Are you new to knowledge management? Want to learn about all the possibilities for making your organization smarter, more collaborative, innovative, and productive? Join our expert knowledge manager to gain insights and ideas for building a robust KM program in your organization—even if it is called by another name! This workshop highlights a range of potential enterprise KM activities being used in real organizations and shares how these activities are impacting the bottom line. It shows real KM practices and discusses various tools and techniques to give those new to KM a vision of what is possible in the enterprise.

Text analytics is becoming essential in any field that tries to utilize unstructured text, and yet confusion remains distinguishing it from text mining, the type of applications that can be built with text analytics, and best practices. This workshop, based on the speaker’s recent book, covers the entire field of text analytics including these points:

The workshop utilizes exercises in auto-categorization, data extraction, machine learning, and sentiment analysis to deepen the participants’ appreciation for the practical process of building text analytics applications and, at the same time, exemplifies some of the key theoretical issues.

The volume of human knowledge is growing. But machine knowledge is growing even faster. And the accelerated pace of both is taxing the limits of traditional KM. Machine learning platforms are valuable tools for discovering hidden patterns and trends. But they often provide little or no insight into how new knowledge is generated, or when a model or algorithm is no longer valid. All of this greatly increases risk. Consider how many of your business decisions are automated, how many business rules your organization has, and if they are current and still valid. You may need to start incorporating knowledge governance into your organization Join our popular speaker and get a road map for implementing a top-level governance model, including how to measure results and make adjustments along the way. Get the seven major facets of knowledge governance, how to align them with overall corporate governance, and most importantly, how to evaluate the range of possible social impacts, both positive and negative. Get a sneak preview of what’s coming, including the emerging technologies you’ll need to be closely watching, and how those technologies will place even greater demand on having a sound knowledge governance model in-place.

You’ve perhaps heard it before: We implemented enterprise social networking but now how do we get people to really use it? Or: We’ve got such a talented workforce—why aren’t people sharing their knowledge more? Our longtime KM advocates answer these questions. They bring collaboration and knowledge tools and processes together in ways that empowers people’s digital fluencies and practice so they can collaborate and work more effectively in rapidly changing contexts and diverse global teams. They know that employees are more willing to collaborate when they have built relationships with the others and they have creative ways to make those relationships happen! Get lots of techniques, insights, and ideas from this workshop to immediately put into practice in your organization.

Expert knowledge is difficult to capture and transfer effectively, because it involves deeply embedded skills that an expert may not be consciously aware of using and may not understand how to share. The challenge this poses is how to capture and transfer that knowledge among co-workers and external partners who need to work together on critical, high-stakes projects. Without effective knowledge transfer strategies, these valuable lessons learned and best practices are often lost. This knowledge is essential to the success of the mission, especially in emergency situations such as responses to natural disaster events that are time-critical. This master class-style workshop is based on case studies of more than 200 top-level executives, engineers, and scientists at Fortune 500 companies, the military, and multiple government agencies. It discusses knowledge transfer and flow strategies and focuses on the challenges you bring from your organization. The workshop combines the power of an SME along with skilled colleagues from other organizations to offer effective processes for enhancing knowledge flow at all levels of organizations, both internally and externally. By working through your challenges, this workshop covers the impact of internal versus external parties on knowledge transfer, as well as maintaining knowledge flow when organizations are geographically dispersed. Best practices and tools are shared for capturing key knowledge, analyzing and documenting that knowledge, and multiple methods to transfer that key knowledge.

Humans connect through stories, find meaning in stories and remember stories far better than data. Steve Jobs once said: “The most powerful person in the world is the story teller. The storyteller sets the vision, values, and agenda of an entire generation that is to come.” And Steve Denning, in his book The Leader’s Guide to Storytelling, provides a guide to different types of organizational storytelling, tying the ancient practice of sharing through stories to today’s business world. Although most KM professionals know about the power of stories in organizations, many KM programs don’t include teaching the art of telling a story or conduct storytelling workshops. This workshop highlights the ways that TechnipFMC is using storytelling in its KM program and walks participants through several fun storytelling activities. Get a heightened awareness of the power of stories and the ability to run storytelling activities in your organization! Enjoy “story-listening,” as other KM practitioners tell their own tales. Come tell us your story!

