research-article

A Case Study of Collaboration and Reputation in Social Web Search

Authors:

Michael P. O’Mahony,

Barry SmythAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology (TIST), Volume 3, Issue 1

Article No.: 4, Pages 1 - 29

https://doi.org/10.1145/2036264.2036268

Published: 01 October 2011 Publication History

Abstract

Although collaborative searching is not supported by mainstream search engines, recent research has highlighted the inherently collaborative nature of many Web search tasks. In this article, we describe HeyStaks, a collaborative Web search framework that is designed to complement mainstream search engines. At search time, HeyStaks learns from the search activities of other users and leverages this information to generate recommendations based on results that others have found relevant for similar searches. The key contribution of this article is to extend the HeyStaks social search model by considering the search expertise, or reputation, of HeyStaks users and using this information to enhance the result recommendation process. In particular, we propose a reputation model for HeyStaks users that utilise the implicit collaboration events that take place between users as recommendations are made and selected. We describe a live-user trial of HeyStaks that demonstrates the relevance of its core recommendations and the ability of the reputation model to further improve recommendation quality. Our findings indicate that incorporating reputation into the recommendation process further improves the relevance of HeyStaks recommendations by up to 40%.

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Guan JChen BYu S(2024)A hybrid similarity model for mitigating the cold-start problem of collaborative filtering in sparse dataExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.123700249:PBOnline publication date: 1-Sep-2024
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OKAY S(2023)Digital Pazarlama Stratejileri ve Hiper KişiselleştirmeDigital Marketing Strategies and Hyper PersonalizationEuropean Journal of Science and Technology10.31590/ejosat.1147526Online publication date: 1-May-2023
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Index Terms

A Case Study of Collaboration and Reputation in Social Web Search
1. Information systems
  1. Information systems applications

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cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 3, Issue 1

October 2011

391 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/2036264

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Copyright © 2011 ACM.

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Publication History

Published: 01 October 2011

Accepted: 01 January 2011

Revised: 01 January 2011

Received: 01 August 2010

Published in TIST Volume 3, Issue 1

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Cited By

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https://dl.acm.org/doi/10.1016/j.eswa.2024.123700
OKAY S(2023)Digital Pazarlama Stratejileri ve Hiper KişiselleştirmeDigital Marketing Strategies and Hyper PersonalizationEuropean Journal of Science and Technology10.31590/ejosat.1147526Online publication date: 1-May-2023
https://doi.org/10.31590/ejosat.1147526
Lan ZYang SWang XYan Y(2023)Criminalization of Copyright-Infringing Information Distribution AlgorithmsProceedings of the 2nd International Conference on Humanities, Wisdom Education and Service Management (HWESM 2023)10.2991/978-2-38476-068-8_35(284-295)Online publication date: 19-Jul-2023
https://doi.org/10.2991/978-2-38476-068-8_35
Behera GNain N(2023)The State-of-the-Art and Challenges on Recommendation System’s: Principle, Techniques and Evaluation StrategySN Computer Science10.1007/s42979-023-02207-z4:5Online publication date: 3-Sep-2023
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Qasim IAwan MAli SKhan SMosleh MAlsanad AKhattak HAlam M(2022)Affinity Propagation-Based Hybrid Personalized Recommender SystemComplexity10.1155/2022/69585962022Online publication date: 1-Jan-2022
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Joorabloo NJalili MRen Y(2020)Improved Collaborative Filtering Recommendation Through Similarity PredictionIEEE Access10.1109/ACCESS.2020.30357038(202122-202132)Online publication date: 2020
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