On the Evaluation of Tweet Timeline Generation Task

Walid Magdy, Tamer Elsayed, Maram Hasanain

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Tweet Timeline Generation (TTG) task aims to generate a timeline of relevant but novel tweets that summarizes the development of a given topic. A typical TTG system first retrieves tweets then detects novel tweets among them to form a timeline. In this paper, we examine the dependency of TTG on retrieval quality, and its effect on having biased evaluation. Our study showed a considerable dependency, however, ranking systems is not highly affected if a common retrieval run is used.
Original languageEnglish
Title of host publicationAdvances in Information Retrieval
Subtitle of host publication38th European Conference on IR Research, ECIR 2016, Padua, Italy, March 20-23, 2016. Proceedings
PublisherSpringer International Publishing
Pages648-653
Number of pages6
ISBN (Electronic)978-3-319-30671-1
ISBN (Print)978-3-319-30670-4
DOIs
Publication statusPublished - Mar 2016
Event38th European Conference on Information Retrieval - Padua, Italy
Duration: 20 Mar 201623 Mar 2016
http://ecir2016.dei.unipd.it/

Publication series

NameLecture Notes in Computer Science (LNCS)
PublisherSpringer International Publishing
Volume9626
ISSN (Print)0302-9743

Conference

Conference38th European Conference on Information Retrieval
Abbreviated titleECIR 2016
Country/TerritoryItaly
CityPadua
Period20/03/1623/03/16
Internet address

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