This workshop covers the entire enterprise search solution lifecycle including the most important concepts of enterprise search and priorities for successful solution implementations. How is data getting indexed in search in a secure away, honoring access control lists? On the UI side, the workshop looks at the fabric of modern search interfaces going far beyond the list of search results and a few filters; it considers deep integrations into intranet portals and business applications. Vogt also covers the search experience management, relevancy optimization, and how this continuous effort ensures success of your users and hence search solution adoption. He outlines how AI can, in practice, be leveraged to augment the search experience. Throughout the workshop, Vogt presents real-world scenarios and explains the underlying implementation and reasoning behind, uses live demos to illustrate the capabilities of both open source-based and commercial search engines, e.g., Google Cloud Search or Microsoft SharePoint and SharePoint Online. This interactive workshop focuses on the aspects which are most valuable for the specific audience and aims at diving deep discussions on how their use cases could be implemented.

This exciting and interactive workshop discusses what you need to know to get ready for the future that is already here. It discusses the different kinds of AI and their use cases, looks at some cool tools, and talks about how you would choose a vendor and or tool to work in your organization and KM program.

This engaging workshop by one of the leading practitioners of complexity theory and solutions discusses practical techniques to create conditions to enable novel emergent solutions to wicked and intractable problems. It introduces a complex approach to design thinking, a non-linear approach, a next generation approach design thinking. Get new ways to support innovation in your organization and generate ideas with a focus on solutions to unarticulated problems. Snowden shares the latest version of Cynefin, a sense-making framework used globally to create a contextual approach to decision support. Better decision in shorter time frames making full use of our resources and networks.

Search is being shipped more frequently with more advanced tools that enable “start search.” Our experienced practitioner looks at the vendor market and capabilities. He also examines what the advanced technologies such as machine learning (ML) and AI can offer and how to go about integrating them with your current search platform—or how to know whether your search technology has the smarts to work in conjunction with the more advanced ML/AI platforms. Building platforms for continuing evolving markets and organizations is a challenge, but our popular speaker sheds some light for future planning and implementation.

With Outlook, OneDrive, Word, Excel, PowerPoint, OneNote, SharePoint, Microsoft Teams, Yammer, and more in the Microsoft Office suite, you have a tremendous technology ecosystem to help automate many aspects of your knowledge management strategy. Learn how to take advantage of the many features and benefits in Office 365, including design options, workflows, designing taxonomies users actually want to use and the latest tips and tricks, to propel your knowledge management program forward to ensure your success! Get lots of tips and good practices from our experienced experts!

This workshop, by a KM pioneer and popular KMWorld speaker, focuses on how to build a successful KM strategy and revitalize knowledge sharing within your organization. Dave Snowden, our engaging workshop leader, takes participants through a step-by-step approach to rethink the role of the KM function within an organization. It includes creating a decision/information flow map to understand the natural flows of knowledge; defining micro-projects that directly link to the decision support needs of senior executives; mapping the current flow paths for knowledge within the organization; and finding natural ways to manage the knowledge of the aging workforce as well as the IT-enabled apprenticeship. Using real-world examples, Snowden shares winning strategies and insights to rejuvenate your knowledge-sharing practices. Always fresh and filled with interesting stories, this workshop continues to stand out with our audience!

Knowledge doesn’t manage itself. No matter how far AI evolves, knowledge, whether human or digital, will always need human curation. Knowledge curation is one of the least-understood aspects of KM. Yet given the accelerated growth of both explicit and hidden knowledge, especially in large datasets, knowledge curation is more critical than ever. There is no shortage of tools and techniques for building knowledgebases and repositories, yet this question remains: “How do I design, build, and maintain a body of knowledge that’s easily accessible to me and others?” This workshop helps you to gain an understanding of the three main pillars of knowledge curation: 1) knowledge capture and transfer; 2) governance, including roles and responsibilities, assurance, performance monitoring, and incentives; and 3) architecture, including the tools, platforms, and processes for putting it all together. Some key elements include how to determine what knowledge is worth capturing and in what form; reconcile different world views, mental models, and learning modalities, especially among mentors and mentees; determine which tools and approaches are appropriate for different types of knowledge; integrate the various tools and approaches into a single system; vet knowledge and keep it up-to-date; and make knowledge flow and grow, from a single individual to an entire community of experts and practitioners. Join our experienced KM expert and take home an initial plan for setting up and implementing a world-class knowledge curation program for your organization.

