exploring personal corespace for dataspace management li yukun and xiaofeng meng wamdm lab renmin...

Exploring Personal CoreSpace For DataSpace Management

Li Yukun and Xiaofeng Meng

WAMDM LabRenmin University of China

Outline

Introduction CoreSpace Overview CoreSpace Design CoreSpace Implementation Conclusion

Motivation

Query

Find a pdf file I downloaded from a web page and stored in a directory of D drive.

Revisit a picture I developed for MDM2008 one years

ago.

BackgroundWith 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.

BackgroundWith 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.

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

Problem Definition

Personal DataSpace Personal CoreSpace

Classify Exploring

-Modeling user features-Exploring based on user features

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.

Outline

Introduction CoreSpace Overview CoreSpace Design CoreSpace Implement Conclussion

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

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 LinkNetwork: Discovery and Learning, IEEE Transactions on Knowledge andData 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.

[1] H.Zhuge, Communities and Emerging Semantics in Semantic LinkNetwork: Discovery and Learning, IEEE Transactions on Knowledge andData 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.

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.

Outline

Introduction CoreSpace Overview CoreSpace Design CoreSpace Implementation Conclussion

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

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

Personal CoreSpace Ontology

Outline


CoreSpace Implementation

System Framework User behavior monitor Storage agent Item identify agent Query processor

Features PayGo evolution From CoreSpace to facet search Extendability

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 Y are neither parent relation nor brother

relationship, it means X or Y.

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”}

Implementation

Outline


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

Thanks