article

Aggregated Search

Author:

Jaime ArguelloAuthors Info & Claims

Foundations and Trends in Information Retrieval, Volume 10, Issue 5

Pages 365 - 502

https://doi.org/10.1561/1500000052

Published: 06 March 2017 Publication History

Abstract

The goal of aggregated search is to provide integrated search acrossmultiple heterogeneous search services in a unified interface-a singlequery box and a common presentation of results. In the web searchdomain, aggregated search systems are responsible for integrating resultsfrom specialized search services, or verticals, alongside the coreweb results. For example, search portals such as Google, Bing, andYahoo! provide access to vertical search engines that focus on differenttypes of media images and video, different types of search taskssearch for local businesses and online products, and even applicationsthat can help users complete certain tasks language translation andmath calculations.Aggregated search systems perform two mains tasks. The first taskvertical selection is to predict which verticals if any to present inresponse to a user's query. The second task vertical presentation is topredict where and how to present each selected vertical alongside thecore web results.The goal of this work is to provide a comprehensive summary of previousresearch in aggregated search. We first describe why aggregatedsearch requires unique solutions. Then, we discuss different sources ofevidence that are likely to be available to an aggregated search system,as well as different techniques for integrating evidence in order to makevertical selection and presentation decisions. Next, we survey differentevaluation methodologies for aggregated search and discuss prioruser studies that have aimed to better understand how users behavewith aggregated search interfaces. Finally, we review different advancedtopics in aggregated search.

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Cited By

Momeni M(2024)Visualization-Enhanced Aggregated Search InterfacesProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638336(461-464)Online publication date: 10-Mar-2024
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cover image Foundations and Trends in Information Retrieval

Foundations and Trends in Information Retrieval Volume 10, Issue 5

6 3 2017

141 pages

ISSN:1554-0669

EISSN:1554-0677

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Published: 06 March 2017

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Momeni M(2024)Visualization-Enhanced Aggregated Search InterfacesProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638336(461-464)Online publication date: 10-Mar-2024
https://dl.acm.org/doi/10.1145/3627508.3638336
Pouamoun AKocabaş İ(2023)Multi-agent-based hybrid peer-to-peer system for distributed information retrievalJournal of Information Science10.1177/0165551521101039249:2(529-543)Online publication date: 22-Mar-2023
https://dl.acm.org/doi/10.1177/01655515211010392
Garba AWu SKhalid S(2023)Federated search techniques: an overview of the trends and state of the artKnowledge and Information Systems10.1007/s10115-023-01922-665:12(5065-5095)Online publication date: 10-Jul-2023
https://dl.acm.org/doi/10.1007/s10115-023-01922-6
Pardi GGottschling SKammerer Y(2023)The influence of knowledge type and source reputation on preferences for website or video search resultsJournal of the Association for Information Science and Technology10.1002/asi.2477175:5(521-537)Online publication date: 17-May-2023
https://dl.acm.org/doi/10.1002/asi.24771
Aliannejadi MZamani HCrestani FCroft W(2021)Context-aware Target Apps Selection and Recommendation for Enhancing Personal Mobile AssistantsACM Transactions on Information Systems10.1145/344767839:3(1-30)Online publication date: 5-May-2021
https://dl.acm.org/doi/10.1145/3447678
Rashid USaleem KAhmed A(2021)MIRRE approach: nonlinear and multimodal exploration of MIR aggregated search resultsMultimedia Tools and Applications10.1007/s11042-021-10603-x80:13(20217-20253)Online publication date: 1-May-2021
https://dl.acm.org/doi/10.1007/s11042-021-10603-x
Steichen BLowe R(2021)How do multilingual users search? An investigation of query and result list language choicesJournal of the Association for Information Science and Technology10.1002/asi.2444372:6(759-776)Online publication date: 14-May-2021
https://dl.acm.org/doi/10.1002/asi.24443
Procházka PKocián MDrdák JVršovský JKadlec VKuchar JPiwowarski BChevalier MGaussier EMaarek YNie JScholer F(2019)Vertical Search BlendingProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331345(1237-1240)Online publication date: 18-Jul-2019
https://dl.acm.org/doi/10.1145/3331184.3331345
Arguello JChoi B(2019)The Effects of Working Memory, Perceptual Speed, and Inhibition in Aggregated SearchACM Transactions on Information Systems10.1145/332212837:3(1-34)Online publication date: 16-May-2019
https://dl.acm.org/doi/10.1145/3322128
Verberne SHe JKruschwitz UWiggers GLarsen BRussell-Rose Tde Vries A(2019)First International Workshop on Professional SearchACM SIGIR Forum10.1145/3308774.330879952:2(153-162)Online publication date: 17-Jan-2019
https://dl.acm.org/doi/10.1145/3308774.3308799
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