Agenda
Text Analytics Forum is a featured event at KMWorld 2025. See the combined program!
- Monday Nov 17
- Tuesday Nov 18
- Wednesday Nov 19
- Thursday Nov 20
Optional Pre-Conference Workshops/Conference Day
Optional Conference Day
Development
Applications
Development
Applications
9:00 AM
Optional Pre-Conference Workshops/Conference Day
Length: 7 Hour 30 Minutes
Description: Text Analytics Forum is part of KMWorld 2025 featuring five co-located events: KMWorld 2025, Taxonomy Boot Camp, Enterprise Search & Discovery, Text Analytics Forum, and Enterprise AI World. Upgrade to a Platinum Pass for your choice of two preconference workshops or access to Taxonomy Boot Camp on Monday. Workshops are also separately priced.
5:00 PM
Optional Pre-Conference Workshops/Conference Day
Length: 1 Hour 30 Minutes
Description: Join us for the Enterprise Solutions Showcase Grand Opening reception. Explore the latest products and services from the top companies in the marketplace while enjoying drinks and light bites. Open to all conference attendees, speakers, and sponsors.
8:30 AM
Optional Conference Day
Length: 8 Hour 30 Minutes
Description: Text Analytics Forum is part of KMWorld 2025. Upgrade to a Platinum or Gold Pass for extended access to KMWorld 2025, Enterprise Search & Discovery, Taxonomy Boot Camp, and Enterprise AI World, a series of co-located events happening alongside Text Analytics Forum 2025. See the registration page for details.
5:00 PM
Optional Conference Day
Length: 1 Hour
Description: Stop by the Enterprise Solutions Showcase after a full day of stimulating sessions to mix and mingle with other conference attendees, speakers, and our conference sponsors.
8:00 AM
8:30 AM
Keynotes
Length: 45 Minutes
Speaker(s):
Seema Swamy, Senior Director, Research Insights, Data Analytics, & Data Science, Walmart
Seema Swamy, Senior Director, Research Insights, Data Analytics, & Data Science, Walmart
Description: Swamy sees a very good role for AI in optimization because there are so many tasks that humans cannot do as effectively. In tasks that are less about optimization and efficiency, Swamy is concerned about biases and transparency. AI is data and efficiency; humans are creative and innovative. Several research studies, including some by our speaker, have established that people respond to smart human–computer interfaces just as they would to another human being during an interpersonal interaction. AI agents should more easily pass the Turing test and be more vivid so human responses have greater valence, that is, their experiences will be significantly more positive or negative, depending on the context. The impact can be favorable or unfavorable from an experiential psychological perspective. Organizations need to ensure that the human experience with AI is favorable. Get insights and tips for ensuring this happens in your enterprise and with your clients. Understand the impact of AI on human experiences, especially as its implementation permeates all aspects of life, from retail shopping to psychotherapy. Swamy provides actionable insights to inform business and product strategy, drive innovation, and develop and implement data strategy, governance, and visualization, sharing real-world examples you can utilize in your organization.
9:15 AM
Keynotes
Length: 15 Minutes
Speaker(s):
Tony Grout, CPO, M-Files
Tony Grout, CPO, M-Files
Description: Technology applications are developing at a rapid-fire pace in today’s accelerated world. As organizations look toward the future of work, AI has emerged as a powerful tool to make jobs easier and enable better data-driven decisions. For knowledge workers especially, the goal has always been to reduce time spent on the essential but unstimulating tasks that distract from using key skills to generate value. For these workers, the future of work is knowledge work automation, to enhance collaboration with colleagues and automate workflows. Grout discusses new innovations like knowledge work automation to build a resilient workforce capable of responding to the most daunting of industry challenges, some time savings tips that occur as a result of adopting AI-supported digital transformation efforts like reduced errors, faster inquiry response time, and increased knowledge work output.
