RDF is increasingly being used to represent large amounts of data on the Web. Current query evaluation strategies for RDF are inspired by databases, assuming perfect answers on finite repositories. In this paper, we present a novel query method based on evolutionary computing, which allows us to handle uncertainty, incompleteness and unsatisfiability, and deal with large datasets, all within a single conceptual framework. Our technique supports approximate answers with anytime behaviour. We present initial results and analyse next steps for improvement.

1. An Evolutionary Perspective on
Approximate RDF Query Answering
Christophe Guéret, Eyal Oren, Stefan Schlobach,
Frank van Harmelen and Martijn Schut
Vrije Universiteit, Amsterdam

2. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
griffioen
SUM 2008 - October 2, 2008 2 / 24

3. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
Data on the Web
griffioen
SUM 2008 - October 2, 2008 2 / 24

4. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
Data on the Web
Inconsistent, uncertain, heterogeneous, Huge and growing!
griffioen
SUM 2008 - October 2, 2008 2 / 24

5. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
Data on the Web
Inconsistent, uncertain, heterogeneous, Huge and growing!
RDF Query answering
griffioen
SUM 2008 - October 2, 2008 2 / 24

6. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
Data on the Web
Inconsistent, uncertain, heterogeneous, Huge and growing!
RDF Query answering
Finding data matching criterion
griffioen
SUM 2008 - October 2, 2008 2 / 24

7. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
Data on the Web
Inconsistent, uncertain, heterogeneous, Huge and growing!
RDF Query answering
Finding data matching criterion
... many queries are actually not satisfiable
griffioen
SUM 2008 - October 2, 2008 2 / 24

8. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
Data on the Web
Inconsistent, uncertain, heterogeneous, Huge and growing!
RDF Query answering
Finding data matching criterion
... many queries are actually not satisfiable
Approximate RDF Query answering
griffioen
SUM 2008 - October 2, 2008 2 / 24

9. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
Data on the Web
Inconsistent, uncertain, heterogeneous, Huge and growing!
RDF Query answering
Finding data matching criterion
... many queries are actually not satisfiable
Approximate RDF Query answering
Finding some, almost valid, data
griffioen
SUM 2008 - October 2, 2008 2 / 24

10. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
Data on the Web
Inconsistent, uncertain, heterogeneous, Huge and growing!
RDF Query answering
Finding data matching criterion
... many queries are actually not satisfiable
Approximate RDF Query answering
Finding some, almost valid, data
The Evolutionary Perspective
griffioen
SUM 2008 - October 2, 2008 2 / 24

11. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
Data on the Web
Inconsistent, uncertain, heterogeneous, Huge and growing!
RDF Query answering
Finding data matching criterion
... many queries are actually not satisfiable
Approximate RDF Query answering
Finding some, almost valid, data
The Evolutionary Perspective
Test different solutions
griffioen
SUM 2008 - October 2, 2008 2 / 24

12. Problem and context Method proposed Experimental results Conclusion
The next 30 minutes in 4 points...
RDF
Data on the Web
Inconsistent, uncertain, heterogeneous, Huge and growing!
RDF Query answering
Finding data matching criterion
... many queries are actually not satisfiable
Approximate RDF Query answering
Finding some, almost valid, data
The Evolutionary Perspective
Test different solutions
Progressive optimisation of the result griffioen
SUM 2008 - October 2, 2008 2 / 24

13. Problem and context Method proposed Experimental results Conclusion
1 What’s the problem ?
Querying RDF datastores
Standard techniques
2 And Now for Something Completely Different
Guessing the solution instead
The way we do it
3 Does it work ?
Evolution of the quality
Some characteristics of this method
4 TODO list
griffioen
SUM 2008 - October 2, 2008 3 / 24

14. Problem and context Method proposed Experimental results Conclusion
1 What’s the problem ?
Querying RDF datastores
Standard techniques
2 And Now for Something Completely Different
Guessing the solution instead
The way we do it
3 Does it work ?
Evolution of the quality
Some characteristics of this method
4 TODO list
griffioen
SUM 2008 - October 2, 2008 4 / 24

