Natural Language Processing & Semantic Models in an Imperfect World
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Alitora Systems develops natural language processing and semantic modeling technologies. Their system uses NLP to extract entities, relationships, and metadata from text and stores this information in a semantic knowledge graph. The knowledge graph uses ontologies and named graphs to represent uncertainty and relationships in the extracted data. Clients can query, analyze, and infer new knowledge from the graph to build applications that make relevant recommendations and matches.
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In this talk, we'll cover some of the emerging trends in AI-powered search, including the use of thought vectors (multi-level vector embeddings) and semantic knowledge graphs to contextually interpret and conceptualize queries. We'll walk through some live query interpretation demos to demonstrate the power that can be delivered through these semantic search techniques leveraging auto-generated knowledge graphs learned from your content and user interactions.
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Ben Ryan (University of Leeds) – Timescapes Project
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IC-SDV 2019: OntoChem
The OntoChem IT Solutions GmbH ...
... was founded in 2015 as a purely IT-oriented offshoot of the OntoChem GmbH. Even before we had many years of experience and it has always been our mission to provide added value to our customers by helping them to navigate today’s complex information world by developing cognitive computing solutions, indexing intranet and internet data and applying semantic search solutions for pharmaceutical, material sciences and technology driven businesses.
We strive to support our customers with the most useful tools for knowledge discovery possible, encompassing up-to-date data sources, optimized ontologies and high-throughput semantic document processing and annotation techniques.
We create new knowledge from structured and unstructured data by extracting relationships thereby exploiting the full potential of full-text documents & databases while also scanning social media, news flows and analyzing web-pages.
We aim at an unprecedented, machine understanding of text and subsequent knowledge extraction and inference. The application of our methods towards chemical compounds and their properties supports our customers in generating intellectual property and their use as novel therapeutics, agrochemical products, nutraceuticals, cosmetics and in the field of novel materials.
It's our mission to provide added value to customers by:
developing and applying cognitive computing solutions
creating intranet and internet data indexing and semantic search solutions
Big Data analytics for technology driven businesses
supporting product development and surveillance.
We deliver useful tools for knowledge discovery for:
creating background knowledge ontologies
high-throughput semantic document processing and annotation
knowledge mining by extracting relationships
exploiting the full potential of full-text documents & databases while also scanning social media, news flows and analyzing web-pages.
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II-DV 2017: Averbis
Averbis is specialized in the area of text mining and machine-learning-based patent monitoring. We help our clients screen large numbers of patents in no time, estimate their relevancy for the company and automatically classify them into customer-specific categories. Our approach is based on artificial intelligence – with the result that it learns from and imitates the behavior of IP professionals. Compared to conventional rule-based approaches, our approach is up to 400% more accurate and achieves the same accuracy offered by manual monitoring. At the same time, it reduces manual patent monitoring intervention by up to 80%. Thanks to Information Discovery, we enable IP professionals to reduce backlogs, improve staff efficiency and minimize inconsistencies associated with patent monitoring, ultimately improving the experience both for you and your customers.
Cedar OnDemand: An intelligent browser extension to generate ontology-based m...
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CEDAR OnDemand is a Chrome browser extension that helps users create standardized metadata on web forms. It utilizes ontology web services from NCBO to provide controlled vocabularies for metadata fields. When activated on a web form, it analyzes the form and recommends relevant ontology terms based on field descriptions. This allows standardized metadata creation within existing repository interfaces without code changes. The goal is to facilitate high-quality FAIR metadata generation through public repository submission forms.BIOMAG2018 - Denis Engemann - MNE-HCP
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Tutorial@BDA 2017 -- Knowledge Graph Expansion and Enrichment
Tutorial@BDA 2017 -- Knowledge Graph Expansion and Enrichment
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A Generic Scientific Data Model and Ontology for Representation of Chemical Data
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Natural Language Search with Knowledge Graphs (Haystack 2019)
Natural Language Search with Knowledge Graphs (Haystack 2019)
Thought Vectors and Knowledge Graphs in AI-powered Search
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HyQue: Evaluating scientific Hypotheses using semantic web technologies
HyQue: Evaluating scientific Hypotheses using semantic web technologies
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Cedar OnDemand: An intelligent browser extension to generate ontology-based m...
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HCI 3e - Ch 12: Cognitive models
Chapter 12: Cognitive models
from
Dix, Finlay, Abowd and Beale (2004).
Human-Computer Interaction, third edition.
Prentice Hall. ISBN 0-13-239864-8.
http://www.hcibook.com/e3/
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https://ucsb.zoom.us/meeting/register/tZYod-ippz4pHtaJ0d3ERPIFy2QIvKqjwpXR
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[1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18
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This talk was recorded in London on Oct 30, 2018 and can be viewed here: https://youtu.be/p4iAnxwC_Eg
The good news is building fair, accountable, and transparent machine learning systems is possible. The bad news is it’s harder than many blogs and software package docs would have you believe. The truth is nearly all interpretable machine learning techniques generate approximate explanations, that the fields of eXplainable AI (XAI) and Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) are very new, and that few best practices have been widely agreed upon. This combination can lead to some ugly outcomes!
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He obtained his M.Sc. in Computer Science from AGH UST in Krakow, Poland, during which he did an exchange at L’ECE Paris in France and worked on distributed flight booking systems. After graduation he move to Tokyo to work as a researcher at Fujitsu Laboratories on machine learning and NLP projects, where he is still currently based.
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Essentials of Automations: Exploring Attributes & Automation Parameters
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Must Know Postgres Extension for DBA and Developer during Migration
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
Mutation Testing for Task-Oriented Chatbots
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
Taking AI to the Next Level in Manufacturing.pdf
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
AppSec PNW: Android and iOS Application Security with MobSF
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Demystifying Knowledge Management through Storytelling
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
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