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D7.pdf

1.0

A.Moreno, A

C.Vicient,

Co-ordinato

1005

A. Valls, S.M

L.Marin, F.M

or

Martinez,

Mata

31/07/2

Antonio

2013

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version1.0

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n dat31.

history

te .July.2013

reasonEvaluat

n of modiftion of recom

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1

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Table of

1  Intro

2  Eva

3  Bibl

up 2010

f Conten

oduction

luation of t

liography

ts

the recomm

mendation

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4 

6 

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up 2010

ction

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tudy: a perso

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chnique expl

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deployment

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places

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mmendation

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mmendations

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in the third

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algorithm fo

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with the centr

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mpute the re

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user. The cit

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on the Touri

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semblance o

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accuracy of

- 5

ecommendat

ties consider

new procedu

finition of a

ist ontology)

e clusters, an

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nt, is that th

tional cost o

of each destin

nd accuracy

the recomm

5 -

tion of

red by

ure for

multi-

). The

nd the

thesis,

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of the

nation

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mender

2

that w

with t

differ

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order

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relate

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tify the simi

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nature

sports

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Cycling

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up 2010

tion of t

ection the rec

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ons (from a s

to a very gen

ally quantify

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larity betwee

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attribute (he

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t in 5 of the

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the reco

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tem.

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of touristic

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of profile pre

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attributes, bu

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c places (A

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preferences f

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- 6

mpared with

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commendati

satisfied by

st of the citie

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able to objec

m the list of

semantic attr

rts, Other s

eums, Land

fferent profile

selected onl

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al one. Not o

find in most

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re that

ctively

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fferent sizes.

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user preferen

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m to user 4

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are highlight

up 2010

dation of the

an ideal re

ting, in ascen

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behaviour o

s of cities to

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mantic attribu

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ecommender

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mmended cit

distances to

are normalise

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nce to the pr

o the user's pr

uracy of the

dation previ

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fect precisio

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the ratio betw

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ties. The rec

otal number

f precision a

ample, table

4. For each r

and F1 value

ted in the tab

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commendati

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e first city in

of our syste

be recomme

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utes (see Deli

we consider a

r system, a

for details of

the user profi

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best (1, 2 or

ties is determ

o determine

ed with resp

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rofile is lowe

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recommenda

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F1 scores of

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of cities wh

and recall.

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ranking of r

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a profile qu

iverable 4). N

a profile as a

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preferences

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if a city sh

pect to the m

can be 1, 2 o

er than the s

ations can b

ibed. To do

f the recomm

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stics of each

mber of corr

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ystem is the

hich the syst

4 show the n

recommenda

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st of cities in

g of cities a

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e considered

0, 15 20, 25 a

uantifies the

Notice that,

a city to use w

ssing step a

tion) and cla

red with the

of the user.

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heir distance

hould be reco

maximum dis

or 3 clusters)

specified thre

be computed

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mender system

ould require a

h of the 150

ect recomme

g n recomm

number of

tem should h

number of re

ations, the ta

ster relative

ng the results

this recomm

n function of

according to

e the first rec

d a number

and 30). The

distance bet

since a profi

with this dist

applies the

assifies 150 c

10 centroids

The final re

cities to the

to the profi

ommended (

tance betwe

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eshold, whic

by compari

[1], we ha

m. The ideal

a lengthy com

0 cities. The

endations (th

mendations) a

correctly rec

have recomm

ecommendat

ables show t

distances. Th

- 7

s obtained b

mendation ca

f its distance

o this profile

commendati

of scenarios

e distance fun

tween cities

file is defined

tance functio

adapted k-m

cities in 10 c

s to find out

ecommendat

e profile. The

file. We eva

(from 0.1 to

een the profil

ecommended

ch means tha

ing them wi

ave compute

recommend

mparison be

e precision o

hose that app

and the numb

commended

mended. F1

tions made b

the correspo

The F1 values

7 -

by our

an be

to the

e. The

on. In

s with

nction

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d with

on.