15. Problem and context Method proposed Experimental results Conclusion
Example
RDF dataset
<Ullman88> type Book .
<Ullman88> label "Principles of Database and
Knowledge-Base Systems" .
<Ullman88> author b1 .
b1 _1 ullman .
ullman homepage <http://stanford.edu/~ullman/> .
SPARQL query
SELECT ?title WHERE {
?publication type Book .
?publication label ?title .
}
Expected answer
griffioen
?title = "Principles of Database and Knowledge-Base Systems
SUM 2008 - October 2, 2008 5 / 24

16. Problem and context Method proposed Experimental results Conclusion
Problem description
Triple =
subject,
predicate,
object
Dataset =
graph of
triples
Querying :
find a
pattern in
the graph griffioen
A query and a graph [PSPARQL07]
SUM 2008 - October 2, 2008 6 / 24

17. Problem and context Method proposed Experimental results Conclusion
Standard techniques
Standard approach :
griffioen
SUM 2008 - October 2, 2008 7 / 24

18. Problem and context Method proposed Experimental results Conclusion
Standard techniques
Standard approach :
1 Find all the possible results for ?publication type
Book
griffioen
SUM 2008 - October 2, 2008 7 / 24

19. Problem and context Method proposed Experimental results Conclusion
Standard techniques
Standard approach :
1 Find all the possible results for ?publication type
Book
?publication
<Ullman88>
griffioen
SUM 2008 - October 2, 2008 7 / 24

20. Problem and context Method proposed Experimental results Conclusion
Standard techniques
Standard approach :
1 Find all the possible results for ?publication type
Book
?publication
<Ullman88>
2 Find all the possible results for ?publication label
?title
griffioen
SUM 2008 - October 2, 2008 7 / 24

21. Problem and context Method proposed Experimental results Conclusion
Standard techniques
Standard approach :
1 Find all the possible results for ?publication type
Book
?publication
<Ullman88>
2 Find all the possible results for ?publication label
?title
?publication ?title
<Ullman88> "Principles of ..."
griffioen
SUM 2008 - October 2, 2008 7 / 24

22. Problem and context Method proposed Experimental results Conclusion
Standard techniques
Standard approach :
1 Find all the possible results for ?publication type
Book
?publication
<Ullman88>
2 Find all the possible results for ?publication label
?title
?publication ?title
<Ullman88> "Principles of ..."
3 Do a join on the two tables and return the result
griffioen
SUM 2008 - October 2, 2008 7 / 24

23. Problem and context Method proposed Experimental results Conclusion
Standard techniques
Standard approach :
1 Find all the possible results for ?publication type
Book
?publication
<Ullman88>
2 Find all the possible results for ?publication label
?title
?publication ?title
<Ullman88> "Principles of ..."
3 Do a join on the two tables and return the result
?title = "Principles of ..."
griffioen
SUM 2008 - October 2, 2008 7 / 24

24. Problem and context Method proposed Experimental results Conclusion
Standard techniques
Standard approach :
1 Find all the possible results for ?publication type
Book
?publication
<Ullman88>
2 Find all the possible results for ?publication label
?title
?publication ?title
<Ullman88> "Principles of ..."
3 Do a join on the two tables and return the result
?title = "Principles of ..."
Fast thanks to the creation of indexes and query
optimisation griffioen
SUM 2008 - October 2, 2008 7 / 24

25. Problem and context Method proposed Experimental results Conclusion
Motivation
Designed to return results only when there are some
Not designed for incomplete and approximate
queries/answers
Hard to distribute
griffioen
SUM 2008 - October 2, 2008 8 / 24

