Markup and Validation Agents in Vijjana – A Pragmatic model for Self-Organizing, Collaborative, Domain-Centric Knowledge Networks

S. Devalapalli, R. Reddy, L. Wang, S. ReddySIPLab, Department of Computer Science & Electrical EngineeringWest Virginia University,

Morgantown, WV 26506, USA

Presentation Outline

Motivation Vijjana Architecture Keyword Extraction Vijjana Browser Extensions Markup and Validation Agents Conclusion and Future Work

Motivation-Knowledge acquisition Process People gain knowledge

through thousands of ways

People accumulate knowledge in a systematic way

People form their own knowledge network

A large knowledge network are formed by collaboration

Workstations

Agent

Context AwareWorld Aware

Selft Aware

Motivation-Methodology in Knowledge acquisition Management Science on

Knowledge organization Machine facilitates people

to gather knowledge Collaborative channel is

needed in communication Knowledge network

publication

Vijjana

Defined as a Pragmatic model for Collaborative, Self-Organizing, Domain-Centric Knowledge Networks

A Semantic web A portal for collaboration A discussion forum And much more!

The Vijjana Model

Vijjana-X = {J, T, R| dA, oA, cA, vA, sA, rA}; where X = the domain name, J= the collection of JAN’s in the Vijjana-X, T = the Taxonomy OR pattern set used for classification of

JAN’s, R= the domain specific relations; dA = the discovery agent which finds relevant JAN’s, oA = the organizing agent which interlinks the JAN’s based

on R, cA = the consistency/completeness agent, vA = the visualization agent, sA = the search agent, rA = the rating agent.

Vijjana Architecture- A standard way to exploit the knowledge Find Organize Update Maintain Consistency and Completeness Distill Tools for Visualization Present on demand contextually relevant

knowledge!

Vijjana Client Interface Architecture

Vijjana Architecture-Knowledge Representation Semantic Networks Logic Frames

graph views of the Vijjana-Computer Science network

How useful is Vijjana

No unproductive browsing sessions anymore Search by concept, not by keywords Semantic visualization Social networking Receive alerts on topics of interest Combine resources on the Web and a user’s local

machine to form a “User JAN Space” Integrate and share “JAN Spaces” among users

Vijjana Network

Vijjana Markup Agents--Web Interface Prototype Browse JAN’s with in the user interest. Comment on the JAN, for discussion . Rate the JAN, to get best & useful content. Visualization of Taxonomy, for addition of

JAN’s manually. Visualization of Knowledge Domains for easy

navigation and User friendly search.

Keyword Extraction

Effectively summarize long documents Provide a context to the document Very valuable in web advertising Vijjana tags JANs with keywords describing them Examples of keyword assignment and usage include

youtube, Gmail, search engines etc

Keyword extraction in Vijjana

KEA algorithm used Simple and effective algorithm based on the

Bayesian model Domain specific keyword extraction Less overhead in training needed Available at http://www.nzdl.org/kea

Vijjana Browser Extensions

Firefox browser required Extensions are provided as toolbar buttons and

menus Extensions must be downloaded and installed on the

user’s browser Current extensions provide navigation to Vijjana

homepage, the Markup feature and Validation of JANs in the database

Vijjana Extensions in Firefox

Markup Process

Part of building up the database Similar to, but more involved than bookmarking Process of adding meta-data to a JAN Pages added to the database simply by clicking the

“Markup” button in the browser extension Invokes the Organizing Agent which adds a JAN to

the database

Markup Example

Markup Example (contd.)

Markup Process

Validation Agent

There may be hundreds or thousands of JANs in a user’s space

JANs are usually URLs or documents that might relocate or cease to exist

JANs must be validated (manually or automatically) The visualization must reflect most recent state of the

JAN

Validation Agent

Validation can be time and memory intensive task Time taken to validate is proportional to the number

of JANs in a user’s space Best carried out as an overnight operation

Validation Process Flow

Validation Confirmation

Database view before Validate process

Database view after Validation

Conclusion

A Firefox browser extension with options to navigate to Vijjana Homepage, Markup the current page and validate the user’s JANs has been developed

The KEA model was trained using a set of 24 documents pertaining to various technical domains and the results have been good

Future Work

A heuristic based key extraction algorithm called VKE is under evaluating

Automated periodic JAN “Validator” which runs as clients work instead of server work to manage load balance.

A series security mechanism should be applied for protecting privacy issue.

References

1. Vijjana – A Pragmatic model for Collaborative, Self-Organizing, Domain-Centric Knowledge Networks - Reddy, Dr. Ramana. Morgantown : IKE08, 2008.

2. KEA: Practical Automatic Key phrase extraction - Witten I.H., Paynter G.W., Frank

3. The KEA project - http://www.nzdl.org/Kea/

4. Mozilla Developer Center – Building an extension, http://developer.mozilla.org/en/docs/Building_an_Extension

5. Twine – Radar Networks Inc., http://www.twine.com/

6. Del.icio.us social bookmarking - http://del.icio.us/

Questions?