NDLI: On Optimizing Airline Ticket Purchase Timing

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ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 8

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 7

Issue 4(Special Issue on Crowd in Intelligent Systems, Research Note/Short Paper and Regular Papers), July 2016

Issue 3(Regular Papers, Survey Papers and Special Issue on Recommender System Benchmarks), April 2016

Issue 2(Special Issue on Causal Discovery and Inference), January 2016

Issue 1, October 2015

Learning to Rank from Noisy Data

Local Structure-Based Sparse Representation for Face Recognition

On Optimizing Airline Ticket Purchase Timing

Nonnegative Multiresolution Representation-Based Texture Image Classification

Multi-Keyword Multi-Click Advertisement Option Contracts for Sponsored Search

Analysis of the Impact of a Tag Recommendation System in a Real-World Folksonomy

A Hybrid Background Subtraction Method with Background and Foreground Candidates Detection

On Learning Prediction Models for Tourists Paths

Where2Stand: A Human Position Recommendation System for Souvenir Photography

Metastrategies in Large-Scale Bargaining Settings

Spatiotemporal Sequential Influence Modeling for Location Recommendations: A Gravity-based Approach

On-Device Mobile Landmark Recognition Using Binarized Descriptor with Multifeature Fusion

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 6

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 5

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 4

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 3

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 2

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 1

On Optimizing Airline Ticket Purchase Timing

Content Provider	ACM Digital Library
Author	Gini, Maria Groves, William
Copyright Year	2015
Abstract	Proper timing of the purchase of airline tickets is difficult even when historical ticket prices and some domain knowledge are available. To address this problem, we introduce an algorithm that optimizes purchase timing on behalf of customers and provides performance estimates of its computed action policy. Given a desired flight route and travel date, the algorithm uses machine-learning methods on recent ticket price quotes from many competing airlines to predict the future expected minimum price of all available flights. The main novelty of our algorithm lies in using a systematic feature-selection technique, which captures time dependencies in the data by using time-delayed features, and reduces the number of features by imposing a class hierarchy among the raw features and pruning the features based on in-situ performance. Our algorithm achieves much closer to the optimal purchase policy than other existing decision theoretic approaches for this domain, and meets or exceeds the performance of existing feature-selection methods from the literature. Applications of our feature-selection process to other domains are also discussed.
Starting Page	1
Ending Page	28
Page Count	28
File Format	PDF
ISSN	21576904
e-ISSN	21576912
DOI	10.1145/2733384
Volume Number	7
Issue Number	1
Journal	ACM Transactions on Intelligent Systems and Technology (TIST)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-10-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Airline ticket prices Data mining E-commerce Feature selection Price prediction
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Theoretical Computer Science

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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