Repository logo
  • Log In
    New user? Click here to register.Have you forgotten your password?
University College Dublin
    Colleges & Schools
    Statistics
    All of DSpace
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Institutes and Centres
  3. Insight Centre for Data Analytics
  4. Insight Research Collection
  5. Towards a Novel and Timely Search and Discovery System Using the Real-Time Social Web
 
  • Details
Options

Towards a Novel and Timely Search and Discovery System Using the Real-Time Social Web

Author(s)
Phelan, Owen  
McCarthy, Kevin  
Smyth, Barry  
Uri
http://hdl.handle.net/10197/9953
Date Issued
2013-04-06
Date Available
2019-04-15T11:13:00Z
Abstract
The world of web search is changing. Mainstream search engines like Google and Bing are adding social signals to conventional query-based services while social networks like Twitter and Facebook are adding query-based search to sharing-based services. Our search and discovery system, Yokie, harnesses the wisdom of the crowd of communities of Twitter users to create indexes of proto-content (or recently shared content) that is typically not yet indexed by mainstream search engines. The system includes an architecture [13] for a range of contextual queries and ranking strategies beyond standard relevance. In this paper, we focus on evaluating Yokies ability to retrieve timely, relevant and exclusive results with which users interacted and found useful, compared to other standard web services.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
Springer
Start Page
746
End Page
757
Series
Lecture Notes in Computer Science
Copyright (Published Version)
2013 Springer-Verlag Berlin Heidelberg
Subjects

Discovery service

Discovery system

Twitter user

Ranking strategy

Social graph

DOI
10.1007/978-3-642-37401-2_72
Language
English
Status of Item
Peer reviewed
Journal
Lecture Notes in Computer Science book series (LNCS, volume 7808)
ISBN
978-3-642-37400-5
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
No Thumbnail Available
Name

insight_publication.pdf

Size

854.16 KB

Format

Adobe PDF

Checksum (MD5)

85133db101c0b4fa761a110d96f2fcd8

Owning collection
Insight Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

For all queries please contact research.repository@ucd.ie.

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement