An Evolutionary Perspective on Approximate RDF Query Answering

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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.

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An Evolutionary Perspective on Approximate RDF Query Answering

  1. 1. An Evolutionary Perspective on Approximate RDF Query AnsweringChristophe Guéret, Eyal Oren, Stefan Schlobach, Frank van Harmelen and Martijn Schut Vrije Universiteit, Amsterdam
  2. 2. Problem and context Method proposed Experimental results Conclusion The next 30 minutes in 4 points... RDF griffioenSUM 2008 - October 2, 2008 2 / 24
  3. 3. Problem and context Method proposed Experimental results Conclusion The next 30 minutes in 4 points... RDF Data on the Web griffioenSUM 2008 - October 2, 2008 2 / 24
  4. 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! griffioenSUM 2008 - October 2, 2008 2 / 24
  5. 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 griffioenSUM 2008 - October 2, 2008 2 / 24
  6. 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 griffioenSUM 2008 - October 2, 2008 2 / 24
  7. 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 griffioenSUM 2008 - October 2, 2008 2 / 24
  8. 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 griffioenSUM 2008 - October 2, 2008 2 / 24
  9. 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 griffioenSUM 2008 - October 2, 2008 2 / 24
  10. 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 griffioenSUM 2008 - October 2, 2008 2 / 24
  11. 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 griffioenSUM 2008 - October 2, 2008 2 / 24
  12. 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 griffioenSUM 2008 - October 2, 2008 2 / 24
  13. 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 griffioenSUM 2008 - October 2, 2008 3 / 24
  14. 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 griffioenSUM 2008 - October 2, 2008 4 / 24
  15. 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 SystemsSUM 2008 - October 2, 2008 5 / 24
  16. 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. 17. Problem and context Method proposed Experimental results Conclusion Standard techniques Standard approach : griffioenSUM 2008 - October 2, 2008 7 / 24
  18. 18. Problem and context Method proposed Experimental results Conclusion Standard techniques Standard approach : 1 Find all the possible results for ?publication type Book griffioenSUM 2008 - October 2, 2008 7 / 24
  19. 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> griffioenSUM 2008 - October 2, 2008 7 / 24
  20. 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 griffioenSUM 2008 - October 2, 2008 7 / 24
  21. 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 ..." griffioenSUM 2008 - October 2, 2008 7 / 24
  22. 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 griffioenSUM 2008 - October 2, 2008 7 / 24
  23. 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 ..." griffioenSUM 2008 - October 2, 2008 7 / 24
  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 griffioenSUM 2008 - October 2, 2008 7 / 24
  25. 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 griffioenSUM 2008 - October 2, 2008 8 / 24
  26. 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 griffioenSUM 2008 - October 2, 2008 8 / 24
  27. 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 griffioenSUM 2008 - October 2, 2008 8 / 24
  28. 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 querySUM 2008 - October 2, 2008 8 / 24
  29. 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 griffioenSUM 2008 - October 2, 2008 9 / 24
  30. 30. Problem and context Method proposed Experimental results Conclusion Approach “I’m Feeling Lucky” approach : griffioenSUM 2008 - October 2, 2008 10 / 24
  31. 31. Problem and context Method proposed Experimental results Conclusion Approach “I’m Feeling Lucky” approach : 1 Assign some random values to the variables griffioenSUM 2008 - October 2, 2008 10 / 24
  32. 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 griffioenSUM 2008 - October 2, 2008 10 / 24
  33. 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 griffioenSUM 2008 - October 2, 2008 10 / 24
  34. 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 griffioenSUM 2008 - October 2, 2008 10 / 24
  35. 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 griffioenSUM 2008 - October 2, 2008 10 / 24
  36. 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) griffioenSUM 2008 - October 2, 2008 10 / 24
  37. 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 griffioenSUM 2008 - October 2, 2008 10 / 24
  38. 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 griffioenSUM 2008 - October 2, 2008 10 / 24
  39. 39. Problem and context Method proposed Experimental results Conclusion Our choices Need to pay attention to two aspects griffioenSUM 2008 - October 2, 2008 11 / 24
  40. 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 griffioenSUM 2008 - October 2, 2008 11 / 24
  41. 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 griffioenSUM 2008 - October 2, 2008 11 / 24
  42. 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 griffioenSUM 2008 - October 2, 2008 11 / 24
  43. 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 griffioenSUM 2008 - October 2, 2008 12 / 24
  44. 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 )kSUM 2008 - October 2, 2008 13 / 24
  45. 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 ..."”) ... griffioenSUM 2008 - October 2, 2008 14 / 24
  46. 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 griffioenSUM 2008 - October 2, 2008 14 / 24
  47. 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 . . . griffioenSUM 2008 - October 2, 2008 14 / 24
  48. 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 ?titleSUM 2008 - October 2, 2008 14 / 24
  49. 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 griffioenSUM 2008 - October 2, 2008 15 / 24
  50. 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 griffioenSUM 2008 - October 2, 2008 15 / 24
  51. 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 griffioenSUM 2008 - October 2, 2008 15 / 24
  52. 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 griffioenSUM 2008 - October 2, 2008 15 / 24
  53. 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 griffioenSUM 2008 - October 2, 2008 15 / 24
  54. 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://...> griffioenSUM 2008 - October 2, 2008 15 / 24
  55. 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> → 46SUM 2008 - October 2, 2008 15 / 24
  56. 56. Problem and context Method proposed Experimental results Conclusion Evolutionary algorithm flowchart [Eiben2003] Set of populations + Set of operators griffioenSUM 2008 - October 2, 2008 16 / 24
  57. 57. Problem and context Method proposed Experimental results Conclusion Query parsing Definition of the chromosome for the individuals ?publication1 ?publication2 ?title griffioenSUM 2008 - October 2, 2008 17 / 24
  58. 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 griffioenSUM 2008 - October 2, 2008 17 / 24
  59. 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) griffioenSUM 2008 - October 2, 2008 17 / 24
  60. 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) griffioenSUM 2008 - October 2, 2008 17 / 24
  61. 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 ) griffioenSUM 2008 - October 2, 2008 17 / 24
  62. 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 ) griffioenSUM 2008 - October 2, 2008 17 / 24
  63. 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 griffioenSUM 2008 - October 2, 2008 18 / 24
  64. 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 griffioenSUM 2008 - October 2, 2008 19 / 24
  65. 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 griffioenSUM 2008 - October 2, 2008 20 / 24
  66. 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 90fitness 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. 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 griffioenSUM 2008 - October 2, 2008 22 / 24
  68. 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 griffioenSUM 2008 - October 2, 2008 23 / 24
  69. 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, . . . ) griffioenSUM 2008 - October 2, 2008 24 / 24
  70. 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 griffioenSUM 2008 - October 2, 2008 24 / 24
  71. 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 griffioenSUM 2008 - October 2, 2008 24 / 24
  72. 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 griffioenSUM 2008 - October 2, 2008 24 / 24
  73. 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 solverSUM 2008 - October 2, 2008 24 / 24

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