Exploring Personal CoreSpace For DataSpace Management

1. Exploring Personal CoreSpace For DataSpace Management Li Yukun and Xiaofeng Meng WAMDM Lab Renmin University of China

2. Outline • Introduction • CoreSpace Overview • CoreSpace Design • CoreSpace Implementation • Conclusion

3. Motivation • Background • With increasing of personal data set, PIM becomes a serious problem and a hot research issue; The current tools can not work well in some cases. Find a pdf file I downloaded from a web page and stored in a directory of D drive. Query Revisit a picture I developed for MDM2008one years ago.

4. Related work • Current solutions • Traditional tools • Folder explorer, Desktop Search • DataSpace Support Platforms (DSSPs) • Personal data integration (Xin Dong,etc.) • Association-based query (Salles MAV, etc.) • Data Resource Model • RSM, SLN (Hai Zhuge, etc.) • Our solution • Based on user features • Users play a key role • Revisit is an popular access style • Research focuses • Highlight the role of users • Produce an effective approach for exploring PDS

5. Problem Definition Classify Exploring Personal DataSpace Personal CoreSpace -Modeling user features-Exploring based on user features

6. Contributions • Propose CoreSpace Model • Divide the semantic links among PDS into two classes: • Objective Semantic Link(OSL) • Memory-based Semantic Link(MSL) • Describe Personal CoreSpace(PCS) based on Resource Space Model (RSM). • An ontology of Personal CoreSpace • Discover several types of meaningful MSLs • Design an ontology of PCS based on the MSLs • A facet-based search interface of PCS • Propose a method to translate the PCS ontology into a facet-based search interface. • Validate the effectiveness of our methods by implementing a prototype system.

7. Outline • Introduction • CoreSpace Overview • CoreSpace Design • CoreSpace Implement • Conclussion

8. Features of personal data • Features of personal data • Versatile, heterogeneous, personalized , complex, evolutionary • Features of personal data operations • Pay-Go Integration • Known-item relocation-- “revisit” • Multiple query methods • Simple interface

9. Resource Space Model • A resource space is a n-dimensional space • Axis :Xi is the name of an axis. Xi = (Ci1;Ci2; ...;Cin) represents an axis with its coordinates and the order between them. • Coordinate:C denotes the coordinate name in form of a noun or a noun phrase. • Point: determines one or a set of entities, we denote it as PCS(X1;X2; ...;Xn). • Data operation [1] H.Zhuge, Communities and Emerging Semantics in Semantic Link Network: Discovery and Learning, IEEE Transactions on Knowledge and Data Engineering, vol.21, no.6, 2009, pp. 785-799. [2] H. Zhuge. Resource space model, its design method and applications. The Journal of Systems and Software 72 (2004) 71-81. [3] H.Zhuge, The Web Resource Space Model, Springer, 2008.

10. Personal CoreSpace Model • Personal DataSpace • Data item • Attribute • Owner • Relationship • Personal CoreSpace • A n-dimensional space • Axis : Attributes of personal data items. • Coordinate: Values of a certain attribute, which can be a tree structure. • Point: A personal item or a set of personal items.

11. Outline • Introduction • CoreSpace Overview • CoreSpace Design • CoreSpace Implementation • Conclussion

12. Personal CoreSpace Ontology • Two type of attributes • Natural attributes • Name, Type ,Access time, Directory, Size, Source • User-based attributes • Access frequency, access type, related task

13. Personal CoreSpace Ontology • Type: • {Email, Web pages, Picture, Documents,…} • Access time • {”Today”,”Yesterday”,”Last week”,”Last month”,”Last year”,”One year ago”} • Directory • A Tree structure • Size • {(0,10K]; (10K,100K]; (100K,1M]; (1M,10M]; (10M,-)} • Sources • {Self-developed, Cloned} • Access frequency • {(1,5]; (6,15]; (16,50]; (50,-]} • Access type: • {Read-only, Modified} • Related tasks • A personal task set

14. Outline • Introduction • CoreSpace Overview • CoreSpace Design • CoreSpace Implementation • Conclussion

15. CoreSpace Implementation • System Framework • User behavior monitor • Storage agent • Item identify agent • Query processor • Features • PayGo evolution • From CoreSpace to facet search • Extendability

16. From CoreSpace to facet search • Method • Take each coordinate Xi as a facet Fi, and take its coordinates as the options of facet Fi. • Based on the hierarchical structure of PCS, we can easily construct a facet-based search interface. • Facet-based query logical • Let X and Y’ be two selected nodes of facet tree, and they can be regarded as two conditional expressions. Our method is detailed as below. • If X is parent of Y, it means X and Y = Y; • If X is brother of Y, it means X or Y; • If X and Yare neither parent relation nor brother relationship, it means X or Y.

17. An example of query algebra • The red nodes represents those options selected by user • According to the rules we can get the logical expression R = {Xi | (Xi. type = JPG∨ Xi.type =VSD) ∧ Xi. place = ”D : \Picture”}

18. Implementation

19. Outline • Introduction • CoreSpace Overview • CoreSpace Design • CoreSpace Implementation • Conclussion

20. Conclusion • This is just a preliminary work • Propose a CoreSpace model • Propose a method to explore PDS based on CoreSpace • Future work • Try to discover more rules of user memory • Enrich the ontology of PCS

21. Thanks