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AuthorMagdy, Walid
AuthorElsayed, Tamer
AuthorHasanain, Maram
Available date2021-09-07T06:16:19Z
Publication Date2016
Publication NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ResourceScopus
ISSN3029743
URIhttp://dx.doi.org/10.1007/978-3-319-30671-1_48
URIhttp://hdl.handle.net/10576/22808
AbstractTweet 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. Springer International Publishing Switzerland 2016.
Languageen
PublisherSpringer Verlag
SubjectInformation retrieval
Ranking system
Retrieval quality
Quality control
TitleOn the evaluation of tweet timeline generation task
TypeConference Paper
Pagination648-653
Volume Number9626


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