9:30 AM
Keynotes
Length: 15 Minutes
Speaker(s):
John Chmaj, Senior Director, Verint
John Chmaj, Senior Director, Verint
Description: In a world where speed is the key to great customer experience (CX), every interaction—whether human or automated—requires fast, flawless access to the right knowledge. As AI becomes prevalent across organizations, it is becoming critical to have the capability to deliver AI-driven knowledge across more solutions and their workflows to enable faster, more effective and efficient interactions. Our experienced and fun speaker looks at how AI can be deployed to push the boundaries of how and where knowledge can be surfaced and optimized for agents, copilots, and intelligent virtual assistants. Get a blueprint for deploying and harnessing the power of AI-driven KM to power measurable outcomes across a wide range of potential users, workflows, and scenarios.
9:45 AM
Keynotes
Length: 15 Minutes
Speaker(s):
Jeff Evernham, Chief Product Officer, Sinequa
Jeff Evernham, Chief Product Officer, Sinequa
Description: As enterprises race to implement agentic AI, many are unsure where to start; others see value quickly, but realize the path from prototype to real-world value is anything but simple and struggle to expand to more complex (and higher-value) applications. Speakers explore a real-world deployment of intelligent AI agents, highlighting what it takes to go beyond chatbots and pilot projects to deliver real business outcomes. Hear how one global organization successfully deployed AI agents to accelerate R&D, streamline compliance, and improve outcomes throughout the organization—first, by grounding the agents on their internal knowledge (with robust enterprise search); second, by applying proper governance using an industrial-strength agentic AI platform. Get key lessons learned, including how to ground agents in trusted enterprise content, what it takes to ensure secure and accurate responses, and how to avoid common pitfalls like siloed content and hallucinations.
10:00 AM
Coffee & Networking Break in the Enterprise Solutions Showcase
Length: 45 Minutes
10:45 AM
Keynotes
Length: 45 Minutes
Speaker(s):
Tom Reamy, Chief Knowledge Architect & Founder, KAPS Group, LLC
Tom Reamy, Chief Knowledge Architect & Founder, KAPS Group, LLC
Description: What are the current and future trends for the field of text analytics? Join program chair Tom Reamy for an overview of the conference themes and highlights and a look at what is driving the field forward. The theme this year is Good Foundations Make Good Applications. As the hype around GenAI subsides somewhat, people are asking about how to build solutions that deliver real business value. Join us as we explore how text analytics is an essential tool for adding accuracy and depth to GenAI and opening up new possibilities.
11:45 AM
Development
Length: 45 Minutes
Speaker(s):
Kristian Bainey, CEO / Chief AI Officer, K Pic Systems Inc.
Kristian Bainey, CEO / Chief AI Officer, K Pic Systems Inc.
Description: This session focuses on how organizations can combine text analytics with GenAI—specifically ChatGPT—to extract meaningful, structured insights from unstructured project and operational data. Attendees learn how to build solid AI foundations that support smarter RAG systems, automated reporting, knowledge graph construction, and fact extraction. It showcases how prompt engineering and text analytics work together to transform everything from stakeholder feedback and meeting notes to SOWs and change requests into reusable knowledge assets. Using real-world enterprise examples, the session demonstrates how to reduce noise, ensure consistency, and enable scalable AI use cases built on trustworthy data foundations. Whether you’re enhancing internal knowledge systems or creating AI-powered tools for search, risk management, or decision support, this session provides hands-on frameworks, tested prompt patterns, and integration strategies for making text analytics and GenAI work in harmony.
