Data Mining: The Knowledge Discovery of Data
Analytics Vidhya
FEBRUARY 20, 2023
This data is fed back to the product owners, who can then use it to […] The post Data Mining: The Knowledge Discovery of Data appeared first on Analytics Vidhya.
Knowledge Discovery Related Topics 
How Pharma Companies Can Scale Up Their Knowledge Discovery with Semantic Similarity Search
Ontotext
MARCH 4, 2020
The post How Pharma Companies Can Scale Up Their Knowledge Discovery with Semantic Similarity Search appeared first on Ontotext. Although this particular solution was developed for a very specific Pharma Regulatory use case , the system’s functionality applies to all types of domains because it is based on a generic technology.
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Webinars
Prepare Now: 2025s Must-Know Trends For Product And Data Leaders
Trending Sources
Knowledge Discovery, Data Gravity, and AI: Usama Fayyad & Gregory Piatetsky-Shapiro on the Data and AI Legends Podcast
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 30th Anniversary Interview with Founder Gregory Piatetsky-Shapiro
KDnuggets
SEPTEMBER 1, 2023
Gregory Piatetsky-Shapiro founded KDnuggets 30 years ago, after organizing early workshops on knowledge discovery. In this retrospective interview, he reflects on KDnuggets' growth, key innovations like deep learning, and concerns about AI's societal impact.
Ontotext Marketing Gets a Boost from Knowledge Graph Powered LLMs
Ontotext
MARCH 13, 2024
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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KDD 2020 Opens Call for Papers
Data Science 101
DECEMBER 11, 2019
This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). KDD 2020 welcomes submissions on all aspects of knowledge discovery and data mining, from theoretical research on emerging topics to papers describing the design and implementation of systems for practical tasks. 1989 to be exact.
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GraphDB in Action: Navigating Knowledge About Living Spaces, Cyber-physical Environments and Skies
Ontotext
AUGUST 3, 2023
Buildings That Almost Think For Themselves About Their Occupants The first paper we are very excited to talk about is Knowledge Discovery Approach to Understand Occupant Experience in Cross-Domain Semantic Digital Twins by Alex Donkers, Bauke de Vries and Dujuan Yang.
KDD 2020 Call for Research, Applied Data Science Papers
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.
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Are You Content with Your Organization’s Content Strategy?
Rocket-Powered Data Science
JULY 6, 2021
Techniques that both enable (contribute to) and benefit from smart content are content discovery, machine learning, knowledge graphs, semantic linked data, semantic data integration, knowledge discovery, and knowledge management.
Strategy 267
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On the Hunt for Patterns: from Hippocrates to Supercomputers
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. Again, the overall aim is to extract knowledge from data and, through algorithms based on artificial intelligence, to assist medical professionals in routine diagnostics processes.
4 ways generative AI addresses manufacturing challenges
IBM Big Data Hub
APRIL 15, 2024
Various initiatives to create a knowledge graph of these systems have been only partially successful due to the depth of legacy knowledge, incomplete documentation and technical debt incurred over decades. IBM also developed an accelerator for context-aware feature engineering in the industrial domain.
Unlocking the Power of Better Data Science Workflows
Smart Data Collective
MARCH 13, 2020
Phase 4: Knowledge Discovery. Phase 3: Data Visualization. With the data analyzed and stored in spreadsheets, it’s time to visualize the data so that it can be presented in an effective and persuasive manner. Finally, models are developed to explain the data. This four-stage workflow is just one framework – but it’s a good one.
Data Science 101
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Understanding Social And Collaborative Business Intelligence
datapine
NOVEMBER 19, 2019
The three most important aspects of collaborative business intelligence are as follows: Knowledge Discovery : When IT departments isolate a user’s experience to mere reports, it can be quite stifling.
