Synthesis of Partial Rankings of Points of Interest Using Crowdsourcing

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

Resumé

The web is increasingly being accessed from mobile devices, and studies suggest that a large fraction of keyword-based search engine queries have local intent, meaning that users are interested in local content and that the underlying ranking function should take into account both relevance to the query keywords and the query location. A key challenge in being able to make progress on the design of ranking functions is to be able to assess the quality of the results returned by ranking functions.
We propose a model that synthesizes a ranking of points of interest from answers to crowdsourced pairwise relevance questions. To evaluate the model, we propose an innovative methodology that enables evaluation of the quality of synthesized rankings in a simulated setting. We report on an experimental evaluation based on the methodology that shows that the proposed model produces promising results in pertinent settings and that it is capable of outperforming an approach based on majority voting.
OriginalsprogEngelsk
TitelProceedings of the 9th Workshop on Geographic Information Retrieval
Antal sider10
ForlagAssociation for Computing Machinery
Publikationsdato2015
Artikelnummer15
ISBN (Trykt)978-1-4503-3937-7
DOI
StatusUdgivet - 2015
Begivenhed9th Workshop on Geographic Information Retrieval - Paris, Frankrig
Varighed: 26 nov. 201527 nov. 2015
Konferencens nummer: 9
http://www.geo.uzh.ch/~rsp/gir15/

Konference

Konference9th Workshop on Geographic Information Retrieval
Nummer9
LandFrankrig
ByParis
Periode26/11/201527/11/2015
Internetadresse

Fingerprint

Search engines
Mobile devices

Citer dette

Keles, I., Saltenis, S., & Jensen, C. S. (2015). Synthesis of Partial Rankings of Points of Interest Using Crowdsourcing. I Proceedings of the 9th Workshop on Geographic Information Retrieval [15] Association for Computing Machinery. https://doi.org/10.1145/2837689.2837705
Keles, Ilkcan ; Saltenis, Simonas ; Jensen, Christian Søndergaard. / Synthesis of Partial Rankings of Points of Interest Using Crowdsourcing. Proceedings of the 9th Workshop on Geographic Information Retrieval. Association for Computing Machinery, 2015.
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abstract = "The web is increasingly being accessed from mobile devices, and studies suggest that a large fraction of keyword-based search engine queries have local intent, meaning that users are interested in local content and that the underlying ranking function should take into account both relevance to the query keywords and the query location. A key challenge in being able to make progress on the design of ranking functions is to be able to assess the quality of the results returned by ranking functions.We propose a model that synthesizes a ranking of points of interest from answers to crowdsourced pairwise relevance questions. To evaluate the model, we propose an innovative methodology that enables evaluation of the quality of synthesized rankings in a simulated setting. We report on an experimental evaluation based on the methodology that shows that the proposed model produces promising results in pertinent settings and that it is capable of outperforming an approach based on majority voting.",
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Keles, I, Saltenis, S & Jensen, CS 2015, Synthesis of Partial Rankings of Points of Interest Using Crowdsourcing. i Proceedings of the 9th Workshop on Geographic Information Retrieval., 15, Association for Computing Machinery, 9th Workshop on Geographic Information Retrieval, Paris, Frankrig, 26/11/2015. https://doi.org/10.1145/2837689.2837705

Synthesis of Partial Rankings of Points of Interest Using Crowdsourcing. / Keles, Ilkcan; Saltenis, Simonas; Jensen, Christian Søndergaard.

Proceedings of the 9th Workshop on Geographic Information Retrieval. Association for Computing Machinery, 2015. 15.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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AB - The web is increasingly being accessed from mobile devices, and studies suggest that a large fraction of keyword-based search engine queries have local intent, meaning that users are interested in local content and that the underlying ranking function should take into account both relevance to the query keywords and the query location. A key challenge in being able to make progress on the design of ranking functions is to be able to assess the quality of the results returned by ranking functions.We propose a model that synthesizes a ranking of points of interest from answers to crowdsourced pairwise relevance questions. To evaluate the model, we propose an innovative methodology that enables evaluation of the quality of synthesized rankings in a simulated setting. We report on an experimental evaluation based on the methodology that shows that the proposed model produces promising results in pertinent settings and that it is capable of outperforming an approach based on majority voting.

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Keles I, Saltenis S, Jensen CS. Synthesis of Partial Rankings of Points of Interest Using Crowdsourcing. I Proceedings of the 9th Workshop on Geographic Information Retrieval. Association for Computing Machinery. 2015. 15 https://doi.org/10.1145/2837689.2837705