Applications
Length: 45 Minutes
Speaker(s):
Alice Chung, Sr. Manager - Integrated engagement & process enablement lead, Genentech
Michalis Michael, CEO, listening247
Alice Chung, Sr. Manager - Integrated engagement & process enablement lead, Genentech
Michalis Michael, CEO, listening247
Title: The Synergistic Power of Text Analytics and GenAI for Actionable Customer Insights
Time: 11:45 AM - 12:05 PM
Description: The proliferation of unstructured text data presents both immense opportunity and significant challenges for organizations aiming to extract real value. While GenAI offers revolutionary capabilities for content generation and understanding, its true potential in enterprise applications is unlocked when grounded in a solid foundation of traditional text analytics. This presentation delves into how the strategic integration of classical text analytics techniques—such as entity extraction, sentiment analysis, and topic modeling—with cutting-edge GenAI models creates a robust framework for building applications that deliver tangible business impact. Focusing on the critical domain of customer insights, the session demonstrates how foundational text analytics provides the necessary structure and accuracy for identifying key themes, pain points, and emerging trends within vast datasets of customer feedback, reviews, and social media conversations. GenAI then amplifies these insights, enabling advanced capabilities such as automated summarization, personalized response generation, and predictive analytics that wouldn't be possible with either technology alone. Attendees learn practical approach to synergize solutions, ensuring their text-driven applications are not only innovative but also reliable, scalable, and truly valuable.
Title: Social Media Mining for Customer Insight and Competitive Intelligence
Time: 12:10 PM - 12:30 PM
Description: SVMs if properly trained (in context) are still better than the known LLMs and GenAI when it comes to labeling text in any language. The common use cases in the social media listening space are for tagging sentiment, topics, and relevance. An F1 score gap analysis between GPT4 and a "humble SVM model" will make the case along with examples of customer reports and how they are useful to brands. The combination of predictive plus GenAI can provide the best of two worlds under the right circumstances. This talk shows how text analytics can add intelligence to a finite dataset which will then be used with an SLM to produce impressive brand Ads.
12:30 PM
Attendee Lunch in the Enterprise Solutions Showcase
Length: 1 Hour
1:30 PM
Development
Length: 45 Minutes
Speaker(s):
Jans Aasman, CEO, Franz Inc
Jans Aasman, CEO, Franz Inc
Description: In nearly all of our recent knowledge-graph projects, unstructured content now outweighs structured data. We repeatedly carry out three distinct tasks: fine-grained annotation that extracts rich, token-level information from narrative sources such as clinical notes, legal filings, and aircraft maintenance logs; string-to-concept alignment that maps phrases in those texts to canonical entities in well-curated taxonomies (medical, legal, engineering, etc.); and rule extraction that derives executable logic from complex documents so that one document can be programmatically evaluated against another (e.g., eligibility criteria, insurance-coverage clauses, or statutory rules). Each task relies on LLMs. We have developed a dedicated tool for each, using ensemble-based processing to enhance accuracy and robustness: a resolver framework that runs multiple LLMs in parallel and reconciles their outputs, consistently driving annotation accuracy to 99%; a vector-store–backed matcher that links free-text strings to ontology concepts with high precision and recall; and a rule-mining engine that translates dense prose into SPARQL or Datalog rules for downstream reasoning. This talk demonstrates all three tools and show how, together, they close the accuracy gap in end-to-end text analytics pipelines.
Applications
Length: 45 Minutes
Speaker(s):
Charity Queret, Chief GenAI Consultant, GenIQ Advisors
Charity Queret, Chief GenAI Consultant, GenIQ Advisors
Description: GenAI and text analytics offer incredible potential, but success isn’t just about technology. It’s about people. While most organizations focus on model performance, the real key to sustainable impact lies in preparing teams to work confidently with AI. This session presents a clear, research-backed roadmap for helping text analytics professionals evolve from rule-based workflows to human–AI hybrid practices. Attendees learn how to lead their teams through every stage of the GenAI adoption journey: assess readiness, redesign roles, lead change with ADKAR, upskill strategically, shift the mindset, and sustain and scale. Attendees walk away with a practical toolkit, assessment checklists, role templates, training outlines, and change-management guides to turn their text analytics groups into GenAI-ready teams.