means

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tion is

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luated

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le and

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at it is

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dations

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of the

pear in

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cities

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by our

onding

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Cluste#tci

5 10 15 20 25 30

precisi

in the

taken i

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precisi

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into ac

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precisi

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into ac

The a

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ITAKA Grou

rs:1 Dist: 0,1r Rec. P

1 0,2 2 0,4 4 0,8 5 1,0 5 1,0 5 1,0

Table 1. Nu

ion (P), recall (

ideal recomme

into account for

rs:2 Dist: 0,1r Rec. P

4 0,5 8 1,0 8 1,0 8 1,0 8 1,0 8 1,0

Table 2. Nu

ion (P), recall (

ideal recomme

ccount for the re

rs:3 Dist: 0,1r Rec. P

4 0,4 9 1,0 9 1,0 9 1,0 9 1,0 9 1,0

Table 3. Nu

ion (P), recall (

ideal recomme

ccount for the re

analysis of th

5 (note that F

4). These fou

the recall (wh

list of recom

ts obtained c

onsidered, th

s of each gra

recommend

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spond to th

mmendations

up 2010

#tcr 5 R F1

20 0,20 0,20 40 0,20 0,27 80 0,27 0,40 00 0,25 0,40 00 0,20 0,33 00 0,17 0,29

umber of recom

(R), F1 and tota

endation (#tcir)

r the recommen

#tcr 8 R F1

50 0,80 0,62 00 0,80 0,89 00 0,53 0,70 00 0,40 0,57 00 0,32 0,48 00 0,27 0,42

umber of recom

(R), F1 and tota

endation (#tcir)

ecommendation

#tcr 9 R F1

44 0,80 0,57 00 0,90 0,95 00 0,60 0,75 00 0,45 0,62 00 0,36 0,53 00 0,30 0,46

umber of recom

(R), F1 and tota

endation (#tcir)

ecommendation

he accuracy o

Figure 5 visu

ur figures sh

hich are obta

mmendations

considering 1

he bigger is t

aphic represe

ded (from 0.1

d cities (see

he results o

s.

Dist: 0,2 #Rec. P R

1 0,08 02 0,17 04 0,33 05 0,42 05 0,42 07 0,58 0

mmended cities

al number of ci

) for different

ndation.

Dist: 0,2 #Rec. P R

4 0,22 08 0,44 0

12 0,67 016 0,89 018 1,00 018 1,00 0

mmended cities

al number of ci

for different d

n.

Dist: 0,2 #Rec. P R

4 0,20 09 0,45 0

13 0,65 018 0,90 020 1,00 020 1,00 0

mmended cities

al number of ci

for different d

n.

of the recom

ualizes the re

how the valu

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s for each use

1, 2 or 3 clus

the number o

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to 0.5); thus

also tables

obtained for

#tcr 12 DisR F1 Rec0,20 0,12 10,20 0,18 20,27 0,30 40,25 0,31 50,20 0,27 50,23 0,33 7

s (Rec.) made

ities recommen

distance values

#tcr 18 DisR F1 Rec0,80 0,35 40,80 0,57 80,80 0,73 120,80 0,84 160,72 0,84 180,60 0,75 21

s (Rec.) made

ities recommen

distance values

#tcr 20 DisR F1 Rec0,80 0,32 40,90 0,60 90,87 0,74 130,90 0,90 180,80 0,89 210,67 0,80 24

s (Rec.) made

ities recommen

distance values

mmendations

esults for the

ue of F1, wh

mparing the

er). Each of

sters in the re

of recommen

ximum relativ

s, the bigger

s 2 to 4). F

an expecte

t: 0,3 #tcrc. P R

0,05 0,200,11 0,200,21 0,270,26 0,250,26 0,200,37 0,23

by our system

nded (#tcr) com

s used (Dist.).

