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1 Context-based Exploitation of Data Warehouses Yeow Wei Choong 1, Dominique Laurent 2, Arnaud Giacometti 3, Patrick Marcel 3, Elsa Negre 3, Nicolas Spyratos 4 1: HELP University College, Kuala Lumpur, Malaysia 2: ETIS, Université de Cergy-Pontoise, France 3: LI, Université François-Rabelais de Tours, France 4: LRI, Université Paris-Sud, France

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2 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

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3 Motivations and Intuitions (1) Problem: How to… Describe/exploit an analysis in an OLAP context: Launch/browse queries Organize/reuse/share an analysis Discover authorities, frequently asked queries Provide recommendations to the user

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4 Motivations and Intuitions (2) Motivating example: 2 user-analysts: Elsa Yeow Wei 2 data cubes: Tourism Agriculture 1 base of analyses sessions

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5 Motivations and Intuitions (3)

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6 Motivations and Intuitions (4) The Query over the Context Base

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7 Motivations and Intuitions (5) The Navigated Context

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8 Motivations and Intuitions (6) The Edited Context

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9 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

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10 Our Framework The Data Level: Based on the model proposed by Theodorakis, Analyti, Constantopoulos, Spyratos (ER’99, IS 2002) Uses the relational model under the logic programming perspective The System Level: Specifies how the data can be browsed and edited

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11 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

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12 The Data Level: Model (1) The relations: Objects: 3-ary relation objects(o id, a, v) objects(2,’topic’,’Transport,Year’) Contexts: Binary relation contexts(c id,o id ) contexts(1,2) References: 4-ary relation references(o id1,o id2,a, v) references(2,3,’refines’,’Transport’) 2 3

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13 The Data Level: Model (2) The Context Base (CB): Schema: Objects, contexts, references Instance: Finite set of facts Querying the CB: Datalog̚ under the stratified semantic to express recursion and relational division objects contexts references objects_a contexts_a references_a

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14 The Data Level: Language Example of Datalog̚ program: « Objects with topic dealing with Tourism but not with Borneo» objects_a(x,’topic’,z) <- objects(x,’topic’,z), substring(z, ‘Tourism’), ¬substring(z, ‘Borneo’) objects_a(x,s,t) <- objects(x,s,t), objects_a(x,’topic’,z) contexts_a(c,x) <- objects_a(x,s,t), contexts(c,x) references_a(x,x1,y1,z1) <- objects_a(x,s,t), references(x,x1,y1,z1)

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15 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

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16 The System Level: Model System = Base = instance of CB State =

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17 The System Level: Language (1) Navigation system operations Operators to change the navigated object Operator to change the set of contexts

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18 The System Level: Language (2) Edition system operations Operators to create a new object Operators to add a descriptor or a reference copyObject: Duplicates the navigated object in the edited context Example

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19 The System Level: Language (3) copyObject

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20 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

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21 Exploitation (1) Exploiting the descriptors: Descriptors associated with Objects: Topicadded and updated Codeby the user Launchedadded and updated Browsed by the system Result

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22 Exploitation (2) Exploiting the descriptors: Descriptors associated with Objects: Example of use: What queries have been launched more than 10 times: objects_a(o1,a,v) 10, objects(o1,a,v) contexts_a(c,o1) 10, contexts(c,o1) references_a(o1,o2,a,v) 10, references(o1,o2,a,v)

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23 Exploitation (3) Exploiting the descriptors: Descriptors associated with References: Intra-context references: Order of importance Query containment Query logs Inter-context references: Comes-from Copied-to

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24 Exploitation (4) Exploiting the references: Authority, Hub, Initiator:

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25 Exploitation (5) Recommendations: The idea: To exploit particular links between queries Example: What are the recommendations started from o1 ? o2o1o3a Comes-from o3b

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26 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

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27 Conclusion and Future work (1) Conclusion: A model for OLAP analysis: Sharing BrowsingOLAP queries Reusing Data Level: To organize OLAP queries System Level: To represent the interface and how the user can interact with the system

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28 Future work: Queries as first class citizen Extending the manipulation language and the navigation language Consider other recommendations Implementing our model Conclusion and Future work (2)

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29 Thanks for your attention

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30 Exploitation Recommendations: Example: What are the recommendations started from o1 ? ans(o2) <- objects(o2,_,_), references(o1,o2,’copied-to’,y) objects_a(o3,a,v) <- ans(o2), references(o2,o3,z,t), objects(o3,a,v) contexts_a(c,o3) <- objects_a(o3,a,v), contexts(c,o3) references_a(o3,o4,w,x) <- objects_a(o3,a,v), objects(o4,_,_), references(o3,o4,w,x) o2o1o3a Comes-from o3b

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