26. Problem and context Method proposed Experimental results Conclusion
Motivation
Designed to return results only when there are some
Not designed for incomplete and approximate
queries/answers
Hard to distribute
Approximate answers to precise queries
If the query is unsat, return the best almost sat solution
found
griffioen
SUM 2008 - October 2, 2008 8 / 24

27. Problem and context Method proposed Experimental results Conclusion
Motivation
Designed to return results only when there are some
Not designed for incomplete and approximate
queries/answers
Hard to distribute
Approximate answers to precise queries
If the query is unsat, return the best almost sat solution
found
Precises answers to approximate queries
Return a subset of existing solutions instead of showing
them all
griffioen
SUM 2008 - October 2, 2008 8 / 24

28. Problem and context Method proposed Experimental results Conclusion
Motivation
Designed to return results only when there are some
Not designed for incomplete and approximate
queries/answers
Hard to distribute
Approximate answers to precise queries
If the query is unsat, return the best almost sat solution
found
Precises answers to approximate queries
Return a subset of existing solutions instead of showing
them all
Interactive querying
Use of intermediate results to help the user improving his griffioen
query
SUM 2008 - October 2, 2008 8 / 24

29. Problem and context Method proposed Experimental results Conclusion
1 What’s the problem ?
Querying RDF datastores
Standard techniques
2 And Now for Something Completely Different
Guessing the solution instead
The way we do it
3 Does it work ?
Evolution of the quality
Some characteristics of this method
4 TODO list
griffioen
SUM 2008 - October 2, 2008 9 / 24

30. Problem and context Method proposed Experimental results Conclusion
Approach
“I’m Feeling Lucky” approach :
griffioen
SUM 2008 - October 2, 2008 10 / 24

31. Problem and context Method proposed Experimental results Conclusion
Approach
“I’m Feeling Lucky” approach :
1 Assign some random values to the variables
griffioen
SUM 2008 - October 2, 2008 10 / 24

32. Problem and context Method proposed Experimental results Conclusion
Approach
“I’m Feeling Lucky” approach :
1 Assign some random values to the variables
?publication = <Ullman88>
?title = Book
griffioen
SUM 2008 - October 2, 2008 10 / 24

33. Problem and context Method proposed Experimental results Conclusion
Approach
“I’m Feeling Lucky” approach :
1 Assign some random values to the variables
?publication = <Ullman88>
?title = Book
2 Verify if the solution is valid
griffioen
SUM 2008 - October 2, 2008 10 / 24

34. Problem and context Method proposed Experimental results Conclusion
Approach
“I’m Feeling Lucky” approach :
1 Assign some random values to the variables
?publication = <Ullman88>
?title = Book
2 Verify if the solution is valid
Triple Is in the graph ?
<Ullman88> type Book yes
<Ullman88> label Book no
griffioen
SUM 2008 - October 2, 2008 10 / 24

35. Problem and context Method proposed Experimental results Conclusion
Approach
“I’m Feeling Lucky” approach :
1 Assign some random values to the variables
?publication = <Ullman88>
?title = Book
2 Verify if the solution is valid
Triple Is in the graph ?
<Ullman88> type Book yes
<Ullman88> label Book no
3 If the solution is OK, stop. Otherwise, try again with
something else
griffioen
SUM 2008 - October 2, 2008 10 / 24

36. Problem and context Method proposed Experimental results Conclusion
Approach
“I’m Feeling Lucky” approach :
1 Assign some random values to the variables
?publication = <Ullman88>
?title = Book
2 Verify if the solution is valid
Triple Is in the graph ?
<Ullman88> type Book yes
<Ullman88> label Book no
3 If the solution is OK, stop. Otherwise, try again with
something else
Rely on membership testing (instead of lookup)
griffioen
SUM 2008 - October 2, 2008 10 / 24