Microsoft Office 365 offers a rich portfolio for building intranet and department sites, employee and team communication, and social collaboration. A centerpiece of Office 365 is the Microsoft Graph and SharePoint Online search. Both allow for not only finding documents but also for easily building rich business applications—applications that actually facilitate collaboration by bringing the most relevant context-dependent content to knowledge workers. This workshop develops the most important search use cases in collaborative environments, describes how they can be implemented with the search provided by Microsoft, and looks at how you can solve your business requirements within Office 365 by combining search with, e.g., Microsoft Flow. Options are presented to integrate search into a cloud-intranet portal or service support desk bot, allowing the most out of your investment. This workshop is use-case-driven and looks at the larger context of the Office 365 collaboration landscape and, of course, its technical architecture.

In the minds of many people, KM is about the past—best practices, lessons learned, organizational memory, etc.—while innovation is about the future—brainstorming new ideas, new product development, prototyping, etc. But one doesn’t do KM for the sake of KM! KM is done with strategic intent, and among many options that could lead to (better/more effective) innovation, of course. Innovation doesn’t happen in a vacuum: Incremental innovation is building on (knowledge of) existing products and services, and even radical innovation needs (knowledge of) current business models and markets to define itself. Innovators may hail the mantra “Fail fast, fail often,” but failing without learning the lessons is useless! Innovation and KM hardly ever collaborate in large organizations, as they typically belong to different departments: KM is often somewhere under HR or support services, while innovation is most often under strategy or operations. This means that leaders most probably report to different VPs. Still, both innovation and KM are all about breaking the organizational silos and have functionally diverse teams collaborating. This workshop explores the relationship between innovation and KM from both our consulting and management point of views. It covers the following:

Be ready to gain lots of insights and ideas!

Congratulations! You’ve just been given the responsibility for search at your organization! Perhaps there is a new initiative to improve search, or perhaps the previous search manager mysteriously disappeared. In any case, you’ve discovered that search is a deceptively tricky domain, and that the expectations of many of your stakeholders are difficult to meet or even to define. This workshop provides an orientation and exposure to the key issues, effective processes, and technology—independent of what brand of search engine you use. It provides lay-of-the-land information and approaches to get you off to a good start. Topics include getting started and where to find practical guidance in search management; kinds of tasks and roles involved in managing search; building a cross-functional team; assessing the current state of search; establishing a vision and creating a findability strategy; getting stakeholders together and constructively involved; discovering and managing expectations; top misconceptions about search and how to educate your organization; top five and next five tools and techniques for improving search; updates and improvements; and measuring search: KPIs, tools, and techniques for internal search engine optimization. If you have been in the search manager’s role for a while but feel like you are missing a grounding in successful practices and management techniques, this workshop is still useful.

If your users can’t find what they need on your intranet, your information architecture (IA) probably needs some work! Join our experienced practitioner and learn tips and best practices to improve findability, information organization, and the basic concepts of information architecture. Rodgers covers the critical aspects of intranet IA: navigation/site architecture, page design architecture, and metadata architecture. Get approaches for planning navigation across the entire intranet and on individual sites, along with tips and best practices for using mega-menus and organizing hub sites. Grab lessons about the best place to focus your IA energy so that you can build an intranet that is an essential part of your digital workplace today and as your organization evolves over time.

The International Standards Organization (ISO) has just published a new set of Knowledge Management Standards. Are you ready? The new standards contain requirements and guidelines for all aspects of the KM program, e.g., establishing, implementing, maintaining, reviewing, and improving an effective management system for knowledge management in organizations. As is the case for all ISO standards, this set of standards can be applied to any organization seeking ISO certification, regardless of its type or size, or the products and services it provides. This workshop covers understanding the ISO standards and how to translate the standards into requirements for your organization; examining how an auditor evaluates a program against a standard; identifying ways to prepare for an ISO KM audit; and looking at examples of KM initiatives or tactics that should satisfy an ISO KM audit. This practical, hands-on, half-day workshop focuses on what participants are already doing in their organizations to meet the standard and how to present these efforts to an auditor. Get a laminated handout of the standards by category and explore in small groups how your organization can meet the standard and the ROI expected for achieving the standards. Get ahead of the crowd by learning about the ISO KM standards and how they relate to your program.

