Programming Project

CSE 335/435 - Intelligent Decision Support Systems - Fall 2006

Authors: Fabiana Prabhakar and

Shruti Bhandari

1) Description of the Project

The “Tour Planning Help System” is an Interactive CBR system for a tour planning domain. It essentially helps a user to decide a trip location depending on his personal preferences.

The user is able to choose pre-defined values among a list of attributes in order to create a new problem. The system will analyze this problem and show the cases in the case base order by its similarity to the problem.

The information gain metric provides the user extra information about the cases and can be very helpful during the attributes values selection.

The user can perform the following actions using the “Tour Planning Help System”:

§ read cases and facts files;

§ assign/change values to attributes;

§ see a case in detail;

§ check the information gain values;

§ enter weights for attributes;

§ enter a parameter for matches/mismatches.

2) The Interface

2.1) Main Window

2.2) Settings Window

2.3) Facts Window

2.4) Cases Window

3) Formulae

3.1) Information Gain

Remainder(A) = p(A,1) I(p1/(p1+ n1), n1/(p1+ n1)) +

p(A,2) I(p2/(p2+ n2), n2/(p2+ n2)) +…+

p(A,v) I(pv/(pv+ nv), nv/(pv+ nv))

Gain(A) = I(p/p+n,n/p+n) – Remainder(A)

3.2) Weighted Hamming distance with a parameter

§ Matches

m = equal(X₁,Y₁) * α_{1 +} equal(X₂,Y₂) * α_{2 + ... +} equal(X_v,Y_v) * α_v;

§ Mismatches

x = diff(X₁,Y₁) * α_{1 +} diff(X₂,Y₂) * α_{2 + ... +} diff(X_v,Y_v) * α_v;

§ Hamming Distance

H_W(X,Y) = 1- ((alpha*m)/((alpha*m) + ((1-alpha)*x)));

equal(A,B) { if (A==B) return 1;

else return 0; }

diff(A,B) { if (A!=B) return 1;

else return 0; }

§ α1 + α2 + … + αv = 1

§ alpha is the weight of matches

4) Initial Setup and Execution Guideline

4.1) Known Cases file – caseBase2.xml

name	# of days	kind	religion	Month	climate	International	maximum_expense	solution
x1	>2 <5	family		Mar - Aug	hot	no	<1000	Rocky Mountain National Park, Colorado, US
x2	>2 <5	family		Sep - Feb	cold	no	<1000	Rocky Mountain National Park, Colorado, US
x3	>2 <5	family		Sep - Feb	cold	no	>1000 <2000	Disneyland, Orlando, US
x4	>2 <5	family		Mar - Aug	hot	no	>1000 <2000	Disneyland, Orlando, US
x5	>7	romantic		Mar - Aug	hot	no	>3000	Napa Valley, California, US
x6	>7	romantic		Sep - Feb	cold	no	>3000	Napa Valley, California, US
x7	>5 <7	romantic		Mar - Aug	hot	no	>1000 <2000	Napa Valley, California, US
x8	>5 <7	romantic		Sep - Feb	cold	no	>3000	Napa Valley, California, US
x9	>2 <5	urban		Mar - Aug	hot	no	<1000	San Francisco, California, US
x10	>2 <5	urban		Sep - Feb	cold	no	<1000	San Francisco, California, US
x11	>5 <7	urban		Mar - Aug	hot	no	>1000 <2000	San Francisco, California, US
x12	>5 <7	urban		Sep - Feb	cold	no	>1000 <2000	San Francisco, California, US
x13	>2 <5	urban		Mar - Aug	hot	no	<1000	New York, New York, US
x14	>2 <5	urban		Sep - Feb	cold	no	<1000	New York, New York, US
x15	>5 <7	urban		Mar - Aug	hot	no	>1000 <2000	New York, New York, US
x16	>5 <7	urban		Sep - Feb	cold	no	>1000 <2000	New York, New York, US
x17	>7	religious	catholic	Mar - Aug	hot	yes	>3000	Italy
x18	>7	religious	catholic	Sep - Feb	cold	yes	>3000	Italy
x19	>7	religious	catholic	Mar - Aug	hot	yes	>3000	Israel
x20	>7	religious	catholic	Sep - Feb	cold	yes	>3000	Israel
x21	>7	religious	jewish	Mar - Aug	hot	yes	>3000	Israel
x22	>7	religious	jewish	Sep - Feb	cold	yes	>3000	Israel
x23	>7	religious	hindu	Mar - Aug	hot	yes	>3000	India
x24	>7	religious	hindu	Sep - Feb	cold	yes	>3000	India