Transcript LREC SPIM 2010 - ppt - DAI

Ernesto William De Luca, Alan Said,
Matthias Böhmer and Florian Michahelles
Organizers
Ernesto William De Luca
 Technische Universität Berlin.
 DAI-Labor
 Head of the Competence Center
for Information Retrieval
and Machine Learning.
(http://www.dai-labor.de/en/irml)
 E-mail:
[email protected]
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Organizers
Alan Said
 Technische Universität Berlin.
 DAI-Labor
 Member of the Competence
Center for Information Retrieval
and Machine Learning.
(http://www.dai-labor.de/en/irml)
 E-mail:
[email protected]
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Organizers
Matthias Böhmer
 German Research Center for AI
 DFKI
 Researcher at Innovative Retail
Laboratory
(http://www.innovative-retail.de)
 E-mail:
[email protected]
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Organizers
Florian Michahelles
 Auto-ID Labs at ETH Zurich
 Zurich, Switzerland
 Associate director
(http://www.im.ethz.ch/people/
fmichahelles)
 E-mail: [email protected]
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Aim of the CaRR Workshop
 Invite the community to a discussion in
which we will try to find new creative
ways to handle context-awareness
 Improve the exchange of ideas between
different communities involved
(user interfaces, machine learning,
information retrieval and recommendation)
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Previous Workshops
Context-awareness in Retrieval and Recommendation
Current SOA systems are generally context-ignorant,
CAMRa focused on identifying and utilizing contextual
data in real-life data from Moviepilot and Filmtipset.
Challenge on Context-aware Movie
Recommendation (CAMRa2010)
joint event with the Workshop on Context-aware
Recommender Systems (CARS-2010)
in conjunction with the ACM Recommender Systems
2010 Conference (RecSys2010).
http://www.dai-labor.de/camra2010/
www.moviepilot.com
www.filmtipset.se
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Can We Define Context?
”Any information that can be used
to characterise the situation of
entities”, Dey 2001
1. Item context
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Seasonal (Christmas, Oscar’s)
Relation (movie sequel, director, actor)
2. User context
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Surroundings (weather, location)
Company (alone, with friends)
Mood/emotions
any user related factor
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Why do we need Context?
+
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Filters relevant information
Ad hoc recommendations
Aware of changes
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What is context?
Where do we find it?
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Context-aware information
 It is widely available in various ways
 interaction patterns, location, devices,
annotations, query suggestions and user
profiles
 It is becoming more and more important
for
 enhancement of retrieval performance and
recommendation results
 personalization and adaptation of
information
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CaRR general information
 16 Submissions - 9 Accepted (6 Long, 3 Short)
56% Acceptance Rate
 Every submission was evaluated by at least three
of the 36 Members of the program committee.
 Proceedings wil be published in ACM DL
 All related information are available at:
http://www.dai-labor.de/carr2011/
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CaRR Topics
CaRR Papers cover different topics:
 Information Retrieval
 Recommender Systems
 Natural Language Processing and
Recommender Systems
 Smart Environments
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Agenda (1/6)
Session 1 (9:00-10:30)
 9:00 – 9:15 Context-awareness in Retrieval and
Recommendation
Ernesto William De Luca; Alan Said; Matthias Böhmer; Florian
Michahelles
 9:15 – 9:45 Towards a Context-Sensitive Online
Newspaper
Jeremy Jancsary; Friedrich Neubarth; Stephanie Schreitter; Harald
Trost
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Agenda (2/6)
Session 1 (9:00-10:30)
 9:45- 10:00 (short) Implicit Acquisition of Context for
Personalization of Information Retrieval Systems
Chang Liu; Nicholas J. Belkin
 10:00-10:30 (instead of 16:00 – 16:30) Guidance and
Support for Healthy Food Preparation in an
Augmented Kitchen
Jurgen Wagner; Gijs Geleijnse; Aart van Halteren
Break (10:30-11:00)
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Agenda (3/6)
Session 2 (11:00-13:00)
 11:00-12:00 Innovative Retail Laboratory: Assistive
Technology in Retail Environments.