Data visualization tools are helpful for those who either a) think visually, b) want to present data to people in more innovative ways, or c) think more creatively. Mind maps have been used for decades in corporate America as well as by writers, attorneys, and educators. Mind maps and other related tools are especially helpful in laying out and organizing unstructured data. This hands-on workshop provides a short look at data visualization theory, concepts, and terminology; a discussion differentiating the tools; and working with three different data visualization tools that are absolutely free. The three different tools provide a myriad of ways to lay out unstructured data in innovative ways. Despite the fact that these tools are free, they are surprisingly powerful and flexible. Bring your device so the group can participate in solving problems using these tools.

Creating value from KM initiatives depends entirely on user adoption by changing behaviors and beliefs. Learning and knowledge initiatives benefit from change management efforts using the transformation road maps common to IT implementations. But real knowledge sharing requires cultural changes that can only be catalyzed through entrepreneurial engagement at all levels of the organization. Any change effort is delicate, and KM programs are especially vulnerable because knowledge sharing can only be voluntary. A design-thinking approach can tap into the initiative and innovation latent in every employee. This workshop combines both the coordinating and catalyzing perspectives with real-world experience and advice. Learn the basic components of any successful change program; practice assessing and addressing challenges and opportunities in your organization; and tap into the latest thinking in organizational change. Come prepared to discuss your own unique situations and learn from your peers in facilitated, interactive discussions and exercises.

Get the highlights and insights from Glimpse, the trend analysis which focuses on emergent generational and societal shifts, and learn how to respond to these changes. Understanding the global context teaches us what each person is facing with the world today and sets the emotional groundwork for every project. From this global context, Turner shares insights into how our minds have changed, how society has shifted in response, and where it is going through the eyes of generational and cultural evolution. Get ideas about what the future holds for knowledge sharing in our organizations. The eight important mega-trends that inform the world today, the disruptors are reinvention, non-linears, crowd-shared revolution, being human, data disruption, human +, a new visual-verbal culture, and human speak. Hear more and get ideas of how to prepare for this future.

Over the last couple of years, AI, machine learning, and deep learning have received unprecedented attention and are now reaching the top of the hype cycle. But today, despite many technology breakthroughs and success stories from early adopters, very few enterprise organizations are actually reaping the promised benefits. Sinequa is one of the few software platform vendors with customers deploying applications powered by AI models. Our journey in the field has taught us some valuable lessons, and there are some key takeaways we would like to share with you: a look at what pragmatic AI can do for you, bridging the gap between AI’s long-term potential and today’s capabilities, tips to identify the highest ROI use cases which can be addressed with AI models today, best practices to deploy these in production and start generating value. Get great insights and ideas from a KMWorld magazine award-winner and industry leader.

Knowledge graphs built on top of semantic technologies, supported by machine learning technologies, can become a paradigm change in how we deal with metadata management. Keeping track of what is going on in your data is the crucial momentum. Active metadata is a key element to achieve this. Traditional approaches do not work anymore—they are not adaptive, cross-application, and do not provide the semantic richness creating additional value from your data. You need a knowledge graph to specify your business rules and semantics. It is the bases for data enrichment, lineage, and impact analysis. Working in complex deployments requires metadata exchange in a unified, standardized way. Knowledge graphs provide better user experience and allow to fulfill specific workflow, security, and privacy requirements. Based on real business examples, our speakers illustrate how active metadata management works and provides more value to your data and, by that, your corporation.

Artificial intelligence, cognitive technologies, and related tools have the ability to fundamentally reshape knowledge management. As always with groundbreaking technologies and management systems, there is a mixture of some successes, lots of hype, and an emerging body of knowledge of how and where to deploy AI/cognitive for both quick wins and long-term transformational impact. Namir provides an overview of this rapidly transforming landscape and discusses how organizations can accelerate their AI investments to derive maximum value.

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. This year’s main new topic is knowledge graphs, which are being developed for everything from enterprise search to a way to build an enterprise platform to integrate all an organization’s data. We also continue the exploration of machine learning and rules-based approaches and how people are combining them to get the best of both worlds. The talk ends with a look at current and future trends that promise to dramatically enhance our ability to utilize text with new techniques and applications.

This talk describes the use of an enterprise knowledge graph as the semantic backbone of a text analytics application. Going beyond traditional hierarchical taxonomies, we demonstrate how we use a knowledge graph to enhance entity resolution, boost signal detection, and improve relevance scoring. We examine a use case where graph-informed tagging adds business value by surfacing connections between different facets of content and by driving personalization and user experience through precise metadata.

