TY - GEN
T1 - On the evaluation of tweet timeline generation task
AU - Magdy, Walid
AU - Elsayed, Tamer
AU - Hasanain, Maram
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/84962508027
U2 - 10.1007/978-3-319-30671-1_48
DO - 10.1007/978-3-319-30671-1_48
M3 - Conference contribution
AN - SCOPUS:84962508027
SN - 9783319306704
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 648
EP - 653
BT - Advances in Information Retrieval - 38th European Conference on IR Research, ECIR 2016, Proceedings
A2 - Moens, Marie-Francine
A2 - Ferro, Nicola
A2 - Silvello, Gianmaria
A2 - di Nunzio, Giorgio Maria
A2 - Hauff, Claudia
A2 - Crestani, Fabio
A2 - Mothe, Josiane
A2 - Silvestri, Fabrizio
PB - Springer Verlag
T2 - 38th European Conference on Information Retrieval Research, ECIR 2016
Y2 - 20 March 2016 through 23 March 2016
ER -