37. Problem and context Method proposed Experimental results Conclusion
Approach
“I’m Feeling Lucky” approach :
1 Assign some random values to the variables
?publication = <Ullman88>
?title = Book
2 Verify if the solution is valid
Triple Is in the graph ?
<Ullman88> type Book yes
<Ullman88> label Book no
3 If the solution is OK, stop. Otherwise, try again with
something else
Rely on membership testing (instead of lookup)
The testing loop can be stopped at any time
griffioen
SUM 2008 - October 2, 2008 10 / 24

38. Problem and context Method proposed Experimental results Conclusion
Approach
“I’m Feeling Lucky” approach :
1 Assign some random values to the variables
?publication = <Ullman88>
?title = Book
2 Verify if the solution is valid
Triple Is in the graph ?
<Ullman88> type Book yes
<Ullman88> label Book no
3 If the solution is OK, stop. Otherwise, try again with
something else
Rely on membership testing (instead of lookup)
The testing loop can be stopped at any time
A result may satisfy part of the query griffioen
SUM 2008 - October 2, 2008 10 / 24

39. Problem and context Method proposed Experimental results Conclusion
Our choices
Need to pay attention to two aspects
griffioen
SUM 2008 - October 2, 2008 11 / 24

40. Problem and context Method proposed Experimental results Conclusion
Our choices
Need to pay attention to two aspects
1 Each try should be a step closer to the solution
Random guessing may never end
Stopping the process at t + 1 should give better results than
at t
griffioen
SUM 2008 - October 2, 2008 11 / 24

41. Problem and context Method proposed Experimental results Conclusion
Our choices
Need to pay attention to two aspects
1 Each try should be a step closer to the solution
Random guessing may never end
Stopping the process at t + 1 should give better results than
at t
2 Testing a candidate solution must be fast
Will try a lot of solutions
griffioen
SUM 2008 - October 2, 2008 11 / 24

42. Problem and context Method proposed Experimental results Conclusion
Our choices
Need to pay attention to two aspects
1 Each try should be a step closer to the solution
Random guessing may never end
Stopping the process at t + 1 should give better results than
at t
2 Testing a candidate solution must be fast
Will try a lot of solutions
We made the following choices
Generation of solutions : Evolutionary algorithm
Verification of solutions : Bloom filter based testing
griffioen
SUM 2008 - October 2, 2008 11 / 24

43. Problem and context Method proposed Experimental results Conclusion
Binary Bloom filters (1/2)
Compact representation of information : a set of n = 8 bits
1 2 3 4 5 6 7 8
Supports two operations
INSERT ( KEY ) : Insert a key into the filter
CONTAINS ( KEY ) : Test for the presence of a key
Use k = 3 hash functions to compute a set of bits from a
key
HASH 1(“ HELLO WORLD ”)=8
HASH 2(“ HELLO WORLD ”)=6
HASH 3(“ HELLO WORLD ”)=3
griffioen
SUM 2008 - October 2, 2008 12 / 24

44. Problem and context Method proposed Experimental results Conclusion
Binary Bloom filters (2/2)
INSERT (“ HELLO WORLD ”)
Current
Bit-wise or operation
OR
Always successful (i.e.
“Hello world”
unlimited capacity)
=
Precision depends of
New
number of elements m.
CONTAINS (“B ONJOUR !”)
Current
Bit-wise and operation
AND
“Bonjour !” Positive result can be a
collision
=
kn griffioen
Test result perror = (1 − e− m )k
SUM 2008 - October 2, 2008 13 / 24

45. Problem and context Method proposed Experimental results Conclusion
A first (naive) approach
Insert all the triples into a unique Bloom filter.
INSERT (“<Ullman88>_type_Book”)
INSERT (“<Ullman88>_label_"Principles of ..."”)
...
griffioen
SUM 2008 - October 2, 2008 14 / 24

46. Problem and context Method proposed Experimental results Conclusion
A first (naive) approach
Insert all the triples into a unique Bloom filter.
INSERT (“<Ullman88>_type_Book”)
INSERT (“<Ullman88>_label_"Principles of ..."”)
...
Use the CONTAINS operation to verify a solution
CONTAINS (“<Ullman88>_type_Book”) ⇒ true
CONTAINS (“<Ullman88>_label_Book”) ⇒ false
griffioen
SUM 2008 - October 2, 2008 14 / 24