This presentation covers text analytics and text processing techniques used in creating several interesting text based knowledge graphs. One example is the Noam Chomsky Knowledge Graph which incorporates hundreds of articles and numerous books that Chomsky has authored about linguistics, mass media, politics, and war. Another example covers health effects for ingredients in foods and beauty products. We show how a combination of AI techniques and knowledge graphs can be used to transform text-heavy applications into an interactive response system that can be used by scientists, technologists, politicians, and scholars along with smart applications, intelligent chatbots, and question/answering machines, as well as other AI and data systems.

This session looks at how AI and data science may be able to shape the world of project delivery, particularly projects which have a high degree of complexity but only if mediated by human sense-making and decision support. Our experienced and popular speaker takes work from counter-terrorism (his DARPA and other work) and applies them to project management using a multi-methods approach. Get in on the ground floor and grab new ways of thinking about AI and analytics.

A panel of four text analytics experts answer questions that have been gathered before the conference, during the conference and some additional questions from the program chair. This was one of our most popular features last year, so come prepared with your favorite questions and be ready to learn!

We’ve been doing text analytics since the mid-2000s. What’s working and what’s not? Seth Grimes presents findings from a 2019 study that surveyed user experiences with text technologies, solutions, and providers. What capabilities are users looking for in text analytics products and services, and are they finding what they need? How has the market evolved—both demand and supply—and how should practitioners and solution providers stay on top of developments? This talk provides practical guidance from fellow users to help you extract the greatest value from text analytics.

At Indeed, we analyze petabytes of unstructured text in support of our mission to help people get jobs. We strive to go beyond keyword search and enable users to search by concepts relevant to their job interests, such as occupation, location, or salary range. Our talk focuses on entity extraction: how can it unlock meaning from big data and what are the best strategies for implementing it? Should you build an in-house tool, choose an off-the-shelf tool, or combine both of these approaches? We review lessons learned from implementing each of these strategies at Indeed. This presentation is targeted at practitioners who want to develop scalable information extraction systems and are interested in decision factors such as model performance, startup training costs, operator workflows, ongoing maintenance, and risk mitigating strategies.

Text analytics is a well-established discipline, yet many organizations don’t have dedicated text analyst roles. When they do, they arise from ad hoc needs and are embedded within specific functional units, often doing work which could be repurposed for other processes. One part call to action, one part proposal, hear ideas about who a text analyst is, where this role should sit in the organization, and what actions to take to create a text analyst role in your organization.

Increasingly, knowledge managers and product developers are looking beyond in-house proprietary data to external sources to provide context and critical information. For companies focused on innovation and research, important sources include scientific journal publications, specialized databases, and a growing body of open access data. This talk looks closely at two different customer use cases that take text and data mining (TDM) projects from start to finish. The first is a knowledge manager seeking to enhance content discovery and linking key research findings to in-house data. The second is a company focused on leveraging research content for product development. In both cases, TDM is applied to drive an efficient research and discovery process, saving time and money, and positively impacting revenue.

Text Analytics has emerged as a defining technology for enterprise transformation. Its promise is no less than a radical rethinking of how businesses organize their workflows and take decisions. When cognitive processes can be automated and scaled, the impact is faster processes and better insights, enabling professionals to focus on the highest added-value parts of their mission. Join this session to discover today’s “art of the possible” in NLP, based on examples of leading-edge analytics and process automation applications

A panel of four text analytics experts answer questions that have been gathered before the conference, during the conference and some additional questions from the program chair. This was one of our most popular features last year, so come prepared with your favorite questions and be ready to learn!

In the age of new and useful technologies rushing to take their place in our organizations, 80% of respondents to a recent global culture survey say their organization’s culture must evolve in the next 5 years for their company to succeed, grow, and retain the best people. Yes, it’s all about the people in any organization. Technology can certainly support, speed, and spark knowledge sharing, innovation and success, but culture is implicit rather than explicit, emotional rather than rational—that’s what makes it so hard to work with, but that’s also what makes it so powerful! Anderson shares secrets from her recent book, a practical guide to working with culture and tapping into a source of catalytic change within your organization. Since every organization’s culture is intimate and personal, aligning culture always involves getting to the heart of difficult matters, unearthing the “family secrets” of a company—the emotional histories that lie under the surface of the story the company tells about itself to the outside world. Get lots of insights and tips to use in your organization to build a knowledge-sharing culture which supports success!

