enhancing academic event participation with context-aware and social recommendations

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

http://creativecommons.org/licenses/by-sa/3.0/





http://dbis.rwth-aachen.de/cms/research/MiCIS


http://www.tellnet.eun.org/web/tellnet

http://www.umic.rwth-aachen.de/

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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





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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





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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





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Filtering and Selection: Researchers





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Filtering and Selection: Events

✔

?





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Support tools already exist in many domains

Research 2.0





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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





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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





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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





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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





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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





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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





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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





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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





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Knowledge Network:the Visualization

- AERCS (http://bosch.informatik.rwth-aachen.de:5080/AERCS/)





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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





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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;





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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





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Thank you for your attention!

Questions?





enhancing academic event participation with context-aware and social recommendations

Business

contextual information

gprslehrstuhl informatik

domainslehrstuhl informatik

keynotelehrstuhl informatik

user context

conference assistant

conference proceedings

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