IAC 2024 - IA Fast Track to Search Focused AI Solutions
DBtrends: Exploring Query Logs for Ranking RDF Data
1. DBtrends
Exploring Query Logs for
Ranking RDF Data
AKSW
Edgard Marx, Amrapali Javeri,
Diego Moussallem, Sandro Rautenberg
12th International Conference on Semantic Systems
4. 4
http://linkeddatacatalog.dws.informatik.uni-annheim.de/state/
"The size of LOD by 2014 was 31 billion triples"
"Facebook users generates 2.7 billion Like actions
per day and 300 million new
photos are uploaded daily"
Josh Constine, 2012
We Have Data
"Google Processing 20,000
Terabytes A Day, And Growing"
Erick Schonfeld, 2008
techcrunch.com
techcrunch.com
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Motivation
11. Things
11
Background
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Web of Data
• Semantic Search
• Entity Search
• Question Answering
• Named Entity Recognition
• Link Discovery
• Machine Learning
Use RDF Data
E=MC²
19. Benchmarks
19
DBtrends Benchmark (Marx, 2016)
• 60 users from different countries (USA, India)
• 9 entity ranking functions applied to DBpedia Knowledge Base
• Users sort relevant classes, properties and entities
extracted from the top twenty entities belonging to the top four
classes
• Task were executed using Amazon Mechanical Turk
Previous Benchmarks
• Not public available
• Evaluate performace of 30 profiles
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Background
20. Why use query logs?
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Ranking using Query Logs
21. Why use query logs?
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21
Ranking using Query Logs
22. Why use query logs?
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Ranking using Query Logs
Query Logs
search...
23. Why use query logs?
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23
Ranking using Query Logs
24. Why use query logs?
• Query logs provide relevant
information about user's
preference
• They refer to the real-world
entities
E=MC²
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Ranking using Query Logs
25. Questions
• How to map real-world entities
to Web of Data?
• How to measure it's relevance?
• Where to find a good and trustable
query log?
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25
Ranking using Query Logs
26. How to map real world
resources?
• Rocha et al. (2004)
• Ding et al. (2005)
• Hogan et al. (2006)
• Alsarem et al (2015)
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Ranking using Query Logs
Query Logs
search...
Web of Data
27. How to measure the
resource's relevance?
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Ranking using Query Logs
• Users search (more often) for
things that are relevant
• Query logs register how often
something is searched
• Query logs can be used for
better estimate resource's
relevance by looking how often
it is searched
28. Where to find a good and
trustable query log?
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Ranking using Query Logs
29. Where to find a good and
trustable query log?
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Ranking using Query Logs
30. Where to find a good and
trustable query log?
• Public API
• Filters
Geographic
• Country
• State
• City
Period
Day
Week
Month
Year
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Ranking using Query Logs
32. DBtrends Ranking Function
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32
Ranking using Query Logs
36
Trendsdbr:New_York_City
“New York”
dbo:City
dbo:Place
2
1
1
• First, the labels of the entities are extracted
and used to acquire the search history in
query logs e.g. GoogleTrends ( )2-
33. DBtrends Ranking Function
18
36
Trendsdbr:New_York_City
“New York”
dbo:City
dbo:Place
1
2
3
4
9 • First, the labels of the entities are extracted
and used to acquire the search history in
query logs e.g. GoogleTrends ( )
• Thereafter, the entity ranks are used as a
base to propagate the rank to the classes
( )3 4-
2-
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1
33
Ranking using Query Logs
38. Discussion
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• Functions that take into
consideration external information
provide more insights about
resource's relevance
• RDF Links reflect natural connections
rather than resouce's relevance
• MIXED-RANK
• PAGE-RANK
• E-PAGE-IN
• SHARED-LINKS
• SEO-PA
• DB-OUT
• PAGE-IN
• DBtrends
• PAGE-OUT
• DB-IN
• DB-RANK
Entity
38
Evaluation
39. Discussion
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• There is no pattern in the impact
distribution of query longs
• Queries (not necessarly) help to
improve a ranking functions
• Internal agreement ~63%
39
Evaluation Entity
44. Discussion
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• Confidence in executing the tasks:
Indians 90%
Americans 60%
• Ranks produced by Indians were
more sparse
• Abstract entities appear before
entities
44
Evaluation Caviats
45. Summary
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• Entity Ranking functions produce better results
when considering external information
• A simple sort of the number of instances can be
very effective for ranking classes
• Query logs can (not necessarily) improve entity
ranking functions
45
Evaluation
47. Future Works
AKSW
• Extend the evaluation to other
countries and ranking functions
• Evaluate the impact of
contex-aware ranking functions
• Use others similarity ranking
functions
47