47. Problem and context Method proposed Experimental results Conclusion
A first (naive) approach
Insert all the triples into a unique Bloom filter.
INSERT (“<Ullman88>_type_Book”)
INSERT (“<Ullman88>_label_"Principles of ..."”)
...
Use the CONTAINS operation to verify a solution
CONTAINS (“<Ullman88>_type_Book”) ⇒ true
CONTAINS (“<Ullman88>_label_Book”) ⇒ false
Not the best approach ! Let’s see what happen in detail . . .
griffioen
SUM 2008 - October 2, 2008 14 / 24

48. Problem and context Method proposed Experimental results Conclusion
A first (naive) approach
Insert all the triples into a unique Bloom filter.
INSERT (“<Ullman88>_type_Book”)
INSERT (“<Ullman88>_label_"Principles of ..."”)
...
Use the CONTAINS operation to verify a solution
CONTAINS (“<Ullman88>_type_Book”) ⇒ true
CONTAINS (“<Ullman88>_label_Book”) ⇒ false
Not the best approach ! Let’s see what happen in detail . . .
?publication label ?title
CONTAINS (“<Ullman88>_label_Book”)
griffioen
modify ?publication and ?title
SUM 2008 - October 2, 2008 14 / 24

49. Problem and context Method proposed Experimental results Conclusion
Graph parsing
Every triple of the graph is inserted into 4 Bloom filters
<Ullman88> type Book
griffioen
SUM 2008 - October 2, 2008 15 / 24

50. Problem and context Method proposed Experimental results Conclusion
Graph parsing
Every triple of the graph is inserted into 4 Bloom filters
<Ullman88> type Book
<Ullman88>_type_Book
SPO
griffioen
SUM 2008 - October 2, 2008 15 / 24

51. Problem and context Method proposed Experimental results Conclusion
Graph parsing
Every triple of the graph is inserted into 4 Bloom filters
<Ullman88> type Book
<Ullman88>_type_Book <Ullman88>_type
SPO SP
griffioen
SUM 2008 - October 2, 2008 15 / 24

52. Problem and context Method proposed Experimental results Conclusion
Graph parsing
Every triple of the graph is inserted into 4 Bloom filters
<Ullman88> type Book
<Ullman88>_type_Book <Ullman88>_type type_Book
SPO SP PO
griffioen
SUM 2008 - October 2, 2008 15 / 24

53. Problem and context Method proposed Experimental results Conclusion
Graph parsing
Every triple of the graph is inserted into 4 Bloom filters
<Ullman88> type Book
<Ullman88>_type_Book <Ullman88>_type type_Book <Ullman88>_Boo
SPO SP PO SO
griffioen
SUM 2008 - October 2, 2008 15 / 24

54. Problem and context Method proposed Experimental results Conclusion
Graph parsing
Every triple of the graph is inserted into 4 Bloom filters
<Ullman88> type Book
<Ullman88>_type_Book <Ullman88>_type type_Book <Ullman88>_Boo
SPO SP PO SO
Three domains are defined
S = <Ullman88> b1 ullman
P = type label author _1 homepage
O = Book "Principles of ..." b1 ullman <http://...>
griffioen
SUM 2008 - October 2, 2008 15 / 24

55. Problem and context Method proposed Experimental results Conclusion
Graph parsing
Every triple of the graph is inserted into 4 Bloom filters
<Ullman88> type Book
<Ullman88>_type_Book <Ullman88>_type type_Book <Ullman88>_Boo
SPO SP PO SO
Three domains are defined
S = <Ullman88> b1 ullman
P = type label author _1 homepage
O = Book "Principles of ..." b1 ullman <http://...>
Each term is replaced by an integer (with a dictionary) griffioen
<Ullman88> → 46
SUM 2008 - October 2, 2008 15 / 24

