

Business Analytics Knowledge Discovery Analytics Data mining 205

KDnuggets

DECEMBER 12, 2019

ACM SIGKDD Invites Industry and Academic Experts to Submit Advancements in Data Mining, Knowledge Discovery and Machine Learning for 26 th Annual Conference in San Diego. 2019 Dec Events Applications CA KDD KDD-2020 Research San Diego

KDD 40

KDD Knowledge Discovery Data mining Machine Learning 40

DataFloq

JULY 4, 2022

Combining large amounts of information with existing tools is possible using the formalized knowledge discovery models in Data Science or Data Mining techniques. Data Science is a growing field that has emerged in many key areas of our world.

Data Science 242

Data Science Knowledge Discovery Statistics Predictive Analytics 242

Rocket-Powered Data Science

JULY 6, 2021

Labeling, indexing, ease of discovery, and ease of access are essential if end-users are to find and benefit from the collection. Contextual TAM enhances a CMS with knowledge-driven search and retrieval, not just keyword-driven. Labels are curated and stored with the content, thus enabling curation, cataloguing (indexing), search, delivery, orchestration, and use of content and data in AI applications, including knowledge-driven decision-making and autonomous operations.

Strategy 208

Strategy Data Science Internet of Things Metadata 208

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. And this is what Ontotext’s role in the project is about: knowledge graphs. Blog Business ExaMode knowledge graph supercomputer

Knowledge Discovery 65

Knowledge Discovery Experimentation Metadata Data Processing 65

datapine

NOVEMBER 19, 2019

Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data discovery tools available in the market to take their brand forward. One of the most imperative features of social BI is its ability to create self-served and user-generated analysis, coupled with the application of business user knowledge. It also facilitates BI tool user adoption, allowing the organization to share knowledge and resources.

Business Intelligence 131

Business Intelligence Knowledge Discovery Dashboards IoT 131

Ontotext

APRIL 27, 2021

The richness of data, if it can be discovered, enables the discovery of novel therapies, causal relationships or, just as important, retrieving existing negative results so that the company doesn’t spend millions of dollars to discover what is already known not to work.

Knowledge Discovery 56

Knowledge Discovery Insurance Unstructured Data Testing 56

Ontotext

AUGUST 26, 2021

This post continues the series of posts we started with At Center Stage: 2 Ontotext Webinars About Reasoning with Big Knowledge Graphs and Power of Graph Analytics. Reasoning with Big Knowledge Graphs: Choices, Pitfalls and Proven Recipes.

Knowledge Discovery 52

Knowledge Discovery Optimization Enterprise Analytics 52

Smart Data Collective

MARCH 13, 2020

Phase 4: Knowledge Discovery. My aim with any notebook is to enable someone to pick it up without any prior knowledge of the project and fully understand the analysis, decisions made and what the final output means,” Osborne explains.

Data Collection 84

Data Collection Data Science Key Performance Indicator Knowledge Discovery 84

FineReport

JULY 16, 2021

It is a process of using knowledge discovery tools to mine previously unknown and potentially useful knowledge. It is an active method of automatic discovery. In daily work, when business develops to a relatively large scale, we will all face variable management problems.

Business Intelligence 83

Business Intelligence Informatics OLAP Data Warehouse 83

Ontotext

JULY 29, 2021

The Semantic Web, both as a research field and a technology stack, is seeing mainstream industry interest, especially with the knowledge graph concept emerging as a pillar for data well and efficiently managed. What can it do and how are enterprise knowledge graphs related to it?

Enterprise 99

Enterprise Metadata Knowledge Discovery Management 99

Ontotext

FEBRUARY 19, 2020

The term “knowledge graph” (KG) has been gaining popularity for quite a while now. Although there is still no single, universally accepted definition, there have been various attempts at it – such as in Towards a Definition of Knowledge Graphs.

Modeling 77

Modeling Knowledge Discovery Data Quality Digital Transformation 77

FineReport

DECEMBER 19, 2019

Data analysis is a type of knowledge discovery that gains insights from data and drives business decisions. Professional data analysts must have a wealth of business knowledge in order to know from the data what has happened and what is about to happen.

Knowledge Discovery 83

Knowledge Discovery Experimentation Visualization Dashboards 83

Ontotext

AUGUST 15, 2019

But it has enriched us in terms of identifying key needs for those looking to build a simple prototype in order to demonstrate the power of semantic technology, linked data and knowledge graphs. Semantic technology is a broad technological term that covers specific technological approaches, principles and methodologies for managing data and knowledge. This will lay solid foundations for the rest of the work necessary for implementing a full, working knowledge graph solution.

Knowledge Discovery 60

Knowledge Discovery Metadata Interactive Modeling 60

Ontotext

FEBRUARY 17, 2022

But no system, even such a highly mature RDF database for knowledge graphs as ours, is an island. The very first post of this series presented two knowledge graph maps with 20+ applications and 30+ capabilities. Knowledge Graphs: 5 Use Cases and 10 Steps to Get There.

Knowledge Discovery 52

Knowledge Discovery Enterprise Data Processing Data Integration 52

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. Here’s our countdown: It Takes Two to Tango: Knowledge Graphs and Text Analysis.