Antonio Krüger (Invited Keynote)
 12:00-12:30 Real-time, Location-aware Collaborative
Filtering of Web Content
Thomas Sandholm; Hang Ung
 12:30-13:00 RecLab: A System For eCommerce
Recommender Research with Real Data, Context and
Feedback
Darren Vengroff
Lunch (13:00-14:00)
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Agenda (4/6)
Session 3 (14:00-15:30)
 14:00-14:15 (short) Cross-lingual Recommender
System for Research Papers
Kiyoko Uchiyama; Akiko Aizawa; Hidetsugu Nanba; Takeshi Sagara
 14:15-14:30 (short) Utilizing Implicit Feedback and
Context to Recommend Mobile Applications from
First Use
Christoffer Davidsson; Simon Moritz
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Agenda (5/6)
Session 3 (14:00-15:30)
 14:30-15:00 Context-Aware POI Recommendations in
an Automotive Scenario using Multi-Criteria Decision
Making Methods
Roland Bader; Eugen Neufeld; Wolfgang Woerndl; Vivian Prinz
 15:00-15:30 Designing Activity-aware Recommender
Systems for Operating Rooms,
Afsaneh Doryab; Jakob E. Bardram
Break (15:30-16:00)
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Agenda (6/6)
Session 4 (16:00-17:30)
 16:00 - 17:30 Open Discussion trying to focus on the
CARR problems and questions.
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Thanks!
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Agenda (Session 1)
Session 1 (9:00-10:30)
 9:15 – 9:45 Towards a Context-Sensitive Online Newspaper
Jeremy Jancsary; Friedrich Neubarth; Stephanie Schreitter; Harald
Trost
 9:45- 10:00 (short) Implicit Acquisition of Context for
Personalization of Information Retrieval Systems
Chang Liu; Nicholas J. Belkin
 10:00-10:30 (instead of 16:00 – 16:30) Guidance and Support for
Healthy Food Preparation in an Augmented Kitchen
Jurgen Wagner; Gijs Geleijnse; Aart van Halteren
Break (10:30-11:00)
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Agenda (Session 2)
Session 2 (11:00-13:00)
 11:00-12:00 Innovative Retail Laboratory: Assistive Technology
in Retail Environments.
Antonio Krüger (Invited Keynote)
 12:00-12:30 Real-time, Location-aware Collaborative Filtering of
Web Content
Thomas Sandholm; Hang Ung
 12:30-13:00 RecLab: A System For eCommerce Recommender
Research with Real Data, Context and Feedback
Darren Vengroff
Lunch (13:00-14:00)
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Agenda (Session 3)
Session 3 (14:00-15:30)
 14:00-14:15 (short) Cross-lingual Recommender System for
Research Papers
Kiyoko Uchiyama; Akiko Aizawa; Hidetsugu Nanba; Takeshi Sagara
 14:15-14:30 (short) Utilizing Implicit Feedback and Context to
Recommend Mobile Applications from First Use
Christoffer Davidsson; Simon Moritz
 14:30-15:00 Context-Aware POI Recommendations in an
Automotive Scenario using Multi-Criteria Decision Making
Methods
Roland Bader; Eugen Neufeld; Wolfgang Woerndl; Vivian Prinz
 15:00-15:30 Designing Activity-aware Recommender Systems
for Operating Rooms,
Afsaneh Doryab; Jakob E. Bardram
Break (15:30-16:00)
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Agenda (Session 4)
Session 4 (16:00-17:30)
 16:00 - 17:30 Open Discussion trying to focus on the CARR
problems and questions.
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Agenda (Session 4)
 CARR problems and questions:
 What is context?
 Is context-awareness
in retrieval and recommendation necessary?
 Which benefits come from
context-aware retrieval and recommendation systems?
 How do user interfaces handle context?
 In what ways can context improve HCI?
 How can we combine
general- and user-centric context-aware technologies?
 How should context affect the way
information is presented?
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Agenda (Session 4)
 CARR Topics
 Context-aware information retrieval
 Context-aware profiling, clustering and collaborative
filtering
 Machine learning for context-aware information
retrieval and ontology learning
 Ubiquitous and context-aware computing
 Use of context-aware technologies in UI/HCI
 Context-aware advertising
 Recommendations for mobile users
 Context-awareness in portable devices
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