TUTA1 at the NTCIR-11 Temporalia Task
نویسندگان
چکیده
This paper details our participation in the NTCIR-11 Temporalia task including Temporal Query Intent Classification (TQIC) and Temporal Information Retrieval (TIR). In the TQIC subtask, we explore the rich temporal information in the labeled and unlabeled search queries. Semi-supervised and supervised linear classifiers are learned to predict the temporal classes for each search query. In the TIR subtask, we perform temporal ranking based on the technique of learning-to-rank. Two classes of features are investigated for estimating the document relevance.
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