t: 0,3 #tcrc. P R

0,12 0,800,24 0,80

2 0,36 0,806 0,48 0,808 0,55 0,72

0,64 0,70

by our system

nded (#tcr) com

used (Dist.). In

t: 0,3 #tcrc. P R

0,11 0,800,25 0,90

3 0,36 0,878 0,50 0,90

0,58 0,844 0,67 0,80

by our system

nded (#tcr) com

used (Dist.). In

made to the

e last user, w

ich is the ha

recommend

the figures h

ecommendat

nded cities, a

ve distance to

the distance

Finally, each

ed number o

19 Dist: 0,F1 Rec. P0,08 1 0,0,14 2 0,0,24 4 0,0,26 5 0,0,23 5 0,0,29 7 0,

to user 4. The

mpared with the

In this test, on

33 Dist: 0,F1 Rec. P0,21 4 0,0,37 8 0,0,50 12 0,0,60 16 0,0,62 18 0,0,67 21 0,

to user 4. The

mpared with the

n this test, 2 clu

36 Dist: 0,F1 Rec. P0,20 4 0,0,39 9 0,0,51 13 0,0,64 18 0,0,69 21 0,0,73 24 0,

to user 4. The

mpared with the

n this test, 3 clu

four users is

hich are deta

armonic mea

ations of the

has 3 graphic

tion process

as shown in t

o the profile

e, the larger w

h graphic ha

of 5, 10, 1

- 8

,4 #tcr 22 P R F1

,05 0,20 0,07,09 0,20 0,13,18 0,27 0,22,23 0,25 0,24,23 0,20 0,21,32 0,23 0,27

e table also sho

total number o

nly 1 cluster ha

,4 #tcr 51 P R F1

,08 0,80 0,14,16 0,80 0,26,24 0,80 0,36,31 0,80 0,45,35 0,72 0,47,41 0,70 0,52

e table also sho

total number o

usters have bee

,4 #tcr 54 P R F1

,07 0,80 0,14,17 0,90 0,28,24 0,87 0,38,33 0,90 0,49,39 0,84 0,53,44 0,80 0,57

e table also sho

total number o

usters have bee

s shown in F

ailed in table

an of the pre

e systems wi

cs, which sho

(the more cl

tables 2 to 4

allowed for

will be the nu

as 6 lines,

15, 20, 25

8 -

Dist: 0,5 Rec. P

7 1 0,053 2 0,092 4 0,184 5 0,231 5 0,237 7 0,32

ows the

of cities

as been

Dist: 0,5 Rec. P

4 4 0,066 8 0,136 12 0,195 16 0,267 18 0,292 21 0,34

ows the

of cities

n taken

Dist: 0,5 Rec. P

4 4 0,068 9 0,148 13 0,209 18 0,273 21 0,327 24 0,36

ows the

of cities

n taken

igures

es 2, 3

cision

ith the

ow the

lusters

). The

a city

umber

which

or 30

#tcr 22 R F1 0,20 0,070,20 0,130,27 0,220,25 0,240,20 0,210,23 0,27

#tcr 62 R F1 0,80 0,120,80 0,220,80 0,310,80 0,390,72 0,410,70 0,46

#tcr 66 R F1 0,80 0,110,90 0,240,87 0,320,90 0,420,84 0,460,80 0,50

F

F

ITAKA Grou

Figure 2. F1 sc

Figure 3. F1 sc

up 2010

core results of

core results of

f the recomme

f the recomme

endation for th

endation for th

he profile 1

he profile 2

- 99 -

F

F

ITAKA Grou

Figure 4. F1 sc

Figure 5. F1 sc

up 2010

core results of

core results of

f the recomme

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endation for th

endation for th

he profile 3

he profile 4

- 110 -

Analy

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ysing the val

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In the cas

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lues of F1 in

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his fact is du

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ities in the s

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mmender us

distances betw

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more cities

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consider sev

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endations (c

n figures 2 to

taken as case

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close intra-

). Concretely

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n the numbe

to recommen

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wo users that h

the case of p

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ses the 3 cl

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precision of

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endations are

hey appear in

veral clusters

iate results.

er distance, t

sed distance

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distance 0.1

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o very good

distance of 0

tained when

concretely,

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e studies. So

nted a very s

alues in the m

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ct that only a

proposed di

r, because ta

commender

obtained for

d decreases fo

er of expecte

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the precision

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lusters close

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n many citie

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However, d

the recomme

e measure dis

utes.

general requ

1 and 10-15

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[1] C. Vicie

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up 2010

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extraction

Artificial Inte

chez, and A

n from he

elligence 26

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6 (2013), 10

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