2:30 PM
Development
Length: 45 Minutes
Title: Hammers and Nails: LLMs vs. Supervised Learning Methods for Enterprise Tagging Problems
Time: 2:30 PM - 2:50 PM
Description: LLMs are powerful, versatile and new. They present exciting opportunities for automating and simplifying workflows. However, for use cases such as tagging of enterprise content, where consistency and traceability are essential, LLMs introduce their own challenges, including hallucinations and irreproducibility of results. This session compares results of tagging using LLMs to a benchmark of tagging using supervised learning methods. It also explores techniques such as prompt tuning and RAG to improve LLM results within the context of applying large, complex taxonomies to heterogenous content. We look at the benefits and limitations of the different approaches. Additionally, just because LLMs are a new hammer, we ask if every use case needs to be a nail.
Title: Classification and IE for AI Agents
Time: 2:55 PM - 3:15 PM
Description: The most common use case for text analytics and taxonomies and ontologies is to improve precision and recall in information retrieval. This is typically achieved by curating knowledge organization systems that contain single-source-of-truth enterprise controlled vocabularies. These vocabularies provide consistent metadata values for classifying and searching content across disparate content management systems. The structure of taxonomies and ontologies are also often used in information architecture to support knowledge discovery via navigation menus, faceted search, and content recommendations. By combining LLM-based classification and information extraction processes with taxonomies, ontologies, and AI, novel use cases emerge. Taxonomies and ontologies can enumerate decision points and criteria, and be linked together to define process triggers, dependencies, and consequences. AI agents then reference the taxonomies and ontologies to provide definitive instructions on how to run business processes. Agentic ontologies are therefore graphs structured with process-oriented semantic concepts, relationships, and properties. They provide the framework for how AI agents perceive, reason, make decisions, and act. Agentic ontologies provide AI agents with the enterprise domain knowledge to manage complex interactions with humans and other systems. The transparency of the ontology graph empowers human agency over the outcomes of AI agents.
Applications
Length: 45 Minutes
Speaker(s):
Alison Bushell, Head of Global Analytics, Forsta
Alison Bushell, Head of Global Analytics, Forsta
Description: GenAI is transforming how we understand and act on human experience data. This dynamic session explores how GenAI can supercharge every phase of the text analytics lifecycle—from initial research to actionable insights. Learn how to harness GenAI for rapid background research that informs smarter design and architecture decisions. Discover how to co-create Boolean categorization rules using GenAI as a brainstorming partner, accelerating development while enhancing recall and precision. Finally, we dive into building a robust, human experience and sentiment model for any industry or vertical. Along the way, we share practical prompts, checks and balances, and real-world examples to ensure your GenAI-powered text analytics workflows are both innovative and robust. Whether you're new to GenAI or looking to deepen your practice, this talk equips you with the knowledge to elevate your text analytics strategy.
3:15 PM
Coffee & Networking Break in Enterprise Solutions Showcase
Length: 45 Minutes
4:00 PM
General Session
Length: 1 Hour
Speaker(s):
Urmi Majumder, Principal Data Architecture Consultant, Enterprise Knowledge, LLC
Kyle Garcia, Senior Technical Analyst, Enterprise Knowledge, LLC
Joe Hilger, COO, Enterprise Knowledge, LLC
Kyle Garcia, Senior Technical Analyst, Enterprise Knowledge, LLC
Urmi Majumder, Principal Data Architecture Consultant, Enterprise Knowledge, LLC
Kyle Garcia, Senior Technical Analyst, Enterprise Knowledge, LLC
Joe Hilger, COO, Enterprise Knowledge, LLC
Kyle Garcia, Senior Technical Analyst, Enterprise Knowledge, LLC
Title: The Cost of Missing Critical Connections in Data: Suspicious Behavior Detection Using Link Analysis (A Case Study)
Time: 4:00 PM - 4:30 PM
Description: Graph-powered link analysis, combined with NLP, offers a powerful approach to identifying complex patterns and trends within extensive and complex datasets, especially unstructured data like emails, documents, and social media. By modeling data as interconnected entities and relationships, link analysis reveals hidden connections and supports various applications such as fraud detection, risk mitigation, and network analysis. In financial services, identifying related entity attributes such as shared bank account information across insurance claims can quickly expose potential fraud. Urmi Majumder and Kyle Garcia of Enterprise Knowledge, LLC (EK) discuss this domain of link analysis and its underlying graph technology using a case study in which EK helped a national agency implement a link analysis solution for suspicious behavior detection. Discover how graph data modeling enables pattern recognition and learn crucial aspects of graph model development, including entity-relationship modeling decisions and selecting appropriate models for various link analysis methods. Gain practical knowledge of building a modular, cost-effective, and enterprise-integrable, end-to-end link analysis solution. Learn to identify opportunities for graph-based solutions in real business challenges and implement effective solutions using best practices for scalable linked data analysis.
