Knowledge Graphs - Creating Connected Search Experiences
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The document discusses enhancing search experiences by implementing connected knowledge graphs and semantic technologies to improve information retrieval. It emphasizes the importance of actionable and context-rich search results that cater to user needs rather than traditional keyword-based searches. The discussion also highlights the growing significance of integrating structured and unstructured data to enable more effective natural language search and aggregation of information.
Knowledge Graphs - Creating Connected Search Experiences
- 1. CREATING CONNECTED SEARCH EXPERIENCES November 7, 2019
- 2. JOE HILGER • Principal Consultant and co-founder at Enterprise Knowledge. • 20 years of KM and technology consulting experience. • 13 years experience implementing enterprise search solutions. • Worked on close to 100 different search projects for companies around the world. @jhilgerbc, @ekconsulting
- 3. “Why can’t our search be more like Google?” “I can’t find anything on our company search.” “Our search would be great if people would just tag their content.” “Everything I find on our company search is old and out of date.” “I don’t trust our company search.” “Lets just use Google search so that we never have to worry about search again.” SEARCH COMPLAINTS Comments I have heard more than once during our search workshops. @jhilgerbc, @ekconsulting
- 4. BUILDING A CONNECTED SEARCH Knowledge Graphs A semantic technology used to aggregate information and map content relationships. Typically used to power Natural Language Search and Artificial Intelligence. Faceting Navigation based on taxonomies and metadata that allows users to filter search results to find information more quickly. Machine Learning Newer technologies that improve the way content is tagged and search results are presented. “The best search experiences connect people to information, information to people, and people to people.” @jhilgerbc, @ekconsulting Action-Oriented Rich search results that help users get their job done and not just find information. Commonly seen on Google. Roger F. Hilger Sr. Manufacturing Project Engineer Roger F. Hilger
- 5. ACTION ORIENTED SEARCH Action-Oriented Rich search results that help users get their job done and not just find information. @jhilgerbc, @ekconsulting Search is about things not strings Search is a detour from what your searchers are trying to do Do not force your searchers down false paths Key considerations: Roger F. Hilger Sr. Manufacturing Project Engineer Roger F. Hilger
- 6. GOOGLE: MOVIES I would like to see a movie and I am trying to find the one I want to see I want to… • Get tickets on-line • See movie times and locations for the next 4 days • View previews of the movie to see if I will like it. • See critics reviews • Find out what other people thought of it. @jhilgerbc, @ekconsulting
- 7. EK CUSTOMER: EXPERT SEARCH I need to speak with an expert in neurology to help answer a question. I want to… • Understand a person’s expertise • Contact them • Understand where they are • Learn who they work for or which department they work for @jhilgerbc, @ekconsulting
- 8. EK CUSTOMER: CONFERENCE ROOMS I want to book a conference room for my upcoming meeting. I want to… • Find which conference rooms are open • Understand which room best meets my purposes • Find a room that is close to me @jhilgerbc, @ekconsulting
- 9. KNOWLEDGE GRAPHS Knowledge Graphs A semantic technology used to aggregate information and map content relationships. Typically used to power Natural Language Search and Artificial Intelligence. @jhilgerbc, @ekconsulting • A knowledge graph: a network of the things we want to describe and how they are related • We construct a semantic model since we want to capture and generate meaning with the model “The application of graph processing and graph DBMSs will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science.” – Gartner’s Top 10 Data and Analytics Technology Trends for 2019
- 10. WHAT IS A KNOWLEDGE GRAPH Content Sources Subject Predicate Object Project A hasTitle Title A Person B isPMOn Project A Document C isAbout Topic D Document C isAbout Topic F Person B IsExpertIn Topic D … … … Business Ontology Graph Database Enterprise Knowledge Graph Business Taxonomy Person B Project A Document C Person F Topic D Topic E @jhilgerbc, @ekconsulting
- 11. BENEFITS OF A KNOWLEDGE GRAPH Understanding Context Relationships between information allows gives us a better understanding of how things fit together so that search can be more precise. Structured and Unstructured Information Graphs allow for the integration of structured and unstructured information so that users can search for data and content at the same time. Natural Language Search Graphs store information the way people speak. Integrating a graph into your search makes natural language search easier to implement. Aggregation Graphs allow for aggregation of information from multiple disparate solutions so that search results can display information that exists in multiple locations and formats. @jhilgerbc, @ekconsulting
- 12. EK CUSTOMER: PEOPLE @jhilgerbc, @ekconsulting
- 13. EK CUSTOMER: TOPICS/PROJECTS @jhilgerbc, @ekconsulting
- 14. GOOGLE’S KNOWLEDGE GRAPH @jhilgerbc, @ekconsulting
- 15. WE’LL BE ANSWERING QUESTIONS NOW Q A& THANKS FOR LISTENING Q & A SESSION