Poolparty Summit 2021

November 3 – 4, 2021 | Online

From Unknowable Chaos to Knowledge Graph: Making Complex Information Environments Useful and Usable

Leveraging User Intent in Content Management for Impactful Outcomes

Recommender Systems that Work

Recommender systems are widely used in e-commerce platforms, where users regularly receive unsuitable tips because they are based on the principle ‘suggest more of the same’. In other words: I buy a couch and get recommended another couch the next time I’m on the website.

The clear problem in this case, is that the average consumer typically does not need a second couch once they’ve already purchased one. While humans can understand this next logical step, a machine recommender system cannot process any of this underlying contextual information so it does not really respond well to individual customer wishes.
As current solutions fall short, web store assistants and recommender systems in knowledge-intensive business processes require different methodologies to provide users with truly relevant information, suggestions, and ‘best next actions’ that are actually helpful. Using the initial example: a better recommendation would be to buy a coffee table to complete my living room, since I have a couch already. A recommender system powered by semantic reasoner has the capacity to deliver a personal and more effective purchasing experience. The powerful combination of PoolParty and RDFox, the high-performance knowledge graph and reasoner, does just that.

The optimised in-memory approach of RDFox provides unmatched speeds, while its unique, highly advanced reasoning capabilities ensure deep insights are extracted from data. Driving the rich and dynamic PoolParty, RDFox is the perfect candidate for a recommender system—together not only do they provide near real-time results, but meaningful suggestions that assist the user and act as a genuine guide to the things they desire. 

Employee 360 in Action

Moving to a Data-Centric World: Building a Consumer Health Data Fabric

Question Answering over Semantically Annotated Documents

Why 360? – It’s All About Improving the Content-Driven Experience

In this session, we will explore how we can use semantic AI and knowledge graphs to inform and improve the content-driven experience at every step along the content supply chain journey. We’ll travel from the creation and organization of the content through to the presentation and measurement of the content’s performance.

By the end of this session, you should be able to take away several concrete ideas and begin implementing them immediately. Our goal is to help you improve the quality, relevancy and efficiency of your content experiences at every step along the content supply chain using ontologies and semantic AI.

Enterprise 360 – Creating Holistic Views of Heterogeneous Data

Enterprise 360 helps to better address individual information needs and contexts, providing relevant information about products, markets, customers, as well as related knowledge and learning content.

Improving Safety and Reliability in Industrial Operations using Semantic AI

This talk describes how semantic web technology can be used to effectively address this challenge using an operations management knowledge graph.

How PoolParty Helps Us to Model Our Product Knowledge Graph and Keep Semantic Standards

For 3 years I have been working on the construction of the publication platform that allows our brands to respond to the new challenges of e-commerce and omnichannel. I am currently working on the design of the knowledge graph which allows us to exploit our knowledge of the products and thus to better support our customers, in particular through the internal search engine and the product recommendation.

Knowledge graphs in machinery and plant engineering

Machinery and plant engineering companies all over the world are highly interested in the use of knowledge graphs at the moment. We show two different use cases based on customer projects.

Companies have to offer their customers excellent service. To do this, support organisations need various information such as technical product data, spare parts information or repair instructions. Knowledge graphs can be used to provide this information intelligently. We demonstrate how relevant information is connected in knowledge graphs to quickly provide service technicians with all information in a service portal, thus improving and shortening the service process.

And by the way, digital twins won’t work without knowledge graphs either.

PoolParty Semantic Suite: Roadmap and Outlook

In this talk at the end of the PoolParty Summit, Andreas will recap and analyze where we are today with knowledge graph technologies and semantic AI, where the PoolParty platform is today and make an outlook to 2023 to finally dare a forecast for 2030.

Where will graph technologies be then, are they really as disruptive as some analysts claim, will they really completely redefine enterprise information management?

An ontology for a universal guidance journey

When the average person changes jobs 12 times in their lifetime, the search for meaning at work is critical. It becomes increasingly important to focus on vocational interests, occupational values, or soft skills to create career paths that are desirable, sustainable, and reduce employee turnover. JobTeaser builds psychometric tools and exercises to capture this information and enrich self-awareness using semantic data. PoolParty not only enables to quickly model and easily distribute data for new domains, but also to create alignment with key dimensions within our career centers, leveraging innovative ways for HR professionals and career counselors to engage with students and young graduates.

Scaling up PoolParty with GraphDB

Organisations are constantly facing the challenges of disparate data silos among departments as well as departmental tools. Structured and unstructured data is buried and unattainable, making it hard to gain a 360 degree view of everything that is going on within their organization. Knowledge graphs address this need by integrating silos in a standards-based manner. More and more organizations are adopting this approach as they understand the business value.

Knowledge graphs are data. They have to be stored, managed, extended, governed, quality-assured and can be queried. This requires databases and components on top, which are usually implemented in the Semantic Middleware Layer.

Graph DB and PoolParty partner together to provide a fully integrated solution that combines a market-leading end-to-end technology stack with professional services. The partnership offers enterprise-ready solutions that enable companies to achieve full control of their data through the use of visionary Graph Database and Enterprise Knowledge Graph technology.

Improving Experiences Through A 360 Taxonomical Approach

In today’s dynamic work environment where spaces are changing from remote to hybrid to in-office, it’s becoming increasingly difficult to navigate and optimize the employee journey for better business value.

A 360 approach connects an organization’s most valued assets, their people, with the other aspects that enrich their experience. We’re aiming to find patterns in the successful characteristics of what our most successful employees share in order to effectively target our recruiting and development efforts.

We’ll be sharing some initiatives that strive to view and understand the impacts of different business aspects on the employee experience from a 360 approach leveraging the power of taxonomy, governance, and PoolParty’s semantic management capabilities.