Title: Generating Structured Outputs From Unstructured Content Using LLMs
Time: 4:00 PM - 5:00 PM
Description: Long, unstructured documents can be difficult to manage and pull information from. Without a formally defined structure, information about what is in these often-important documents is difficult to obtain without reading their entire length. Search tools show the document, but not always the relevant source of information. AI tools pull some information out, but longer documents can also be a source of hallucinations. Consequently, a clear structure is essential for transforming disorganized content into more usable, valuable assets by dividing documents into distinct components. A well-formed content structure allows for componentization of content, enables the ability to add content to a knowledge graph, and facilitates efficient reuse, personalization, and discoverability across platforms and contexts. So, what’s the best way to break apart unstructured content and give it structure? One method is using a combination of LLMs and content models, allowing the LLM to reference a blueprint of components and what they should include. By undertaking this process, organizations can create a set of easily referenceable components that can be presented across contexts. As a result, this breaking apart of content helps make it more consistent, reusable, and easier to manage across platforms. In this talk, Joe Hilger and Kyle Garcia of Enterprise Knowledge, LLC share key considerations for building a structured content extractor using LLMs and a content model, highlight real-world use cases and examples of past work, and demonstrate how structured content can power a knowledge graph.
8:00 AM
8:30 AM
Keynotes
Length: 45 Minutes
Description: Innovation is the process of taking ideas from inception to impact. Organization leaders face continuous pressure to innovate, but no corporation, government agency, or non-profit has the resources, time or talent it needs to keep up with rapid advances in innovation, technology and global changes. Leaders know they need to look beyond their own enterprises to the external landscape and ecosystem to support internal innovation. Our speaker shares insights and practical examples from around the world as well as frameworks and models to work effectively in the innovation ecosystem. He provides tips on how to build structures and processes to support employee engagement as they learn and connect with other stakeholders.
9:15 AM
Keynotes
Length: 15 Minutes
Speaker(s):
Andreas Blumauer, SVP Growth, Graphwise
Andreas Blumauer, SVP Growth, Graphwise
Description: Building a powerful knowledge graph is no longer a choice between slow manual effort and untrusted automation. Our speaker shares real-world examples of how organizations are using an AI Flywheel to build and enhance trusted AI solutions that deliver measurable business value.
9:30 AM
Keynotes
Length: 15 Minutes
Speaker(s):
Brian Corcoran, KCS Certified Expert and Global Support Evangelist, SearchUnify
Brian Corcoran, KCS Certified Expert and Global Support Evangelist, SearchUnify
Description: Discover how Agentic AI is transforming enterprise search into a dynamic, autonomous knowledge ecosystem. This session explores how intelligent agents think, reason, and act to deliver real-time insights, streamline knowledge flow, and power smarter support experiences—redefining the role of search in today’s AI-driven, hyperconnected business landscape.
