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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (1): 3-15    DOI: 10.11925/infotech.2096-3467.2017.01.02
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Reviews on Temporal Information Retrieval
Xiaojuan Zhang(),Yi Han
School of Computer and Information Science, Southwest University, Chongqing 400715, China
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Abstract  

[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.

Key wordsTemporal Information Retrieval      Temporal Information      Temporal Intent      Temporal Ranking     
Received: 15 August 2016      Published: 22 February 2017

Cite this article:

Xiaojuan Zhang, Yi Han. Reviews on Temporal Information Retrieval. Data Analysis and Knowledge Discovery, 2017, 1(1): 3-15.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.01.02     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I1/3

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