[Objective]This study aims to summarize the research status of temporal information retrieval (T-IR) and to provide theoretical basis for the study of the relevant scholars to better grasp the T-IR problems. [Coverage] We first used Google Scholar to search related literatures by typing the keywords “termporal information retireval” in Chinese and English repectively, without time limit. After getting some related literatures, we further used the retrospective method to get more related literatures. Finally, we get 92 literatures totally. [Methods] Based on method of literature survey and methods of inducting and summarizing, a survey of the existing literature on temporal information retrieval was presented from the following three aspects: extracting temporal information from document, identifying temporal information in queries and temporal ranking model. [Results] The problems and challenges existing in temporal information retrieval are as follows: little related work existing in China while most of related work existing in foreign countries; lack of methods of data collection and data indexing reflecting dynamic characteristics of real network; ignorance of the important role of the entity and event represent time information when identify the focus time of document; lack of the predicting intent for non-periodic queries and the improvement of reproducibility of temporal information retrieval model experiment to be needed. [Limitations] This paper did not review the document crawling, document index and corresponding application of temporal information retrieval. [Conclusions] The construction of standardized evaluation datasets and non-parameter temporal information retrieval models will be the future research trends of T-IR.
(归一化)期望获益指标(nEG(S))、全面性指标(Comprehensiveness Metric, C(S))、期望延迟指标(Excepted Latency Metric, E[latency])及综合以上三类评测指标的归一化期望延迟获益的调和平均值指标(Harmonic Mean of normalized EL, EGτ(S))与延迟全面性性指标(Latency Comprehensiveness, Cτ (S))
TERC 知识资源扩展任务(TRCE Knowledge Base Acceleration Track: KBA)③(③http://trec-kba.org/.)
通过时态排序筛选出与预定义实体相关的文档, 并以此 来扩展知识资源(如Wikipedia)
TREC 知识库扩展 数据集(TREC KBA Stream Corpus)
2011年10月- 2013年2月中旬
F_1准确度指标(F_1 Accuracy)与Scaled Utility指标
相关会议名称
会议主要任务
数据集内容
数据集时间跨度
实验结果评价指标
NTCIR时态信息获取任务(NTCIR Temporal Information Access Temporalia )①(①https://sites.google.com/site/ntcirtemporalia/.)
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