Maurice Coyle

TIST Journal 2011 Journal Article

A Case Study of Collaboration and Reputation in Social Web Search

• Kevin McNally
• Michael P. O’Mahony
• Maurice Coyle
• Peter Briggs
• Barry Smyth

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%.

IJCAI Conference 2005 Conference Paper

A Live-User Evaluation of Collaborative Web Search

• Barry Smyth
• Evelyn Balfe
• Oisin Boydell
• Keith Bradley
• Peter Briggs
• Maurice Coyle
• Jill

Collaborative Web search exploits repetition and regularity within the query-space of a community of like-minded individuals in order to improve the quality of search results. In short, search results that have been judged to be relevant for past queries are promoted in response to similar queries that occur in the future. In this paper we present the results of a large-scale evaluation of this approach, in a corporate Web search scenario, which shows that significant benefits are available to its users.

IJCAI Conference 2005 Conference Paper

Explaining Search Results

• Maurice Coyle
• Barry

In this paper we argue that it may be possible to help searchers to better understand the relevance of search results by generating explanations that highlight how other users have interacted with such results under similar search conditions in the past. We propose the use of the search histories of a community of online users as a source of these explanations. We describe the results of a recent study to examine the use of such explanation-based techniques to help Web searchers better appreciate the relevancy of search results. We highlight shortcomings of this approach in its current form and offer suggestions as to how it may be improved in future work.

ECAI Conference 2004 Conference Paper

Different Strokes for Different Folks: An Analysis of Similarity and Diversity in Web Search

• Maurice Coyle
• Barry Smyth

IJCAI Conference 2003 Conference Paper

Collaborative Web Search

• Barry Smyth
• Evelyn Balfe
• Peter Briggs
• Maurice Coyle
• Jill Freyne

Web search engines struggle to satisfy the needs of Web users. Users are notoriously poor at representing their needs in the form of a query, and search engines are poor at responding to vague queries. However progress has been made by introducing context into the search process. In this paper we describe and evaluate a novel approach to using context in Web search that adapts a generic search engine for the needs of a specialist community of users. This collaborative search method enjoys significant performance benefits and avoids the privacy and security concerns that are commonly associated with related personalization research.