Talk given at the Dagstuhl Seminar on Conversational Search, November 2019

1. PERSONAL KNOWLEDGE GRAPHS
Krisztian Balog
University of Stavanger
@krisztianbalog
Dagstuhl Seminar on Conversa>onal Search | Dagstuhl, Germany, November 2019

2. KNOWLEDGE GRAPHS ARE POWERFUL ASSETS
FOR A BROAD RANGE OF SEARCH,
RECOMMENDATION, AND MINING SCENARIOS

4. What is the capital of
Norway?

5. What is its popula>on?

6. KNOWLEDGE GRAPHS ARE POWERFUL ASSETS
FOR A BROAD RANGE OF SEARCH,
RECOMMENDATION, AND MINING SCENARIOS
They tend to focus on prominent, globally important en@@es
This rules out many en@@es we interact with on a daily basis!

7. MOTIVATIONAL SCENARIO
I would like to get some new strings
for my guitar
AIOK, would that be your electric guitar or
the acoustic one?
The electric one.
AIAlright. I can repeat your Amazon order of
3 months ago, or you can go by a music
store on Elm street on the way to your
dentist appointment this afternoon.

8. MOTIVATIONAL SCENARIO #2
AISince you're running a half marathon at
Hackney in May, may I suggest you
undertake a 10k run this weekend?
Yes, that sounds like a good idea. Any
suggestions for a not too popular route
that I haven't done before?
AISure thing. I'll upload some routes to the
running app on your phone.
Cheers mate!

9. IT IS DIFFICULT TO IMAGINE A TRULY
PERSONAL CONVERSATIONAL ASSISTANT
WITHOUT IT HAVING ACCESS TO
STRUCTURED PERSONAL INFORMATION

10. PERSONAL KNOWLEDGE GRAPHS
A personal knowledge graph (PKG) is
a resource of structured information
about entities that are of personal
interest to the user
Key differences from general KGs:
• Entities of personal interest to the user
• Distinctive shape (“spiderweb” layout)
• Links between a PKG and external
sources are inherent to its nature

11. ASSOCIATED PROBLEMS
• Knowledge representation
• Semantic annotation of text
• Population and maintenance
• Integration with external sources

12. KNOWLEDGE REPRESENTATION
Task: representing entities and their properties
• KGs are organized according to a knowledge model (schema)
Peculiarities/challenges
• Entities need to be (directly/indirectly) connected to the user
• Not all attributes have to be filled; the focus is on personal relevance
• Information about entities can be very sparse
• Some entities may not have any digital presence
• Relations can be highly temporal in nature
RQ1
How should en@@es and their proper@es and rela@ons be represented,
considering the vast but sparse set of possible predicates and their short-lived
nature?

13. SEMANTIC ANNOTATION OF TEXT
Task: annotating text with respect to a knowledge repository (commonly
known as entity linking)
• Usually involves mention detection, entity disambiguation, and NIL-
detection
Challenges
• Entities might have little to no digital presence
• Entities are not necessarily proper nouns
• Linking, NIL-detection, and KG population are intertwined
RQ2a How can en@ty linking be performed against a personal knowledge graph,
where structured en@ty informa@on to rely on is poten@ally absent?
When should en@ty linking be performed against a personal knowledge graph
as opposed to a general-purpose KG?
RQ2b

14. POPULATION AND MAINTENANCE
Task: extending a KG from external sources (KB acceleration/
population) or via internal inferencing
• Verification of facts in the KG
Challenges
• Single curator => More automation is desired than for KGs, but the
user should still be in control
• The first mention of an entity should trigger population
• Properties may be inferred from the context
RQ3 How can personal knowledge graphs be automa@cally populated and reliably
maintained?

15. INTEGRATION WITH EXTERNAL SOURCES
Task: recognizing the same entity across multiple data sources
• Also known as: object resolution, record linkage
Challenges
• One-to-many, as opposed to one-to-one linkage
• Continuous process, not a one-off effort
• Two-way synchronization would be desired
• Conflicting facts or relations need resolving by the user
RQ4 How should external knowledge sources con@nuously be integrated with, in a
two-way process, poten@ally involving the user?

16. THERE IS MORE…
Evaluation
• This would require an environment where users can interact with a
PKG
Implementation
• Storage (cloud vs. device), security, privacy, access control, ...
Utilization
• From specific apps (calendar, health/wellbeing app, etc.) to a truly
personal assistant

17. TAKING CONTROL OF OUR DATA
Present Alternative
service #1
service #2
service #3
service #1
service #2
service #3
Different service providers each have some (possibly
overlapping) portion of the person’s PKG
The person has full control over her PKG and may grant access
to different service providers to specific parts of the PKG

18. http://bit.ly/ictir2019-pkg