Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | SIGIR 2016 - Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval |
| Seiten | 1157-1160 |
| Seitenumfang | 4 |
| ISBN (elektronisch) | 9781450342902 |
| Publikationsstatus | Veröffentlicht - 2016 |
| Veranstaltung | 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2016 - Pisa, Italien Dauer: 17 Juli 2016 → 21 Juli 2016 |
Abstract
Manually inspecting text in a document collection to assess whether an event occurs in it is a cumbersome task. Although a manual inspection can allow one to identify and discard false events, it becomes infeasible with increasing numbers of automatically detected events. In this paper, we present a system to automatize event validation, defined as the task of determining whether a given event occurs in a given document or corpus. In addition to supporting users seeking for information that corroborates a given event, event validation can also boost the precision of automatically detected event sets by discarding false events and preserving the true ones. The system allows to specify events, retrieves candidate web documents, and assesses whether events occur in them. The validation results are shown to the user, who can revise the decision of the system. The validation method relies on a supervised model to predict the occurrence of events in a non-annotated corpus. This system can also be used to build ground-truths for event corpora.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Information systems
- Informatik (insg.)
- Software
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SIGIR 2016 - Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2016. S. 1157-1160.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Where the event lies
T2 - 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2016
AU - Ceroni, Andrea
AU - Gadiraju, Ujwal
AU - Matschke, Jan
AU - Wingert, Simon
AU - Fisichella, Marco
N1 - Publisher Copyright: © 2016 ACM.
PY - 2016
Y1 - 2016
N2 - Manually inspecting text in a document collection to assess whether an event occurs in it is a cumbersome task. Although a manual inspection can allow one to identify and discard false events, it becomes infeasible with increasing numbers of automatically detected events. In this paper, we present a system to automatize event validation, defined as the task of determining whether a given event occurs in a given document or corpus. In addition to supporting users seeking for information that corroborates a given event, event validation can also boost the precision of automatically detected event sets by discarding false events and preserving the true ones. The system allows to specify events, retrieves candidate web documents, and assesses whether events occur in them. The validation results are shown to the user, who can revise the decision of the system. The validation method relies on a supervised model to predict the occurrence of events in a non-annotated corpus. This system can also be used to build ground-truths for event corpora.
AB - Manually inspecting text in a document collection to assess whether an event occurs in it is a cumbersome task. Although a manual inspection can allow one to identify and discard false events, it becomes infeasible with increasing numbers of automatically detected events. In this paper, we present a system to automatize event validation, defined as the task of determining whether a given event occurs in a given document or corpus. In addition to supporting users seeking for information that corroborates a given event, event validation can also boost the precision of automatically detected event sets by discarding false events and preserving the true ones. The system allows to specify events, retrieves candidate web documents, and assesses whether events occur in them. The validation results are shown to the user, who can revise the decision of the system. The validation method relies on a supervised model to predict the occurrence of events in a non-annotated corpus. This system can also be used to build ground-truths for event corpora.
KW - Corpus construction
KW - Evaluation
KW - Event detection
KW - Event validation
UR - http://www.scopus.com/inward/record.url?scp=84980343524&partnerID=8YFLogxK
U2 - 10.1145/2911451.2911452
DO - 10.1145/2911451.2911452
M3 - Conference contribution
AN - SCOPUS:84980343524
SP - 1157
EP - 1160
BT - SIGIR 2016 - Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval
Y2 - 17 July 2016 through 21 July 2016
ER -