9:45 AM
Keynotes
Length: 15 Minutes
Speaker(s):
Philip Brittan, CEO, Bloomfire
Philip Brittan, CEO, Bloomfire
Description: Enterprise Intelligence is the next evolution of knowledge management—designed to connect, optimize, and activate knowledge where it matters most. In this keynote, Bloomfire CEO Philip Brittan shares how forward-thinking organizations are transforming static information into a dynamic, intelligent asset that fuels strategic decision making.
10:00 AM
10:15 AM
Development
Length: 45 Minutes
Speaker(s):
Bonnie Bowes, Semantic Graph Solutions Specialist, Squirro AG, UK
Bonnie Bowes, Semantic Graph Solutions Specialist, Squirro AG, UK
Description: In today’s data-rich environment, enterprises face a new kind of problem, not data scarcity, but data overload. While AI, particularly LLMs, promises to tame this flood, it struggles when lacking structure and context. Without semantic grounding, LLMs generate inaccurate, inconsistent, and often misleading outputs. This talk explores how taxonomies and ontologies close the accuracy gap in GenAI by providing the essential foundation for context-aware, explainable, and trustworthy results. Taxonomies classify information hierarchically, while ontologies define the relationships, attributes, and logic between concepts. Together, they bring order to unstructured data, emails, documents, chats, and sensor logs, allowing GenAI systems to disambiguate terms, infer meaning, and tag content accurately. We explore how this structured approach powers deterministic outputs, enhances compliance, and enables traceability, especially in regulated industries like finance and healthcare. Using real-world examples and case studies, this session demonstrates how systems like Synaptica Graphite (a no-code TOM platform) and the Squirro AI Classifier combine semantic structure with probabilistic AI to deliver relevant, explainable insights. From improving precision in customer feedback analysis to supporting auditable classification in pharmaceutical workflows, TOM-based systems create AI that doesn’t just guess, it understands. The presentation makes the case that taxonomies and ontologies are not back-office tools, but strategic assets. They are the bridge between data chaos and intelligent automation, unlocking GenAI’s full potential with structure, logic, and control.
Applications
Length: 45 Minutes
Speaker(s):
Mark Gross, President, Data Conversion Laboratory
Mark Gross, President, Data Conversion Laboratory
Description: The Association for Materials Protection and Performance (AMPP) is the global authority in materials protection and performance and is at the forefront of standards and training to enhance infrastructure protection and maintenance. To best serve its members, AMPP recognized the need to modernize its workflows and digital tooling by transforming a vast archive of unstructured technical papers, standards, books, and articles into a dynamic, AI-ready knowledge base. In this case study, we discuss how AMPP harnessed text-analytics such as NLP, entity extraction, topic modeling, and semantic enrichment to transform unstructured documents into richly tagged, interoperable data. By building a knowledgebase with granular, interoperable content, AMPP can seamlessly integrate new materials and adapt to emerging AI platforms. This scalable architecture not only underpins today’s member services but also accelerates future AI-driven offerings, driving continuous enhancements in user experience and enabling data-driven decision making across the organization.
11:15 AM
Development
Length: 45 Minutes
Speaker(s):
Prathik Roy, Product Director, Springer Nature
Prathik Roy, Product Director, Springer Nature
Description: Join us on a journey into the realm of scientific exploration as we delve into the power of text and data mining. This talk focuses on how structured, enriched, and curated scientific literature in the areas of healthcare, semiconductors, pharma, chemicals, and life sciences are poised to accelerate technology implementation such as RAG-LLMs to the new generation of Model Context Protocol and NLWeb in the areas of agentic AI. Our goal is to uncover patterns and insights that can revolutionize the way we develop intellectual property in research and development. This discussion aims to showcase the untapped potential of data mining in fostering innovation. Discover how this approach can streamline the discovery process, foster interdisciplinary collaboration, and pave the way for groundbreaking advancements in critical industries that drive progress and shape our future.
