TAILS: COBWEB 1 [1]

TAILS: COBWEB1[1]

Online Digital Learning Environment for Conceptual Clustering

ⱡ This material is based upon work supported by the National Science Foundation under Course, Curriculum, and Laboratory Improvement (CCLI) Grant No. 0942454. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

CMSI 401 COBWEB TAILS Enhancement 2

Meet The Team● Carlos

o Senior CMSI Major, 401 Project● Liyang

o MSEE Graduate Student● Poulomi

o Graduate Student● Michael

o EE Senior working with TAILS● Miguel

o EE Senior working with TAILS

Stephanie August

Mention Liyang Hao, MSEE grad student responsible for developing the teaching materials to accompany the COBWEB application.

Michael Fraser

Each member can add to their details if desired


Motivation● Chemistry, Biology, Physics

○ all have lectures and labs■ lectures provide concepts■ labs provide hands-on and visual experience

● Artificial Intelligence○ Traditionally taught with large arrays of algorithms at a

conceptual level■ little hands-on experience and low levels of coding

○ Or one to two algorithms taught with large projects


Project Overview● TAILS Goal

○ Develop complete applications with embedded algorithms■ Will allow students to study and experiment with the

application■ Will allow students to implement and enhance AI aspects

of the application● Module Goal

○ Develop a complete application depicting the COBWEB Conceptual Clustering algorithm

COBWEB Algorithm• What is COBWEB• How does COBWEB work


What is the COBWEB Algorithm?• Unsupervised

○ No desired output for the input data• Incremental

○ Data stream• Conceptual

○ Concept for each cluster• Polythetic

○ Evaluation on all of the observation's attribute-values rather than a single one

Michael Fraser

For this slide and the next few, I took Liyang's powerpoint slides and placed them up here roughly. When her slides are finalized I can copy them over in a cleaner way


What is the COBWEB Algorithm?• Two tasks• Unsupervised

o No desired output for the input data

• Incrementalo Data stream

• Conceptualo Concept for each cluster

Discover the appropriate cluster for each input

Discover the concept for each cluster


How COBWEB Works

Design


Requirements1. The system shall initialize depending on the user inputs

2. The system shall allow the user with options to add feature vectors to the tree

3. The system shall display the results such that the user can understand working of the algorithm

4. The system shall have a feature of backtracking to previous working stages

5. The systems shall provide the user with an option to view diverse set of representations of the clustered tree generated.

6. The system shall have project documentation that will be maintained by assigned team member

7. The system shall be verified using test cases developed by assigned team member


Design• Functional View - focuses on the functional

requirements. No specific implementation details

• Behavioral View - focuses on the behavior of working of the system.

• Structural View - focuses on the structure of intended implementation


Use Case Diagram (previous)


Use Case Diagram (revised)


State Chart Diagram (Behavioral View)


Package Diagram (Old Structure)


Package Diagram (New Structure)


Project Timeline


Responsibilities

Implementation


Clustering User Interface DesignFrom previous to Current

Designed and implemented by Robert “Quin” Thames, 2012


Implement an Intuitive and Responsive UI• Adapt the application to the

TAILS project

• Make it possible to port the application use across devices

• Implement new functionality

• Create an overall more elegant look


Project Justification• Developing a complex UI and back end

functionality has enhanced the abilities acquired from:- Interaction Design

- Algorithms

- Graphics

Vector Initialization GUI



Cluster GUI


Methods of Input• For adding attributes and values

• For adding nodes to tree


Action Log


Undo• Unable to go back to previous state• Able to go back by up to three phases• To remake a tree as previously made, need to

re-input each node- Algorithm produces same tree if nodes are input in same

order- Takes longer to produce larger trees


Undo• Nodes are added or

removed in a group.• Add 10 random undo

causes the same 10 to disappear


Hover Text• Tree statistics used to appear only when a node

was clicked on- Would appear as an alert dialog requiring the user to close

it

• A text box will now appear below the node when the user hovers over it


Hover Text


Challenges• Working with Raphael.js• CSS Media Queries• Improving with the previous version of the

cluster• Parsing File Paste Input


Demonstration!Carlos and Miguel will now show a visual demonstration.


Questions? Concerns?


AcknowledgementsWe are grateful to Quin Thames for implementing the original version of the COBWEB algorithm. While we redesign the user interface, Quin’s implementation of the the category utility function remains at the heart of the module.

We are also grateful to Doug Fisher for publishing such a fascinating clustering algorithm.[1] Fisher, Douglas (1987).

"Knowledge acquisition via incremental conceptual clustering". Machine Learning 2 (2): 139–172.doi:10.1007/BF00114265.

http://www.springerlink.com/content/qj16212n7537n6p3/fulltext.pdf





http://en.wikipedia.org/wiki/Digital_object_identifier

http://dx.doi.org/10.1007/BF00114265

TAILS: COBWEB 1 [1]

Documents

Transcript of TAILS: COBWEB 1 [1]