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Jitter Search: A News-Based Real-Time Twitter Search Interface

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9626)

Abstract

In this demo we show how we can enhance real-time microblog search by monitoring news sources on Twitter. We improve retrieval through query expansion using pseudo-relevance feedback. However, instead of doing feedback on the original corpus we use a separate Twitter news index. This allows the system to find additional terms associated with the original query to find more “interesting” posts.

Keywords

Query Expansion Twitter News Original User Query Top Fragment Account Creation Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This project was supported by FCT/MEC under the projects: GoLocal CMUP-ERI/TIC/0046/2014 and NOVA LINCS PEst UID/CEC/04516/2013.

References

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    Si, L., Callan, J.: Relevant document distribution estimation method for resource selection. In: Proceedings of SIGIR 2003, pp. 298–305. ACM, New York (2003)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.NOVA LINCS, DI, Faculty of Science and TechnologyUniversidade NOVA de LisboaCaparicaPortugal
  2. 2.School of Computer Science, LTICarnegie Mellon UniversityPittsburghUSA

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