Studying the use of popular destinations to enhance web search interaction

White, Ryen W.; Bilenko, Mikhail; Cucerzan, Silviu

doi:10.1145/1277741.1277771

Cited by 164 publications

(130 citation statements)

References 18 publications

Supporting

Mentioning

128

Contrasting

Order By: Relevance

“…The paper written by Shannon [155] is the reference for entropy. The papers on exploratory search by White et al [172]; White and Kelly [173]; White et al [170,171]; White and Roth [174]; White [169] are also useful reading.…”

Section: Concluding Remarks and Suggestionsmentioning

confidence: 99%

Contextual Search: A Computational Framework

Melucci

2012

FNT in Information Retrieval

View full text Add to dashboard Cite

Section: Concluding Remarks and Suggestionsmentioning

confidence: 99%

Contextual Search: A Computational Framework

Melucci

2012

FNT in Information Retrieval

View full text Add to dashboard Cite

“…Examples of this include Kelly et al's [11] lab-based user study examining participants' usage of query and term suggestions; White et al's [17] comparative lab-based user study involving a novel popular search destinations feature for specific queries; Anick's [1] naturalistic log-based study of searchers' usage of suggested queries; Koenemann and Belkin [12] and Ruthven's [15] empirical studies on the effectiveness of Interactive Query Expansion.…”

Section: Related Workmentioning

confidence: 99%

Interactive Search Support for Difficult Web Queries

Diriye

Kumaran

Huang

2012

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. Short and common web queries are aptly supported by stateof-the-art search engines but performance and user experience are degraded when web queries are longer and less common. Extending previous solutions that automatically shorten queries, we introduce searchAssist: a novel search interface that provides interactive support for difficult web queries. The query logs and questionnaires from a naturalistic study of 90 web users' search behaviors show that the usage rate of searchAssist for difficult queries was almost 40%. The results also highlight the importance of term dropping for long queries, and the improvements obtained in topical relevance when our searchers used searchAssist.

show abstract

“…Since the early use of collaborative filtering techniques in the early 1990's (Goldberg et al 1992), (Resnick et al 1994), (Shardanand and Maes 1995) collaborative or community based methods have evolved and been used to aid browsing (Wexelblat and Maes 1999), e-learning (Freyne et al 2007), and in collaborative search engines (Smyth et al 2004). White et al (White et al 2007) use the concept of "search trails", meaning the search queries and document interactions sequences performed by the users during a search session, to enhance web search. Craswell and Szummer (Craswell and Szummer 2007) applied a random walk on a graph of user click data, to help retrieve relevant documents for user searches.…”

Section: Collaborative Information Seekingmentioning

confidence: 99%

An asynchronous collaborative search system for online video search

Halvey

Vallet

Hannah

et al. 2010

Information Processing & Management

View full text Add to dashboard Cite

This version is available at https://strathprints.strath.ac.uk/52294/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the AbstractThere are a number of multimedia tasks and environments that can be collaborative in nature and involve contributions from more than one individual. Examples of such tasks include organising photographs or videos from multiple people from a large event, students working together to complete a class project, or artists and/or animators working on a production. Despite this, current state of the art applications that have been created to assist in multimedia search and organisation focus on a single user searching alone and do not take into consideration the collaborative nature of a large number of multimedia tasks. The limited work in collaborative search for multimedia applications has concentrated mostly on synchronous, and quite often co-located, collaboration between persons. However, these collaborative scenarios are not always practical or feasible. In order to overcome these shortcomings we have created an innovative system for online video search, which provides mechanisms for groups of users to collaborate both asynchronously and remotely on video search tasks. In order to evaluate our system a user evaluation was conducted. This evaluation simulated multiple conditions and scenarios for collaboration, varying on awareness, division of labour, sense making and persistence. The outcome of this evaluation demonstrates the benefit and usability of our system for asynchronous and remote collaboration between users. In addition the results of this evaluation provide a comparison between implicit and explicit collaboration in the same search system.

show abstract

Studying the use of popular destinations to enhance web search interaction

Cited by 164 publications

References 18 publications

Contextual Search: A Computational Framework

Contextual Search: A Computational Framework

Interactive Search Support for Difficult Web Queries

An asynchronous collaborative search system for online video search

Contact Info

Product

Resources

About