Knowledge Discovery 52

Knowledge Discovery Publishing Enterprise Technology 52

Ontotext

AUGUST 19, 2020

To ensure the metadata extracted is of high-quality, Ontotext uses knowledge graphs to increase the performance of its text analysis services. The text analysis is also able to identify gaps in the knowledge graph such as concepts and relationships previously unidentified.

Metadata 56

Metadata Knowledge Discovery Cost-Benefit Enterprise 56

Domino Data Lab

AUGUST 1, 2021

Conference on Knowledge Discovery and Data Mining, pp. In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model.

Modeling 110

Modeling Testing Knowledge Discovery Deep Learning 110

Domino Data Lab

MAY 20, 2021

Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed.

Knowledge Discovery 108

Knowledge Discovery Metrics Data mining Measurement 108

Ontotext

SEPTEMBER 15, 2020

Knowledge Graphs are the Warp and Weft of a Data Fabric. Given a critical mass of domain knowledge and good level of connectivity, KG can serve as context that helps computers comprehend and manipulate data. Ontotext’s Platform for Enterprise Knowledge Graphs.

Knowledge Discovery 63

Knowledge Discovery Data Quality Enterprise Data Processing 63

The Unofficial Google Data Science Blog

JULY 22, 2020

Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

Experimentation 80

Experimentation Statistics Testing Knowledge Discovery 80

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). Domain Knowledge. The foremost step of this process is to possess relevant domain knowledge regarding the problem at hand. To anyone looking at a large pile of data, it may seem like a collection of junk unless the person has the background knowledge and information about the business.

Data mining 65

Data mining KDD Knowledge Discovery Forecasting 65

Domino Data Lab

DECEMBER 4, 2020

The openness of the Domino Data Science platform allows us to use any language, tool, and framework while providing reproducibility, compute elasticity, knowledge discovery, and governance.

Metrics 56

Metrics Knowledge Discovery Experimentation Modeling 56

Ontotext

AUGUST 16, 2019

But it has enriched us in terms of identifying key needs for those looking to build a simple prototype in order to demonstrate the power of semantic technology, linked data and knowledge graphs. Semantic technology is a broad technological term that covers specific technological approaches, principles and methodologies for managing data and knowledge. This will lay solid foundations for the rest of the work necessary for implementing a full, working knowledge graph solution.

Knowledge Discovery 40

Knowledge Discovery Metadata Interactive Modeling 40

Ontotext

OCTOBER 28, 2021

In our previous post, we covered the basics of how the Ontotext and metaphacts joint solution based on GraphDB and metaphactory helps customers accelerate their knowledge graph journey and generate value from it in a matter of days. Building a Knowledge Graph Application with metaphactory.

Visualization 52

Visualization Interactive Knowledge Discovery Dashboards 52

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

This knowledge has influenced our decision-making way beyond the concrete cases we studied in detail. We use this knowledge to define objective functions to optimize our ads system with a view towards the long-term. 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]

Data Science 54

Data Science Experimentation KDD Testing 54

Domino Data Lab

JUNE 15, 2021

The data science team grows and people can’t work in isolation anymore – they need to be able to share knowledge, handover projects, and have validation and reproducibility capabilities at their disposal.

Modeling 63

Modeling Knowledge Discovery Data Science Data Warehouse 63

datapine

NOVEMBER 19, 2019

Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data Discovery tools available in the market to take their brand forward. One of the most imperative features of social BI is its ability to create self-served and user-generated analysis, coupled with the application of business user knowledge. It also facilitates BI tool user adoption, allowing the organization to share knowledge and resources.

Business Intelligence 20

Business Intelligence Knowledge Discovery IoT Dashboards 20

The Unofficial Google Data Science Blog

JANUARY 14, 2016

References [1] Diane Tang, Ashish Agarwal, Deirdre O'Brien, Mike Meyer, “ Overlapping Experiment Infrastructure: More, Better, Faster Experimentation ”, Proceedings 16th Conference on Knowledge Discovery and Data Mining, Washington, DCby AMIR NAJMI Running live experiments on large-scale online services (LSOS) is an important aspect of data science.

Data Science 41

Data Science Experimentation Statistics Metrics 41

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

Brendan McMahan et al, "Ad Click Prediction: a View from the Trenches" , Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2013. [3] by OMKAR MURALIDHARAN Many machine learning applications have some kind of regression at their core, so understanding large-scale regression systems is important. But doing this can be hard, for reasons not typically encountered in problems with smaller or less critical regression systems.

Data Science 40

Data Science KDD Testing Modeling 40

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

References [1] Diane Tang, Ashish Agarwal, Deirdre O’Brien, Mike Meyer, “ Overlapping Experiment Infrastructure: More, Better, Faster Experimentation ”, Proceedings 16th Conference on Knowledge Discovery and Data Mining, Washington, DCby AMIR NAJMI In the previous post we looked at how large scale online services (LSOS) must contend with the high coefficient of variation (CV) of the observations of particular interest to them.

Data Science 40

Data Science Experimentation Metrics Statistics 40