Presentation done by Adriano Venturini, during "Recommender systems" workshop, of the ENTER2015 eTourism conference.

1. ENTER 2015 Research Track Slide Number 1
Exploiting Web Analytics Tracking
for Bootstrapping a
Case-based Recommender System
Paolo Massa(a)
, Michela Ferron(a),
Adriano Venturini(b)
(a)Fondazione Bruno Kessler, Italy
(b)ECTRL Solutions SRL, Italy
venturini@ectrlsolutions.com
http://www.ectrlsolutions.com
http://www.fbk.eu

2. ENTER 2015 Research Track Slide Number 2
Contents
• The Travel Monitor Project
• Develop a tool to monitor the travel
planning process of the user
• How collected data can be used to
bootstrap the recommender system
• Current status and future works

3. ENTER 2015 Research Track Slide Number 3
Travel Monitor
• Tool to analyze the users’ behviours while planning a
travel, when he is interacting with the hotel or
destination websites, or in place using a mobile
devices or local infopoints positioned on site.
• Exploit navigation data to understand:
• Effectiveness of the used systems
• Users’ interests
• Choices and decisions
• Buying behviours

4. ENTER 2015 Research Track Slide Number 4
Travel Monitor: goals
Understand the users:
To identify the different characteristics, needs
Understand the travel planning process:
To define more interesting offers
planning marketing campaign
Indentify strong and weak points of the online presence
To support adaptive behviour of the system
Possiblity to exploit the collected data to initialze
the knowledge base of our recommender
system

5. ENTER 2015 Research Track Slide Number 5
Suggesto PortalSuggesto Portal
Suggesto
Recommender
Suggesto
Recommender
Suggesto
CMS
Suggesto
CMS
Travel plannerTravel planner Infopoint/MobileInfopoint/MobileTourism portalsTourism portals
Booking EngineBooking Engine
ECTRL’s Suggesto Platform

6. ENTER 2015 Research Track Slide Number 6
Travel Monitor: monitoring the
travel planner process

7. ENTER 2015 Research Track Slide Number 7
General structure of Travel
Monitor

8. ENTER 2015 Research Track Slide Number 8
Interacting with the
tourism portal

9. ENTER 2015 Research Track Slide Number 9
Visited sections

10. ENTER 2015 Research Track Slide Number 10
Monitoring the user’s
query and results

11. ENTER 2015 Research Track Slide Number 11
From the users’ query we can
understand:
Which are the most interesting categories ?
Does the user find what is looking for ?
It helps DMO to plan marketing of the
destinations, to understand weakness of the
tourist offers
To define categories for structuring their
contents in the CMS

12. ENTER 2015 Research Track Slide Number 12
The Travel Planner

13. ENTER 2015 Research Track Slide Number 13
Getting recommendations

14. ENTER 2015 Research Track Slide Number 14
My travel plan

15. ENTER 2015 Research Track Slide Number 15

16. ENTER 2015 Research Track Slide Number 16
Analysing travel planner data
DMOs can get:
Profiles of their visitors and their distributions
Which are the most interesting products
according to different types of travelers
Travel planning choices:
which items they select when they plan a
travel

17. ENTER 2015 Research Track Slide Number 17
Hotel websites

18. ENTER 2015 Research Track Slide Number 18
Number of accesses to the
booking pages, number of
bookings

19. ENTER 2015 Research Track Slide Number 19
Hotel booking process

20. ENTER 2015 Research Track Slide Number 20
Hotel booking process

21. ENTER 2015 Research Track Slide Number 21
Infopoints
Located in hotel lobbies and
tourism offices

22. ENTER 2015 Research Track Slide Number 22
Usage on the territory

23. ENTER 2015 Research Track Slide Number 23
Suggesto Recommendation
technology
• Derives from the Trip@dvice case-based
reasoning recommender (Ricci et al, 2006)
• It utilizes travel plans (cases) built by other
users in the past to identify possible items
the user is interested in

24. ENTER 2015 Research Track Slide Number 24
Case Model
• Collaborative features:
• Travel Party
• Travel Budget
• Travel Interests
• Chosen items in the travel plans
• Attractions
• Events
• Accommodations
• Interests
• The system exploits similarity among the collaborative
features of past travels to identify items which could fit the
travel plan planned by the current user

25. ENTER 2015 Research Track Slide Number 25
Bootstrap the recommender
To initialze the casebase with an initial set of
«good» cases:
• Representative of the visitors
• With the correct associations between
collaborative features and selected items

26. ENTER 2015 Research Track Slide Number 26
Mapping analytics data to the
collaborative features
From booking search (number of persons)
 Travel Party
From booking search (type of accommodations)
 Budget
From search of activities
 Travel interests
From visited pages
 preferred items

27. ENTER 2015 Research Track Slide Number 27
A possibile methodology

28. ENTER 2015 Research Track Slide Number 28
Project status and future
activities
Developed the Travel Monitor tool
Collecting analyitical data
Analysing how systems are used
Described the methodology for bootstrapping
the recommender
Next step is to implement and evaluate the
indentified methodology

29. ENTER 2015 Research Track Slide Number 29
Thanks!
Acknowledgment: This work has been partially funded by
Travel Monitor Project, FESR 2011 funding programme,
CUP C67I12000030008.