Knowledge Graphs 101: The Story (and Benefits) Behind the Hype
Ontotext
NOVEMBER 11, 2024
Knowledge graphs expressed in RDF provide this as well as numerous applications in data and information-heavy services. Examples include intelligent content, packaging, and reuse; responsive and contextually aware content recommendation; automated knowledge discovery; semantic search; and intelligent agents.
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Why Establishing Data Context is the Key to Creating Competitive Advantage
Ontotext
AUGUST 22, 2023
Semantically integrated data makes metadata meaningful, allowing for better interpretation, improved search, and enhanced knowledge-discovery processes. Semantic metadata provides this by allowing a higher level of abstraction where deeper understanding of the data relationships is achieved.
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At Center Stage: 2 Ontotext Webinars About Reasoning with Big Knowledge Graphs and the Power of Cognitive Graph Analytics
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.
Bridging the Gap Between Industries: The Power of Knowledge Graphs – Part I
Ontotext
APRIL 6, 2023
To Wrap It Up Knowledge graphs play a vital role in connecting the data from siloed legacy systems and platforms, enabling seamless data sharing, knowledge discovery and analytics. This can lead to operational cost cutting and improve competitiveness.
Knowledge Graphs and Healthcare
Ontotext
APRIL 27, 2021
The knowledge graph seamlessly connects proprietary internal data with open public data to provide a single comprehensive view. Ontotext’s GraphDB’s unique inference capabilities infer new knowledge from existing facts, which adds extra explanatory power to their knowledge discovery.
Crafting a Knowledge Graph: The Semantic Data Modeling Way
Ontotext
FEBRUARY 19, 2020
Start delivering the answers to your original questions through different knowledge discovery tools such as SPARQL queries, semantic search, faceted search, data visualization, etc. As a result, your KG becomes more than the sum of its constituent datasets. Maximize the usability of your data.
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SIM Cards And Knowledge Graphs – Unseen But Valuable Technologies
Ontotext
AUGUST 10, 2023
They make this possible by adding domain knowledge that puts your organization’s data in context and enables its interpretation. Adding context and semantic consistency to the data, improves knowledge discovery, business analytics, and decision-making.
Technology 52
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How Do Super Rookies Start Learning Data Analysis?
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. For super rookies, the first task is to understand what data analysis is.
Ontotext’s Most Popular Blog Posts for 2019
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.
Designing a SemTech Proof-of-Concept: Get Ready for Our Next Live Online Training
Ontotext
AUGUST 15, 2019
Of course, this can mean a variety of things but we can start by thinking about: how to model the data to allow for its dynamic integration and reuse in the future; how to automate knowledge discovery; how to interlink data with other data sources (think Linked Open Data); what kind of auxiliary resources should we use, if at all; what kind of databases (..)
Top Graph Use Cases and Enterprise Applications (with Real World Examples)
Ontotext
MARCH 8, 2023
Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services. Linked Data, subscriptions, purchased datasets, etc.).
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Business Intelligence System: Definition, Application & Practice
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 practical applications, data mining is also used to mine the past and predict the future. Data Visualization.
Enrich your serverless data lake with Amazon Bedrock
AWS Big Data
SEPTEMBER 26, 2024
Across industries, this solution unlocks numerous use cases: Research and academia – Summarizing research papers, journals, and publications to accelerate literature reviews and knowledge discovery Legal and compliance – Extracting key information from legal documents, contracts, and regulations to support compliance efforts and risk management Healthcare (..)
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Three’s Company Too: Metadata, Data and Text Analysis
Ontotext
AUGUST 19, 2020
Faster and easier knowledge discovery has obvious cost benefits and reduces duplication of effort. Without metadata, the chances of finding anything you are looking for are near nil. Finding what you need through file structures on our personal computers is bad enough, never mind an enterprise-wide ICT.
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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All
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.
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From Data Silos to Data Fabric with Knowledge Graphs
Ontotext
SEPTEMBER 15, 2020
Start delivering the answers to your original questions through different knowledge discovery tools such as powerful SPARQL queries, easy to use GraphQL interface, semantic search, faceted search, data visualization, etc. It is also better interconnected, which brings more content and enables deeper analytics.
