@article{mcnally2011study,
  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%.},
  acmid = {2036268},
  address = {New York, NY, USA},
  articleno = {4},
  author = {McNally, Kevin and O'Mahony, Michael P. and Coyle, Maurice and Briggs, Peter and Smyth, Barry},
  doi = {10.1145/2036264.2036268},
  interhash = {d2c8b459dba49425b1db33bd0d6fae47},
  intrahash = {2544752b497c7f74b809e2d24145f14b},
  issn = {2157-6904},
  issue_date = {October 2011},
  journal = {ACM Transactions on Intelligent Systems and Technology},
  month = oct,
  number = 1,
  numpages = {29},
  pages = {4:1--4:29},
  publisher = {ACM},
  title = {A Case Study of Collaboration and Reputation in Social Web Search},
  url = {http://doi.acm.org/10.1145/2036264.2036268},
  volume = 3,
  year = 2011
}

@inproceedings{smyth2012heystaks,
  abstract = {The purpose of this paper is to provide a deployment update for the HeyStaks social search system which uses recommendation techniques to add collaboration to mainstream search engines such as Google, Bing, and Yahoo. We describe our the results of initial deployments, including an assessment of the quality of HeyStaks' recommendations, and highlight some lessons learned in the marketplace},
  acmid = {2366017},
  address = {New York, NY, USA},
  author = {Smyth, Barry and Coyle, Maurice and Briggs, Peter},
  booktitle = {Proceedings of the sixth ACM conference on Recommender systems},
  doi = {10.1145/2365952.2366017},
  interhash = {79493147080cf8f22d34d6b6d8e4c636},
  intrahash = {857d0a369453edfb9292e7a3aad29e37},
  isbn = {978-1-4503-1270-7},
  location = {Dublin, Ireland},
  numpages = {4},
  pages = {289--292},
  publisher = {ACM},
  title = {HeyStaks: a real-world deployment of social search},
  url = {http://doi.acm.org/10.1145/2365952.2366017},
  year = 2012
}

@inproceedings{mcnally2010towards,
  abstract = {While web search tasks are often inherently collaborative in nature, many search engines do not explicitly support collaboration during search. In this paper, we describe HeyStaks (www.heystaks.com), a system that provides a novel approach to collaborative web search. Designed to work with mainstream search engines such as Google, HeyStaks supports searchers by harnessing the experiences of others as the basis for result recommendations. Moreover, a key contribution of our work is to propose a reputation system for HeyStaks to model the value of individual searchers from a result recommendation perspective. In particular, we propose an algorithm to calculate reputation directly from user search activity and we provide encouraging results for our approach based on a preliminary analysis of user activity and reputation scores across a sample of HeyStaks users.},
  acmid = {1719996},
  address = {New York, NY, USA},
  author = {McNally, Kevin and O'Mahony, Michael P. and Smyth, Barry and Coyle, Maurice and Briggs, Peter},
  booktitle = {Proceedings of the 15th international conference on Intelligent user interfaces},
  doi = {10.1145/1719970.1719996},
  interhash = {039d613f3fae6adab294e4b52f1ecb0e},
  intrahash = {877ae3a66485776de88ba99951d9af2c},
  isbn = {978-1-60558-515-4},
  location = {Hong Kong, China},
  numpages = {10},
  pages = {179--188},
  publisher = {ACM},
  title = {Towards a reputation-based model of social web search},
  url = {http://doi.acm.org/10.1145/1719970.1719996},
  year = 2010
}

@incollection{smyth2009google,
  abstract = {Web search is the dominant form of information access and everyday millions of searches are handled by mainstream search engines, but users still struggle to find what they are looking for, and there is much room for improvement. In this paper we describe a novel and practical approach to Web search that combines ideas from personalization and social networking to provide a more collaborative search experience. We described how this has been delivered by complementing, rather than competing with, mainstream search engines, which offers considerable business potential in a Google-dominated search marketplace.},
  address = {Berlin/Heidelberg},
  affiliation = {CLARITY: Centre for Sensor Web Technologies School of Computer Science and Informatics, University College Dublin, Ireland},
  author = {Smyth, Barry and Briggs, Peter and Coyle, Maurice and O’Mahony, Michael},
  booktitle = {User Modeling, Adaptation, and Personalization},
  doi = {10.1007/978-3-642-02247-0_27},
  editor = {Houben, Geert-Jan and McCalla, Gord and Pianesi, Fabio and Zancanaro, Massimo},
  interhash = {7bc2fa43b8ea2d34ed00f2bfb072b9f3},
  intrahash = {c3e8aa7308b701aec9325577cd298e58},
  isbn = {978-3-642-02246-3},
  keyword = {Computer Science},
  pages = {283--294},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {Google Shared. A Case-Study in Social Search},
  url = {http://dx.doi.org/10.1007/978-3-642-02247-0_27},
  volume = 5535,
  year = 2009
}