56. Problem and context Method proposed Experimental results Conclusion
Evolutionary algorithm flowchart [Eiben2003]
Set of populations + Set of operators
griffioen
SUM 2008 - October 2, 2008 16 / 24

57. Problem and context Method proposed Experimental results Conclusion
Query parsing
Definition of the chromosome for the individuals
?publication1 ?publication2 ?title
griffioen
SUM 2008 - October 2, 2008 17 / 24

58. Problem and context Method proposed Experimental results Conclusion
Query parsing
Definition of the chromosome for the individuals
?publication1 ?publication2 ?title
Creation of constraints to verify
griffioen
SUM 2008 - October 2, 2008 17 / 24

59. Problem and context Method proposed Experimental results Conclusion
Query parsing
Definition of the chromosome for the individuals
?publication1 ?publication2 ?title
Creation of constraints to verify
Clause ?publication type Book .
bloom(spo |?publication1 type Book)
bloom(sp |?publication1 type)
bloom(po |type Book)
griffioen
SUM 2008 - October 2, 2008 17 / 24

60. Problem and context Method proposed Experimental results Conclusion
Query parsing
Definition of the chromosome for the individuals
?publication1 ?publication2 ?title
Creation of constraints to verify
Clause ?publication type Book .
bloom(spo |?publication1 type Book)
bloom(sp |?publication1 type)
bloom(po |type Book)
Clause ?publication label ?title .
bloom(spo |?publication2 label ?title)
bloom(sp |?publication2 label)
bloom(po |label ?title)
bloom(so |?publication2 ?title)
griffioen
SUM 2008 - October 2, 2008 17 / 24

61. Problem and context Method proposed Experimental results Conclusion
Query parsing
Definition of the chromosome for the individuals
?publication1 ?publication2 ?title
Creation of constraints to verify
Clause ?publication type Book .
bloom(spo |?publication1 type Book)
bloom(sp |?publication1 type)
bloom(po |type Book)
Clause ?publication label ?title .
bloom(spo |?publication2 label ?title)
bloom(sp |?publication2 label)
bloom(po |label ?title)
bloom(so |?publication2 ?title)
Equality constraint
equal(?publication1 ,?publication2 ) griffioen
SUM 2008 - October 2, 2008 17 / 24

62. Problem and context Method proposed Experimental results Conclusion
Query parsing
Definition of the chromosome for the individuals
?publication1 ?publication2 ?title
Removed
Creation of constraints to verify
because
Clause ?publication type Book .
always true
bloom(spo |?publication type Book)
1
bloom(sp |?publication1 type)
bloom(po |type Book)
Clause ?publication label ?title .
bloom(spo |?publication2 label ?title)
bloom(sp |?publication2 label)
bloom(po |label ?title)
bloom(so |?publication2 ?title)
Equality constraint
equal(?publication1 ,?publication2 ) griffioen
SUM 2008 - October 2, 2008 17 / 24

63. Problem and context Method proposed Experimental results Conclusion
Evaluation of a candidate solution
Solution is checked against all the constraints. If one is
satisfied,
A global reward w is won
Each variable used is equally rewarded
Rewards for : bloom(spo|?publication2 label
?title)
reward(solution) += w
w
reward(?publication1 ) += 2
reward(?title) += w
2
griffioen
SUM 2008 - October 2, 2008 18 / 24

64. Problem and context Method proposed Experimental results Conclusion
Creation of new individuals
Select two individuals and do a one point crossover
dblp:ullman <Ullman88> "Principles. . . " dblp:ullman <Ullman88> _:b1
<Ullman88> dblp:ullman _:b1 <Ullman88> dblp:ullman "Principles. . . "
Randomly pick a pivot point Swap the two parts
Mutate the least efficient variable
dblp:ullman <Ullman88> "Principles. . . "
0 3×w 2×w <Ullman88> <Ullman88> "Principles. . . "
Select the variable with lowest Assign a random new value
reward griffioen
SUM 2008 - October 2, 2008 19 / 24