Metadata 69
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Designing a SemTech Proof-of-Concept: Get Ready for Our Next Live Online Training
Ontotext
AUGUST 16, 2019
Of course, this can mean a variety of things but we can start by thinking about: how to model the data to allow for its dynamic integration and reuse in the future; how to automate knowledge discovery; how to interlink data with other data sources (think Linked Open Data); what kind of auxiliary resources should we use, if at all; what kind of databases (..)
The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later
Ontotext
JULY 29, 2021
We rather see it as a new paradigm that is revolutionizing enterprise data integration and knowledge discovery. Ontotext was founded in 2000 with the Semantic Web in its genes and we had the chance to be part of the community of its pioneers. We can’t imagine looking at the Semantic Web as an artifact.
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Fundamentals of Data Mining
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). This data alone does not make any sense unless it’s identified to be related in some pattern.
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Enhancing Knowledge Discovery: Implementing Retrieval Augmented Generation with Ontotext Technologies
Ontotext
FEBRUARY 21, 2024
The post Enhancing Knowledge Discovery: Implementing Retrieval Augmented Generation with Ontotext Technologies appeared first on Ontotext. Or you can take things into your hands directly. Take advantage of the amazing set of new features introduced in GraphDB to place a conversational layer on top of your data!
Performing Non-Compartmental Analysis with Julia and Pumas AI
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. In this tutorial, we demonstrated how to carry out a simple Non-Compartmental Analysis.
Metrics 59
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Experiment design and modeling for long-term studies in ads
The Unofficial Google Data Science Blog
OCTOBER 7, 2015
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] Henne, Dan Sommerfield, Overall Evaluation Criterion , Proceedings 13th Conference on Knowledge Discovery and Data Mining, 2007.
Modeling 61
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GraphDB and metaphactory Part II: An RDF Database and A Knowledge Graph Platform in Action
Ontotext
OCTOBER 28, 2021
Knowledge discovery is one of the core strengths of metaphactory as it enables the creation of UIs that provide a user specific and tailored view on the knowledge graph.
ML internals: Synthetic Minority Oversampling (SMOTE) Technique
Domino Data Lab
MAY 20, 2021
Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. 30(2–3), 195–215. link] Ling, C. X., & Li, C. Data mining for direct marketing: Problems and solutions. Quinlan, J. Programs for machine learning. Morgan Kaufmann Publishers Inc. Everhart, J. Dickson, W. Knowler, W.
Machine Learning 136
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Changing assignment weights with time-based confounders
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. Henne, and Dan Sommerfield. 2] Scott, Steven L. armed bandit experiments in the online service economy." 2015): 37-45. [3]
Accelerating model velocity through Snowflake Java UDF integration
Domino Data Lab
JUNE 15, 2021
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. About Domino.
Modeling 69
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Data Mining Use Cases
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
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Understanding Social And Collaborative Business Intelligence
datapine
NOVEMBER 19, 2019
The three most important aspects of collaborative business intelligence are as follows: Knowledge Discovery : When IT departments isolate a user’s experience to mere reports, it can be quite stifling.
AI, the Power of Knowledge and the Future Ahead: An Interview with Head of Ontotext’s R&I Milena Yankova
Ontotext
APRIL 4, 2019
Source: Economy.bg. On March 19, 2019, Economy.bg interviewed Milena Yankova, Head of Research and Innovation for Ontotext. The conversation covered a wide range of topics from the tasks Artificial Intelligence (AI) can handle and the challenges it poses, to “fake news”, the intelligent enterprise of the future, cancer and much more.
Using Empirical Bayes to approximate posteriors for large "black box" estimators
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] 3] Bradley Efron, "Robbins, Empirical Bayes, and Microarrays" , Technical Report, 2003. [4]
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Variance and significance in large-scale online services
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, DC
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