Applications
Length: 45 Minutes
Speaker(s):
Sergei Ananyan, CEO, Megaputer Intelligence
Sergei Ananyan, CEO, Megaputer Intelligence
Description: Solving data curation tasks requires navigating vast and complex collections of documents, frequently involving charts and tables, to extract critical facts with accuracy and speed. Combining the collaborative multi-model approach where GenAI engines—vision-language models and LLMs—identify and extract relevant insights from diverse data sources with NLP tools that expose underlying textual patterns and enable human validation, organizations can streamline and enhance the curation process. This approach addresses key challenges such as information overload, domain-specific language complexity, and the need for precise fact-checking while reducing manual effort and error rates. Automating data curation helps accelerate research, improve compliance, and drive informed decision making, making it a vital innovation in data-intensive industries.
12:00 PM
Keynote Lunch & Awards
Length: 1 Hour
Speaker(s):
Parind Oza, Managing Director, Evalueserve
Parind Oza, Managing Director, Evalueserve
Title: Keynote: Activating Enterprise Intelligence in the Age of AI
Time: 12:15 PM - 12:30 PM
Description: As enterprise AI adoption surges, a startling paradox has emerged: While 70% of organizations are investing in AI and automation, only 18% say their KM strategy is ready to support it (Gartner 2024). An overreliance on technology without the processes or expertise to activate what enterprises already know is a challenge. Oza challenges the dominant "tool-first" narrative and reveals how forward-looking firms are building tailored, domain-driven KM ecosystems to fuel enterprise intelligence. Drawing on real-world transformations from top consulting and professional services firms, he shares how organizations are capturing what's in people’s heads before that information walks out the door, enabling decentralized, frontline decision making with embedded intelligence and scaling tacit knowledge into AI-ready assets through human-in-the-loop annotation and stewardship. Learn why LLMs and chatbots underperform without robust, contextual knowledge layers; how leading firms reduced content redundancy and enabled 20%–40% time savings across workflows; how annotation, sanitization, and human-in-the-loop curation drive model performance and user trust; discover strategies to capture primary knowledge in expert’s heads before it disappears and why internal influencers, not tech, make or break KM adoption and long-term ROI. See KM not as a backend content repository, but as the strategic core of how intelligence is produced, shared, and acted upon in modern enterprises.
Title: KMWorld Awards
Time: 12:30 PM - 12:45 PM
Description: KMWorld magazine is proud to sponsor the 2025 KMWorld awards, KM Promise & KM Reality, which are designed to celebrate the success stories of knowledge management. The awards will be presented along with Step Two’s Digital Awards, where you get a sneak peek behind the firewall of these organizations. Find out more—kmworld.com/Conference/2025/Awards.aspx.
1:00 PM
General Sessions
Length: 45 Minutes
Speaker(s):
Tom Reamy, Chief Knowledge Architect & Founder, KAPS Group, LLC
Tom Reamy, Chief Knowledge Architect & Founder, KAPS Group, LLC
Description: Knowledge graphs, text analytics, and GenAI are all foundation technologies supporting a wide variety of applications. While each is powerful in its own right, combined, they enrich each other and can support an almost limitless range of application. This talk explores the latest text analytics techniques of data and relationship extraction and auto-classification and how those techniques can feed the development of knowledge graphs and ontologies, and faceted search applications. It includes using auto-classification to disambiguate entities. It also examines how knowledge graphs and ontologies can provide input into taxonomy and text analytics development and enrich applications like business and customer intelligence. The talk concludes with a discussion of how the combination of text analytics and knowledge graphs can improve GenAI with semantic RAG or GraphRAG. Finally, we take a quick look at how GenAI can be used as a productivity tool to speed up both text analytics and knowledge graph development and applications.
