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TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-1 This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.
Enhancing Academic Event Participation with Context-aware
and Social Recommendations
Manh Cuong Pham, Dejan Kovachev, Yiwei Cao, Ghislain Manib Mbogos and Ralf Klamma
RWTH Aachen UniversityAdvanced Community Information Systems (ACIS)
{pham|kovachev|cao|manib|klamma}@dbis.rwth-aachen.de
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-2
Responsive Open
Community Information
Systems
Community Visualization
and Simulation
Community Analytics
Community Support
Web A
nalytics
Web
Eng
inee
ring
Advanced Community Information Systems (ACIS)
Requirements Engineering
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-3
Motivation
Main reasons to participate in academic conferences: – To get informed about the state-of-the-art– To present own research, and get reactions from peers– To have papers published in the conference proceedings
– To meet others working in the same domain– Quickly exchange a variety of experiences– Establish personal relationships– Lay the foundation for future collaboration
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-4
Motivation
Room 204: paper session
?
??
Hall: poster session
Room 342: workshop
Room 048: round table
Auditorium: keynote
E.g. ACM SIGGRAPH 2010- 105 sessions- 1000 participants- 5 days Sightseeing & more
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-5
Filtering and Selection: Researchers
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-6
Filtering and Selection: Events
✔
?
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-7
Support tools already exist in many domains
Research 2.0
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-8
Context-Aware Mobile Recommender System for Conference Participants (CAMRS)
Goals – A mobile recommendation service for conference participants – Talk and researcher recommendations
Spatio-temporal context– Whereabouts at the venue – Popularity and activities of talks and presentations
Social context – Academic community context– SNA and link prediction on large-scale co-authorship and citation
networks of participants– Analysis of the collaboration ties existing among the participants
Mobility– The service runs on participants‘ smartphones– On-site real-time recommendations
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-9
Mobile Services for Conference Participants
System FeaturesConference Navigator[Farzan, 2008]
Schedule, community-based talk recommendation based on individuals‘ schedules
I-KNOW Conference Assistant (KNOW Center, TU Graz, Austria)
I-KNOW conference program browsing, planning; real time tracking of talks
ACM UIST Conference App(RWTH Aachen, Germany)
ACM UIST conference program browsing, planning
Conference App (Microsoft Research)
ICSE, MSR, etc., conference program browsing, real time tracking of talks
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-10
Social Mobile Services
Accessing online social networking services through mobile devices to facilitate social interaction
Current approaches
System Features Techniques
WhozThat[Beach, 2008]
Social networking ID sharing, content adaptation
Bluetooth, WiFi, Online social networking access
SIM-Mee[Albert, 2009]
Bussiness card exchange, nearby contacts finding
Bluetooth, WiFi, NFC
CenceMe[Miluzzo, 2007]
Publishing sensing presence (status, activities, location, etc.) of users to social neworking sites, analysis of historical sensing data
Bluetooth, GPRS, WiFi
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-11
Context-Aware Mobile Recommendation Services
Multidimensional recommendation model (MD) [Adomavicius 2005]
- CF: 2-dimensions, e.g., user and item- MD: n-dimentions, e.g., user, item, time, location, etc.- Incorporate contextual information: reduce n to two dimentions
Current approachesSystem Features Techniques
CARS[Bouzeghoub, 2009]
Learning user context from interaction history, building active user profiles
Follows MD model
UbiComp[McCarthy, 2001]
Display people information in presentation, discussion and other social (informal events) at conferences
RFID tags and readers
PeerHood[Karki, 2009]
Dynamically creates and manages social network of mobile devices based on dynamic profile matching
Bluetooth, WLAN, GPRS communication
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-12
Conflation of Contextual and Social Information
Dynamic preference matrix- User-talk matrix: schedule and location of
participants- Projection of user-talk matrix on time
dimension Neighborhood formulation
- Pre-compute similarity using link-prediction measure Jaccard based on citation and co-authorship networks
- Select top k similar authors
Recommendation generation:- Talk recommendation: apply CF on preference matrix- People recommendation: top similar authors (no-direct links) nearby
CAMRS recommendation process
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-13
Neighborhood Formulation Link prediction on co-authorship and citation networks Two types of neighbor
- Direct peer: two authors who are directly connected, similarity equal to 1 - In-direct peer: Jaccard measure (other measures are possible)
where is the set of direct peer of author u Overall similarity: linear combination of link prediction measures on two
networks
where is the parameter to control the strength of coauthorship. In the evaluation, we set
|)()(|
|)()(|),(
vu
vuvuS
),(*)1(),(*),( vuSvuSvuS citationcoauthor
)(u
10 7.0
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-14
CAMRS Prototype RESTful Web Service Oracle 11g database Android app Location sensing:
- At least at room level- Currently used a QR code scanner on
Android smartphones- Other possible techniques:
RFID, WiFi, etc. Conference program
- XML schema to handle conference program CAMRS Mobile Client
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-15
Data Sets DBLP (http://www.informatik.uni-trier.de/~ley/db/)
- 788,259 author’s names- 1,226,412 publications- 3,490 series (conferences, workshops, journals)
CiteSeerX (http://citeseerx.ist.psu.edu/)- 7,385,652 publications (including publications in reference lists)- 22,735,240 citations- Over 4 million author’s names
Combination- Canopy clustering [McCallum 2000]- Result: 864,097 matched pairs - On average: series cite 2306 and are cited 2037 times
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-16
Knowledge Network:the Visualization
- AERCS (http://bosch.informatik.rwth-aachen.de:5080/AERCS/)
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-17
Evaluation 1: ICWL 2010 Simulation
Testbed setup- Choose 6 evaluators equipped with Android smartphones- Program: 15 tracks (3 keynotes, 6 paper sections, 6 workshops) with 128
participants- Three rooms with QR code
Procedure- Conference program was run in real time- Evaluators moved around between three rooms- Recommendations were logged for later analysis
Results- Real time recommendations - Performance:
- Talk recommendations are helpful- People recommendation: some are known; evaluators agreed to interact with recommended
(unknown) people
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-18
Evaluation 2: ECTEL 2011
Testbed setup- A poster was presented in ECTEL 2011- ECTEL program was imported into CAMRS- Android smartphones were available to participants at the conference
Procedure- Conference program was run in real time- Participants can login and get recommendations- Mobility was not evaluated- A survey was sent after the conference
Results- 20 feedbacks with positive comments
- „The talk recommendations were strikingly accurate“, „ Some of the recommendations were surprising, but it remains unclear, why they have been chosen“, etc.
- People recommendation: some are known personally;
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-19
Conclusions and Future Work Combination of research history and contextual information
– Link prediction on co-authorship and citation networks to find similar researchers– Dynamic implicit preference data of users on talks/presentations
Two case studies verify the recommendations Open issues
– Topic drift: user interest changes over time– Diversity in user interest: user may be interested in different topics
On-going work– Community mining from citation and collaboration networks: non-overlapping and
overlapping communities– Topic modeling: enhance communities with topics– Further evaluations on more conferences
TeLLNet
Lehrstuhl Informatik 5(Information Systems)
Prof. Dr. M. JarkeI5-CMP-0812-20
Thank you for your attention!
Questions?