@inproceedings{freyne2007collecting,
  abstract = {The goal of this paper is to detail the integration of two "social Web" technologies - social search and social navigation - and to highlight the benefits of such integration on two levels. Firstly, both technologies harvest and harness "community wisdom" and in an integrated system each of the search and navigation components can benefit from the additional community wisdom gathered by the other when assisting users to locate relevant information. Secondly, by integrating search and browsing we facilitate the development of a unique interface that effectively blends search and browsing functionality as part of a seamless social information access service. This service allows users to effectively combine their search and browsing behaviors. In this paper we will argue that this integration provides significantly more than the simple sum of the parts.},
  acmid = {1216312},
  address = {New York, NY, USA},
  author = {Freyne, Jill and Farzan, Rosta and Brusilovsky, Peter and Smyth, Barry and Coyle, Maurice},
  booktitle = {Proceedings of the 12th international conference on Intelligent user interfaces},
  doi = {10.1145/1216295.1216312},
  interhash = {871e012dc7b1c131d32480f1e3a655e7},
  intrahash = {93fecd064cd42e0ea5f9dc06a9458d3c},
  isbn = {1-59593-481-2},
  location = {Honolulu, Hawaii, USA},
  numpages = {10},
  pages = {52--61},
  publisher = {ACM},
  title = {Collecting community wisdom: integrating social search \& social navigation},
  url = {http://doi.acm.org/10.1145/1216295.1216312},
  year = 2007
}

@incollection{citeulike:3149792,
  abstract = {The motivation behind many Information Retrieval systems is to identify and present relevant information to people given their current goals and needs. Learning about user preferences and access patterns recent technologies make it possible to model user information needs and adapt services to meet these needs. In previous work we have presented ASSIST, a general-purpose platform which incorporates various types of social support into existing information access systems and reported on our deployment experience in a highly goal driven environment (ACM Digital Library). In this work we present our experiences in applying ASSIST to a domain where goals are less focused and where casual exploration is more dominant; YouTube. We present a general study of YouTube access patterns and detail how the ASSIST architecture affected the access patterns of users in this domain.},
  author = {Coyle, Maurice and Freyne, Jill and Brusilovsky, Peter and Smyth, Barry},
  citeulike-article-id = {3149792},
  doi = {http://dx.doi.org/10.1007/978-3-540-70987-9\_12},
  interhash = {487512d7286ca43ca9b96ee4a0efc198},
  intrahash = {f75eb556b19abd7b399f2f27ae49cb1c},
  journal = {Adaptive Hypermedia and Adaptive Web-Based Systems},
  pages = {93--102},
  posted-at = {2008-10-13 00:16:23},
  priority = {2},
  title = {Social Information Access for the Rest of Us: An Exploration of Social YouTube},
  url = {http://www.springerlink.com/content/6h410u3w4836v866/},
  year = 2008
}

@inproceedings{freyne07,
  address = {New York, NY, USA},
  author = {Freyne, Jill and Farzan, Rosta and Brusilovsky, Peter and Smyth, Barry and Coyle, Maurice},
  booktitle = {IUI '07: Proceedings of the 12th international conference on Intelligent user interfaces},
  doi = {http://doi.acm.org/10.1145/1216295.1216312},
  interhash = {871e012dc7b1c131d32480f1e3a655e7},
  intrahash = {88603ee0903b30dc642aebdaa6a22f93},
  isbn = {1-59593-481-2},
  location = {Honolulu, Hawaii, USA},
  pages = {52--61},
  publisher = {ACM Press},
  title = {Collecting community wisdom: integrating social search \& social navigation},
  url = {http://portal.acm.org/citation.cfm?id=1216312},
  year = 2007
}