Answering planning queries with the crowd

Haim Kaplan, Ilia Lotosh, Tova Milo, Slava Novgorodov

Research output: Contribution to journalConference articlepeer-review

Abstract

Recent research has shown that crowd sourcing can be used effectively to solve problems that are difficult for computers, e.g., optical character recognition and identification of the structural configuration of natural proteins. In this paper we propose to use the power of the crowd to address yet another difficult problem that frequently occurs in a daily life - answering planning queries whose output is a sequence of objects/actions, when the goal, i.e, the notion of "best output", is hard to formalize. For example, planning the sequence of places/attractions to visit in the course of a vacation, where the goal is to enjoy the resulting vacation the most, or planning the sequence of courses to take in an academic schedule planning, where the goal is to obtain solid knowledge of a given subject domain. Such goals may be easily understandable by humans, but hard or even impossible to formalize for a computer. We present a novel algorithm for efficiently harnessing the crowd to assist in answering such planning queries. The algorithm builds the desired plans incrementally, choosing at each step the 'best' questions so that the overall number of questions that need to be asked is minimized. We prove the algorithm to be optimal within its class and demonstrate experimentally its effiectiveness and efficiency.

Original languageEnglish
Pages (from-to)697-708
Number of pages12
JournalProceedings of the VLDB Endowment
Volume6
Issue number9
DOIs
StatePublished - 2013
Event39th International Conference on Very Large Data Bases, VLDB 2012 - Trento, Italy
Duration: 26 Aug 201330 Aug 2013

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