Modeling social information learning among taxi drivers

Siyuan Liu, Ramayya Krishnan, Emma Brunskill, Lionel M. Ni

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

Abstract

When a taxi driver of an unoccupied taxi is seeking passengers on a road unknown to him or her in a large city, what should the driver do? Alternatives include cruising around the road or waiting for a time period at the roadside in the hopes of finding a passenger or just leaving for another road enroute to a destination he knows (e.g., hotel taxi rank)? This is an interesting problem that arises everyday in many cities worldwide. There could be different answers to the question poised above, but one fundamental problem is how the driver learns about the likelihood of finding passengers on a road that is new to him (as in he has not picked up or dropped off passengers there before). Our observation from large scale taxi drivers behavior data is that a driver not only learns from his own experience but through interactions with other drivers. In this paper, we first formally define this problem as Socialized Information Learning (SIL), second we propose a framework including a series of models to study how a taxi driver gathers and learns information in an uncertain environment through the use of his social network. Finally, the large scale real life data and empirical experiments confirm that our models are much more effective, efficient and scalable that prior work on this problem.

Original languageEnglish (US)
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 17th Pacific-Asia Conference, PAKDD 2013, Proceedings
Pages73-84
Number of pages12
EditionPART 2
DOIs
StatePublished - 2013
Event17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013 - Gold Coast, QLD, Australia
Duration: Apr 14 2013Apr 17 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7819 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013
CountryAustralia
CityGold Coast, QLD
Period4/14/134/17/13

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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