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- W2294990410 abstract "According to the organizers, the objective of the 2014 CLEF- INEX Tweet Contextualization Task is: ...The Tweet Contextualization aims at providing automatically information - a summary that explains the tweet. This requires combining multiple types of processing from in- formation retrieval to multi-document summarization including entity linking. We present three statistical summarizer systems applied to the CLEF-INEX 2014 task. Cortex summarizer uses several sentence selec- tion metrics and an optimal decision module to score sentences from a document source. Artex summarizer uses a simple inner product among the topic-vector and the pseudo-word vector. Reg summarizer is a per- formant graph-based summarizer. The results show that our systems performed well on CLEF-INEX task. Our three systems have obtained the rst rank in the INEX manual evaluation." @default.
- W2294990410 created "2016-06-24" @default.
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- W2294990410 date "2014-01-01" @default.
- W2294990410 modified "2023-09-27" @default.
- W2294990410 title "Three Statistical Summarizers at CLEF-INEX 2014 Tweet Contextualization Track" @default.
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