Enhancing Academic Event Participation with Context-aware and Social Recommendations

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The plethora of talks and presentations taking place at academic conferences makes it difficult, especially for young researchers to attend the
right talks or discuss with participants and potential collaborators with similar interests. Participants may not have a priori knowledge that allows
them to select the right talks or informal interactions with other participants. In this paper we present the context-aware mobile
recommendation services (CAMRS) based on the current context (whereabouts at the venue, popularity and activities of talks and presentations)
sensed at the conference venue. Additionally, we augment the current context with the academic community context of conference participants
which is inferred by using social network analysis and link prediction on large-scale co-authorship and citation networks of participants. By
combining the dynamic and social context of participants, we are able to recommend talks and people that may be interesting to a particular
participant. We evaluated CAMRS using data from two large digital libraries - the DBLP and CiteSeerX, and participants from two conferences -
ICWL 2010 and EC-TEL 2011. The result shows that the new approach can recommend novel talks and helps participants in establishing new
connections at conference venue.

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Enhancing Academic Event Participation with Context-aware and Social Recommendations

  1. 1. TeLLNet 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 University Advanced Community Information Systems (ACIS)Lehrstuhl Informatik 5(Information Systems) {pham|kovachev|cao|manib|klamma}@dbis.rwth-aachen.de Prof. Dr. M. Jarke I5-CMP-0812-1 This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.
  2. 2. TeLLNet Advanced Community Information Systems (ACIS) Responsive Web Engineering Community Web Analytics Open Visualization Community and Information Simulation Systems Community Community Support AnalyticsLehrstuhl Informatik 5 Requirements(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-2 Engineering
  3. 3. TeLLNet 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 collaborationLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-3
  4. 4. TeLLNet Motivation  E.g. ACM SIGGRAPH 2010 105 sessions 1000 participants 5 days Sightseeing & more ? ? Room 342: workshop ? Auditorium: keynoteLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke Room 204: paper session Hall: poster session Room 048: round table I5-CMP-0812-4
  5. 5. TeLLNet Filtering and Selection: ResearchersLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-5
  6. 6. TeLLNet Filtering and Selection: Events ✔ ?Lehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-6
  7. 7. TeLLNet Research 2.0  Support tools already exist in many domainsLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-7
  8. 8. TeLLNet 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  MobilityLehrstuhl Informatik 5(Information Systems) – The service runs on participants‘ smartphones Prof. Dr. M. Jarke I5-CMP-0812-8 – On-site real-time recommendations
  9. 9. TeLLNet Mobile Services for Conference Participants System Features Conference Navigator Schedule, community-based talk recommendation based on [Farzan, 2008] individuals‘ schedules I-KNOW Conference Assistant I-KNOW conference program browsing, planning; real time (KNOW Center, TU Graz, Austria) tracking of talks ACM UIST Conference App ACM UIST conference program browsing, planning (RWTH Aachen, Germany) Conference App ICSE, MSR, etc., conference program browsing, real time (Microsoft Research) tracking of talksLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-9
  10. 10. TeLLNet Social Mobile Services  Accessing online social networking services through mobile devices to facilitate social interaction  Current approaches System Features Techniques WhozThat Social networking ID sharing, content Bluetooth, WiFi, Online social [Beach, 2008] adaptation networking access SIM-Mee Bussiness card exchange, nearby Bluetooth, WiFi, NFC [Albert, 2009] contacts finding CenceMe Publishing sensing presence (status, Bluetooth, GPRS, WiFi [Miluzzo, 2007] activities, location, etc.) of users to social neworking sites, analysis of historicalLehrstuhl Informatik 5 sensing data(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-10
  11. 11. TeLLNet 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 approaches System Features Techniques CARS Learning user context from interaction Follows MD model [Bouzeghoub, 2009] history, building active user profiles UbiComp Display people information in RFID tags and readers [McCarthy, 2001] presentation, discussion and other social (informal events) at conferences PeerHood Dynamically creates and manages social Bluetooth, WLAN, GPRSLehrstuhl Informatik 5 [Karki, 2009] network of mobile devices based on communication(Information Systems) Prof. Dr. M. Jarke dynamic profile matching I5-CMP-0812-11
  12. 12. TeLLNet 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 CAMRS recommendation process  Recommendation generation: - Talk recommendation: apply CF on preference matrixLehrstuhl Informatik 5(Information Systems) - People recommendation: top similar authors (no-direct links) nearby Prof. Dr. M. Jarke I5-CMP-0812-12
  13. 13. TeLLNet 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) | (u ) (v ) | S (u , v ) | (u ) (v ) | where (u ) is the set of direct peer of author u  Overall similarity: linear combination of link prediction measures on two networks S (u, v) * Scoauthor (u, v) (1 ) * Scitation (u, v)Lehrstuhl Informatik 5(Information Systems) where 0 1 is the parameter to control the strength of coauthorship. In the Prof. Dr. M. Jarke I5-CMP-0812-13 evaluation, we set 0.7
  14. 14. TeLLNet 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 ClientLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-14
  15. 15. TeLLNet 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 timesLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-15
  16. 16. TeLLNet Knowledge Network: the VisualizationLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-16 - AERCS (http://bosch.informatik.rwth-aachen.de:5080/AERCS/)
  17. 17. TeLLNet 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 helpfulLehrstuhl Informatik 5 - People recommendation: some are known; evaluators agreed to interact with recommended(Information Systems) Prof. Dr. M. Jarke (unknown) people I5-CMP-0812-17
  18. 18. TeLLNet 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.Lehrstuhl Informatik 5(Information Systems) - People recommendation: some are known personally; Prof. Dr. M. Jarke I5-CMP-0812-18
  19. 19. TeLLNet 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 conferencesLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-19
  20. 20. TeLLNet Thank you for your attention! Questions?Lehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-CMP-0812-20

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