Creating a consumer-like, personalized experience for the daily work of finding information people need to do their jobs is the crux of efficient knowledge sharing. These uniquely personal experiences facilitate the flow of organizational operations and more intelligent decision-making. Professionals at companies like Red Hat, Reddit, and PwC rely on this type of platform to quickly find answers and proactively suggest insights. Learn how they approached their challenges and the solutions they found to empower employees to be more productive and help their organizations to attract and retain the best talent.

Our speaker shares best practices for and lessons learned from implementing and enriching enterprise search solutions.

Government influence operations (IO) have been conducted throughout recorded history. In recent times, they have commonly been referred to as propaganda, active measures, or psychological operations (PSYOPS). More than a century of Russian “Chekist” tradition has culminated in a force that can mobilize thousands of humans augmented by unlimited numbers of bots. As documented in congressional testimony, this force has repeatedly seized control of foreign news cycles, inserting sentiments or wholly fictional stories. A simple positive/neutral/negative axis is not as applicable to the IO mission as one specific to the operation in question, such as entity stability/ instability, trustworthiness, or advocacy of violence. Given an IO action, such as promotion of an embarrassing story, the operator wants to measure the effect as change in sentiment, such as distrust of the now-discredited entity.

Regulations.gov was launched in 2003 to provide the public with access to federal regulatory content and the ability to submit comments on federal regulations. Manually reading thousands of comments is time-consuming and labor-intensive. It is also difficult for multiple reviewers to accurately and consistently assess content, themes, stakeholder identity, and sentiment. In response to this issue, text analytics can be used to develop transparent and accurate text models, and visual analytics can quantify, summarize, and present the results of that analysis. This talk addresses public commentary submitted in response to new product regulations by the U.S. Food and Drug Administration.

Due to subjective content, an absence of labels and a lack of dimensions, analyzing unstructured data can be a challenging task. In this session we’ll discuss improving unstructured data analysis through automation (including a human-in-the-loop), pre-processing capabilities for reducing noise, and options for feature engineering and extraction. You will also get an overview of our hybrid analytical platform, which combines Natural Language Processing along with Machine Learning and statistical techniques in order to deliver rich insights. Our hope is that regardless of your platform of choice, you obtain ideas that make your own analysis easier and more effective

One fundamental obstacle for using machine learning (ML) to accurately extract facts from free text documents is that it requires huge amounts of pre-categorized data for training. Manual annotation is not a viable option as it would entail enormous amounts of human analyst time. In this presentation we outline an innovative rule-based approach for automated generation of pre-categorized data that can be further used for training ML models. This approach relies on writing queries expressed in the powerful pattern definition language that fully exploits the results of the underlying natural language processing (NLP): deep linguistic, semantic, and statistical analysis of documents. The sequential application of rule-based and ML techniques facilitates the high accuracy of results. An example project illustrating this technology focuses on the automated extraction of clinical information from patient medical records.

Efforts to counter human trafficking internationally must assess data from a variety of sources to determine where best to devote limited resources. How can analysts effectively tap all the relevant data to best inform decisions to counter human trafficking? This presentation showcases a framework supporting AI for exploring all data related to counter human trafficking initiatives internationally. The framework incorporates rule-based and machine learning (ML) text analytics results not available in the original datasets. As a focal point, we demonstrate how to apply rule-based text extraction of trafficking victims to generate training data for subsequent ML and deep learning models. We ultimately show how this framework provides decision makers with capabilities for countering human trafficking internationally, and how it is extensible as new AI techniques and sources of information become available.

As organizations shift focus from data-generating to data-powered, the ability to incorporate all information—structured and unstructured—is key to delivering insight that is trusted by the business. What does an organization need to bring together all information and successfully manage its data quality? Semantic AI provides the context and meaning that transforms textual information into trusted data. It uncovers the insights and relationships using NLP, machine learning, and AI strategies so you can expose new information to the business and answer questions you couldn’t answer before. Using the real-life success story of one of the world’s largest auto manufacturers that uses Semantic AI to harmonize, extract, and enrich data for vehicle safety analysis, this session covers how the use of Semantic AI cleans and calibrates IoT, text-based data, and unstructured content to improve data quality, analytics, and the fidelity of business decisions.

