research-article

Voyageur: An Experiential Travel Search Engine

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Xiaolan WangAuthors Info & Claims

WWW '19: The World Wide Web Conference

Pages 3511 - 5

https://doi.org/10.1145/3308558.3314125

Published: 13 May 2019 Publication History

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Abstract

We describe Voyageur, which is an application of experiential search to the domain of travel. Unlike traditional search engines for online services, experiential search focuses on the experiential aspects of the service under consideration. In particular, Voyageur needs to handle queries for subjective aspects of the service (e.g., quiet hotel, friendly staff) and combine these with objective attributes, such as price and location. Voyageur also highlights interesting facts and tips about the services the user is considering to provide them with further insights into their choices.

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Cited By

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Amer-Yahia SMilo TYoungmann BLi GLi ZIdreos SSrivastava D(2021)Exploring Ratings in Subjective DatabasesProceedings of the 2021 International Conference on Management of Data10.1145/3448016.3457259(62-75)Online publication date: 9-Jun-2021
https://dl.acm.org/doi/10.1145/3448016.3457259
Li YFeng ALi JChen SMumick SHalevy ALi VTan W(2020)Querying subjective dataThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-020-00634-530:1(115-140)Online publication date: 8-Sep-2020
https://dl.acm.org/doi/10.1007/s00778-020-00634-5
Li YFeng ALi JMumick SHalevy ALi VTan W(2019)Subjective databasesProceedings of the VLDB Endowment10.14778/3342263.334227112:11(1330-1343)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.14778/3342263.3342271

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Information & Contributors

Information

Published In

WWW '19: The World Wide Web Conference

May 2019

3620 pages

ISBN:9781450366748

DOI:10.1145/3308558

Editors:
Ling Liu
Georgia Tech, USA
,
Ryen White
Microsoft Research, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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IW3C2: International World Wide Web Conference Committee

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 May 2019

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WWW '19

WWW '19: The Web Conference

May 13 - 17, 2019

CA, San Francisco, USA

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Amer-Yahia SMilo TYoungmann BLi GLi ZIdreos SSrivastava D(2021)Exploring Ratings in Subjective DatabasesProceedings of the 2021 International Conference on Management of Data10.1145/3448016.3457259(62-75)Online publication date: 9-Jun-2021
https://dl.acm.org/doi/10.1145/3448016.3457259
Li YFeng ALi JChen SMumick SHalevy ALi VTan W(2020)Querying subjective dataThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-020-00634-530:1(115-140)Online publication date: 8-Sep-2020
https://dl.acm.org/doi/10.1007/s00778-020-00634-5
Li YFeng ALi JMumick SHalevy ALi VTan W(2019)Subjective databasesProceedings of the VLDB Endowment10.14778/3342263.334227112:11(1330-1343)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.14778/3342263.3342271

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