Session Expert: A Lightweight Conference Session Recommender System

Jinfeng Yi, Qi Lei, Junchi Yan, Wei Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

At large and popular conferences, it is not uncommon for attendees to feel overwhelmed and lost while trying to navigate through many parallel sessions. In this paper, we present a conference session recommender system. In contrast to the conventional »query-search» model where a system passively engages with users, Session Expert actively interacts with users via natural, human-like conversations and provides personalized recommendations. The underlying session recommender engine is designed to handle the cold start problem, and is lightweight to enable real-time session recommendations and rationale-aware response generation. Specifically, the recommender system alleviates the cold start problem by transferring knowledge from another similar conference in an offline setting. This step is achieved by first exploiting a positive-unlabeled (PU) learning model to reveal the underlying user interest from the historical enrollment data, and then modeling a bilinear relationship which captures how user and session features influence users' interests. Given the learned bilinear model, recommendation scores and rationale can be generated online as it only involves a few matrix-vector multiplications which can be computed efficiently.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018
EditorsYang Song, Bing Liu, Kisung Lee, Naoki Abe, Calton Pu, Mu Qiao, Nesreen Ahmed, Donald Kossmann, Jeffrey Saltz, Jiliang Tang, Jingrui He, Huan Liu, Xiaohua Hu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1677-1682
Number of pages6
ISBN (Electronic)9781538650356
DOIs
StatePublished - Jan 22 2019
Event2018 IEEE International Conference on Big Data, Big Data 2018 - Seattle, United States
Duration: Dec 10 2018Dec 13 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

Conference

Conference2018 IEEE International Conference on Big Data, Big Data 2018
Country/TerritoryUnited States
CitySeattle
Period12/10/1812/13/18

Keywords

  • cold start problem
  • Conference session recommendation
  • rationale generation

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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