Paper Info
Title
Using Markov Chain Monte Carlo to play Trivia
Abstract
We introduce in this Demonstration a system called Trivia Masster that generates a very large Database of facts in a variety of topics, and uses it for question answering. The facts are collected from human users (the "crowd"); the system motivates users to contribute to the Database by using a Trivia Game, where users gain points based on their contribution. A key challenge here is to provide a suitable Data Cleaning mechanism that allows to identify which of the facts (answers to Trivia questions) submitted by users are indeed correct / reliable, and consequently how many points to grant users, how to answer questions based on the collected data, and which questions to present to the Trivia players, in order to improve the data quality. As no existing single Data Cleaning technique provides a satisfactory solution to this challenge, we propose here a novel approach, based on a declarative framework for defining recursive and probabilistic Data Cleaning rules. Our solution employs an algorithm that is based on Markov Chain Monte Carlo Algorithms.
Year
DOI
Venue
2011
10.1109/ICDE.2011.5767941
ICDE
Keywords
Field
DocType
markov chain monte carlo,probabilistic data,trivia masster,trivia question,trivia game,key challenge,suitable data,trivia player,data quality,users gain point,existing single data,question answering,probability,games,probabilistic logic,markov processes,markov process,reliability,databases,data analysis,monte carlo method,monte carlo methods,very large database
Data mining,Monte Carlo method,Markov process,Question answering,Data quality,Markov chain Monte Carlo,Computer science,Very large database,Theoretical computer science,Probabilistic logic,Database,Recursion
Conference
ISSN
Citations 
PageRank 
1084-4627
4
0.48
References 
Authors
8
4
Name
Order
Citations
PageRank
Daniel Deutch134541.49
Ohad Greenshpan219513.43
Boris Kostenko3131.43
Tova Milo440741052.72