How can we classify audio files of music with very sparsely available text? A large commercial music publisher with a faceted classification system (for 650,000 tracks!) realized that its search problems were caused by incomplete, missing, or misapplied metadata. Additionally, the text associated with each track (or album) was spotty at best. In this talk, Kasenchak describes the variety of text analytical (and other) approaches used to try to solve the problem: adding or correcting metadata to improve search.

Vocabularies and natural language processing (NLP) often work handin- hand to provide text analytics solutions. This talk explores this partnership in detail in the context of a specific knowledge domain: biomedicine. Standard assumptions made by NLP engines regarding how words are stemmed, tokenized, assembled to form phrases and sentences can be challenged by a specialized domain such as biomedicine, which has its own terminology and knowledge models. Biomedical vocabularies and ontologies play an essential role to make biomedical text is being analyzed appropriately. This talk goes into more detail about how the two capabilities—domain-specific vocabularies and ontologies and NLP engines—can learn from each other to deliver better biomedical text analytics solutions.

The Internet of Things, computer vision, and document understanding are all becoming critical drivers of enterprise evolution. These are the “3 Pillars of AI” and they are having a real, practical impact on the world of KM. Khan, who leads Accenture's Search & Content Analytics Group, briefly explains these pillars, delving into document understanding and explaining how it is drastically changing the search and KM landscape. Citing a real-world example, he discusses how search and analytics are being combined with AI technologies like machine learning and natural language processing to help make it possible for a global enterprise to extract valuable insights from their untapped, unstructured data sources, improving operations and maintaining a competitive advantage.

KMWorld magazine is proud to sponsor the 2019 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 Intranet & Digital Awards, where you get a sneak peek behind the firewall of these organizations.

AI promises to categorize all types of content with reliable results, but the reality is much more complex. Most applications won’t work with a meat grinder approach, where you pour a huge amount of content in one end and a perfectly organized collection comes out the other end. Effective automated categorization depends on defining a process workflow and assembling a stack of methods to process different types of content in different ways. Designing and validating a content processing workflow requires human judgments. So good quality categorization applications often rely on how to make the best use of people. This presentation provides a reality check on unsupervised automated categorization, and discusses a case study in which the performance was suitable for editorial review and approval, but not for unsupervised processing of a large collection.

There is no such thing as unstructured text—even tweets have some structure—words, clauses, phrases, even the occasional paragraph. Techniques that treat documents as undifferentiated bags of words have never achieved a high enough accuracy to build good auto-categorization whether using machine learning (ML) or rules. However, going beyond bags of words and utilizing the structures found in “unstructured” text, it is possible to achieve dramatically improved accuracy. This talk, using multiple examples from recent projects, presents how to build content structure models and content structure rules that can be used for both rules-based and ML categorization. We conclude with a method for combining rules and ML in a variety of ways for the best of both worlds.

The American Psychological Association’s PsycINFO databases release around 3,000 records per month. In June 2017, a plan was created to bring machine-aided indexing (MAI) back to the APA’s PsycINFO databases. Since then, MAI has been implemented across three of the databases, including PsycARTICLES. Pearson discusses the strategy used to build the rule base, and integrate the software into the production system. He also takes a look at some of the challenges faced along the way and explores future goals and further deployment plans.

Products like Amazon Alexa and Google Home are changing the expectations as to how search should work. Searchers now expect voice-driven search solutions that provide answers and not just a list of links. Part of this talk shares how knowledge graphs enable a natural language search and how text analytics along with machine learning can be used to populate these powerful constructs. We explain how to architect these solutions and provide real world examples as to how many of our clients have taken advantage of these powerful tools.

Similar to many enterprises, the Inter-American Development Bank (IDB) has multiple information sources which are isolated in different systems. There is no link between all these information resources that can make them accessible outside of their native systems. It is not possible to relate distinct kinds of resources that share some characteristics, e.g., to find a course that is about the same topic as a publication. To achieve this objective, IDB implemented a system that can automatically extract entities and concepts from its systems, including structured and unstructured data. Further, it semantically enhanced the data and made it accessible in a Knowledge Graph. Hernandez and Marino share lessons learned from this project that can help interested attendees start with a baseline of best practices for their own projects, saving valuable time and money.