65. Problem and context Method proposed Experimental results Conclusion
1 What’s the problem ?
Querying RDF datastores
Standard techniques
2 And Now for Something Completely Different
Guessing the solution instead
The way we do it
3 Does it work ?
Evolution of the quality
Some characteristics of this method
4 TODO list
griffioen
SUM 2008 - October 2, 2008 20 / 24

66. Problem and context Method proposed Experimental results Conclusion
Results on some (small) datasets
Database FOAF (15k triples) and DBLP (3M triples)
Query with, respectively, 4 and 11 different variables
Average result for 200 individuals and 500 generations
60 100
50
90
fitness value
fitness value
40
30 80
20
70
10
0 60
0 100 200 300 400 500 0 100 200 300 400 500
n-th generation n-th generation
Solutions with maximum reward (52) are found for FOAF griffioen
Not enough time for DBLP (max 319)
SUM 2008 - October 2, 2008 21 / 24

67. Problem and context Method proposed Experimental results Conclusion
Scalibility & speed
Low memory requirements
Only depends on the number of individuals and the size of
the Bloom filters
(a) parsing (b) querying
dataset memory dataset memory
FOAF 65 MB FOAF 15 MB
DBLP 230 MB DBLP 140 MB
Table: Average memory usage (mostly due to dictionary)
Computation can be distributed
Candidate solutions are independent
The dictionary can be based on a DHT griffioen
SUM 2008 - October 2, 2008 22 / 24

68. Problem and context Method proposed Experimental results Conclusion
1 What’s the problem ?
Querying RDF datastores
Standard techniques
2 And Now for Something Completely Different
Guessing the solution instead
The way we do it
3 Does it work ?
Evolution of the quality
Some characteristics of this method
4 TODO list
griffioen
SUM 2008 - October 2, 2008 23 / 24

69. Problem and context Method proposed Experimental results Conclusion
Status and future work
Current status
The search process can be slow to converge
Several parameters to tune (rewards, size of the population,
number of generations, . . . )
griffioen
SUM 2008 - October 2, 2008 24 / 24

70. Problem and context Method proposed Experimental results Conclusion
Status and future work
Current status
The search process can be slow to converge
Several parameters to tune (rewards, size of the population,
number of generations, . . . )
Current work
griffioen
SUM 2008 - October 2, 2008 24 / 24

71. Problem and context Method proposed Experimental results Conclusion
Status and future work
Current status
The search process can be slow to converge
Several parameters to tune (rewards, size of the population,
number of generations, . . . )
Current work
1 Improve benchmarking
Test with more queries and more datasets
Better study of the influence of the parameters
griffioen
SUM 2008 - October 2, 2008 24 / 24

72. Problem and context Method proposed Experimental results Conclusion
Status and future work
Current status
The search process can be slow to converge
Several parameters to tune (rewards, size of the population,
number of generations, . . . )
Current work
1 Improve benchmarking
Test with more queries and more datasets
Better study of the influence of the parameters
2 Improve evolution
Experiment different type of crossover and mutation
Implement dynamic valuations for the rewards
Improve early results on tabbu search approach
griffioen
SUM 2008 - October 2, 2008 24 / 24

73. Problem and context Method proposed Experimental results Conclusion
Status and future work
Current status
The search process can be slow to converge
Several parameters to tune (rewards, size of the population,
number of generations, . . . )
Current work
1 Improve benchmarking
Test with more queries and more datasets
Better study of the influence of the parameters
2 Improve evolution
Experiment different type of crossover and mutation
Implement dynamic valuations for the rewards
Improve early results on tabbu search approach
3 Test other, easy to parallelize and anytime, optimizer
Swarm based algorithm (PSO, ...) or an other EA griffioen
CSP solver
SUM 2008 - October 2, 2008 24 / 24