2:00 PM
General Sessions
Length: 45 Minutes
Speaker(s):
Lauren Clark Hill, Expert Knowledge Management Solutions Engineer, Squirro
Lauren Clark Hill, Expert Knowledge Management Solutions Engineer, Squirro
Description: Enterprise taxonomies are vital for metadata management, content discovery, and supporting AI initiatives. However, maintaining taxonomies—ensuring accuracy, adaptability, and alignment with emerging trends—can be complex and resource-intensive. This session explores how advanced machine learning techniques can be integrated into taxonomy workflows to automate and refine taxonomy creation, expansion, and governance. Through the use of sophisticated text classifiers, taxonomies can be audited, gaps identified, and relevant terms suggested to ensure comprehensive coverage. Attendees will learn how these techniques can analyze content for latent structures, generating metadata and enabling a more efficient and scalable taxonomy management process. The session will cover the following: identifying new terms, expanding vocabularies, and addressing multilingual or domain-specific needs using AI-driven classifiers; automating the categorization of content while ensuring alignment with established taxonomy standards; implementing a hybrid approach that combines AI suggestions with human oversight, improving consistency and reducing bias; and creating a feedback loop that allows classifiers to adapt and improve based on user input and evolving content. This semi-automated approach provides attendees with strategies for enhancing taxonomy workflows while maintaining governance, transparency, and control over AI-generated suggestions. The session is ideal for taxonomists, knowledge managers, and content strategists looking to integrate AI-driven solutions into their enterprise taxonomy processes.
3:00 PM
General Sessions
Length: 45 Minutes
Speaker(s):
Michele Lamorte, Senior Manager, Information Analysis, IEEE
Michele Lamorte, Senior Manager, Information Analysis, IEEE
Title: Ditto: When ‘Auto-Tagging’ Becomes Whirling, Transient Nodes of Thought Careening Through a Cosmic Vapor of Invention
Time: 3:00 PM - 3:20 PM
Description: Content management is boosted when your software can analyze your content and apply relevant tags, classifications, and other metadata. Even better (from a taxonomist’s opinion) is when your content management system integrates with a semantic layer, where you manage your taxonomies, thesauri, and/or ontologies so you control what content is tagged and with what terms. But what about the other vendors who can also tag your content in other stages of the content management workflow? Do you add their capabilities as well? How many different tag sources should you have? When in the workflow should content be tagged? How many are too many distinct groups of tags? This presentation goes over examples of different keyword tagging methods as well as different options for managing multiple sources of keyword tags.
4:00 PM
Closing Keynotes
Length: 15 Minutes
Speaker(s):
Seth Earley, CEO & Founder, Earley Information Science
Seth Earley, CEO & Founder, Earley Information Science
Description: With all of the valuable insights from the conference, it can be challenging to identify where to begin and how to focus resources and attention. How do you bring key messages back to colleagues, teams, and leadership? A longtime KMer, Earley highlights ways to process and apply what you have learned and identify the best way to bring concepts to reality. He considers all the conference themes—search, discovery, taxonomy, information architecture, knowledge sharing, text processing—and how AI cuts across each of these. Get a simple framework for building a road map by discovering user needs, connecting findings to overarching themes, and then identifying the needed capabilities to address user needs, regardless of the tools, technologies, or approaches.
4:15 PM
Closing Keynotes
Length: 45 Minutes
Speaker(s):
Brian Pichman, Director, Strategic Innovation, Evolve Project
Dave Snowden, Founder & Chief Scientist, The Cynefin Company
Ross Smith, WW Support Leader, Microsoft
Sandra Montanino, Founder & Principal, Navig8 PD
Kim Glover, Director, TechnipFMC
Brian Pichman, Director, Strategic Innovation, Evolve Project
Dave Snowden, Founder & Chief Scientist, The Cynefin Company
Ross Smith, WW Support Leader, Microsoft
Sandra Montanino, Founder & Principal, Navig8 PD
Kim Glover, Director, TechnipFMC
Description: Where is KM going with all the AI developments for the enterprise? How are our organizations responding to the social structures and changes in our world? How are they innovating and exceeding customer expectations? Get inspiration from our practitioners and futurists and be ready for KM in 2026.