In some contexts, such as e-discovery, achieving high recall when retrieving documents is critical. Over the past year, Dimm has challenged audiences at several conferences to construct keyword searches that perform better than supervised machine learning. This talk summarizes the results and explains why it is so hard for humans to beat machine learning when seeking high recall.

It's “How the Future Was” in 2004: Microsoft and enterprise search vendors showed semantic search demos that were "so close" to being better than keywords. Fifteen years on, we're still "so close," and most information retrieval searches are still keyword lookups in hash tables. What has happened is that semantic search matured in other directions. We explore multiple use cases and specific applications to government missions and commercial business problems, where semantic search has established these and a few other niches. We give special emphasis to the “analytic refutation problem,” in which both keyword search and much of current AI serves only to assist people find even more content that reinforces their biases and mistaken conceptions. Here semantic search has found its deepest niche: helping human analysts triage otherwise intractable quantities of textual information, maintaining a healthy bias against their working hypotheses.

Combining search with text analytics creates a powerful tool called SAS Cognitive Search to elevate the intelligence of information retrieval. Search features a flexible query syntax to fit various business needs and help uncover insights hidden in data. Text analytics can extract entities from user text data and enrich the raw data with category and sentiment information. This session presents an easy-to-use interface that leverages SAS Cognitive Search to perform search on temporal and spatial data, enriched with NLP features. With this interface, the user can analyze customer reviews for a product category to create a timeline and deduce trends. Other features include an interactive map facilitating geographic data search and filtering and a facet-based view for query results aggregation. Understanding your customers and what they think of your products has never been easier!

Key words and hundreds, if not thousands, of rules are no longer enough to keep up with Amazon and recapture lost market share. Amazon has set the new standard that organizations must meet to effectively compete for their customers’ attention. Join this presentation and learn how to capture and aggregate valuable customer interactions like queries, clicks, and cart behavior in real-time so every customer gets a customized experience that is continuously being refined; easily incorporate regional trends and seasonality to deliver relevant results; make every customer experience personal; and run A/B testing and experiments so the shopping and purchase flow is constantly fine-tuned and optimized. Go from running a few experiments that take months to get out the door to dozens running live in production, without having to bother your data scientists or the engineers.

Similar to many enterprises, the Inter-American Development Bank (IDB) has multiple information sources which are isolated in different systems. There is no link between all these information resources that can make them accessible outside of their native systems. It is not possible to relate distinct kinds of resources that share some characteristics, e.g., to find a course that is about the same topic as a publication. To achieve this objective, IDB implemented a system that can automatically extract entities and concepts from its systems, including structured and unstructured data. Further, it semantically enhanced the data and made it accessible in a Knowledge Graph. Hernandez and Marino share lessons learned from this project that can help interested attendees start with a baseline of best practices for their own projects, saving valuable time and money.

Products like Amazon Alexa and Google Home are changing the expectations as to how search should work. Searchers now expect voice-driven search solutions that provide answers and not just a list of links. Part of this talk shares how knowledge graphs enable a natural language search and how text analytics along with machine learning can be used to populate these powerful constructs. We explain how to architect these solutions and provide real world examples as to how many of our clients have taken advantage of these powerful tools.

The possibilities are endless but what can we really expect in 2020? Our experience speaker, who wrote the book SharePoint 2013 Consultant’s Handbook, coached people on metadata and taxonomies as well apps for Office 365, and more, shares the most recent developments and promises for the coming years.

We live in a world which promises infinite choice, but are we more trapped in the patterns of past practice than we care to think? Is the hierarchical or matrixed organization fit for purpose in a world of increased uncertainty and volatility? Governments have increasing legitimate demands on their resources from citizens and the wider needs of the planet, but few resources to deal with it. Ideology and belief seem at times to triumph over fact, evidence, and reason. Have we gone beyond even post-modernism into a new world with constantly shifting paradigms and increasingly less time to adjust to them? Our panel looks at these questions from the perspectives of knowledge and complexity. They discuss transforming and revolutionizing the way we do business as we move into an uncertain future, how we satisfy our clients in an ever-changing technological age, and how, in our complex societies, we provide value, exchange knowledge, innovate, grow and support our world. Our panel of experienced thinkers and doers shares their insights about what we should be doing to further develop a sustainable ecosystem in our organizations, communities, and world.