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数据分析与知识发现  2017, Vol. 1 Issue (1): 3-15     https://doi.org/10.11925/infotech.2096-3467.2017.01.02
  综述评介 本期目录 | 过刊浏览 | 高级检索 |
时态信息检索研究综述*
张晓娟1,2(), 韩毅1
西南大学计算机与信息科学学院 重庆 400715
Reviews on Temporal Information Retrieval
Zhang Xiaojuan(), Han Yi
School of Computer and Information Science, Southwest University, Chongqing 400715, China
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摘要 

目的】总结国内外时态信息检索研究现状, 以期为相关学者更好地把握时态信息检索研究问题提供理论基础。【文献范围】在Google Scholar中分别以检索式“Temporal Information”与“时态信息”且不限定时间范围地进行文献检索,获得部分相关文献后,再结合追溯法最终得到92篇相关文献。【方法】基于文献调研与归纳总结方法,分别从文档中时态信息抽取、查询中时态信息识别和时间感知排序三方面对时态信息检索的相关研究进行综述与评述。【结果】研究发现时态信息检索研究存在着如下问题和挑战:国外对时态检索研究比较多,而国内的相关研究甚少; 利用表征时间信息的实体与事件演化信息识别文档关注时间的相关研究不足; 缺乏对非周期变化查询的意图预测; 时态信息检索模型实验的可重复性有待提高。【局限】未对该领域的文档采集、文档索引以及相关应用进行文献综述。【结论】构建标准化的评测数据集以及无参数时态信息检索模型将是时态信息检索领域的未来方向研究。

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张晓娟
韩毅
关键词 时态信息检索时态信息时态查询意图时态感知排序    
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
收稿日期: 2016-08-15      出版日期: 2017-02-22
ZTFLH:  G350  
基金资助:*本文系国家社会科学基金青年项目“融合用户个性化与实时性意图的查询推荐模型研究”(项目编号: 15CTQ019)和西南大学博士启动基金项目“查询意图自动分类与分析研究”(项目编号: SWU114093)的研究成果之一
引用本文:   
张晓娟, 韩毅. 时态信息检索研究综述*[J]. 数据分析与知识发现, 2017, 1(1): 3-15.
Zhang Xiaojuan,Han Yi. Reviews on Temporal Information Retrieval. Data Analysis and Knowledge Discovery, 2017, 1(1): 3-15.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2017.01.02      或      http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2017/V1/I1/3
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
SemEval 2015时间与空间任务(SemEval 2015 - Time and Space Track)(①http://alt.qcri.org/semeval2015/index.php?id=tasks.) 与实体相关事件的识别; 时态性问答; 时态临床信息抽取; 空间信息识别等 新闻、论文、维基
百科、博客与临床
数据集
1960年-2014年 F1值(F1-score)、召回率(Recall)与准确率(Precision)
TREC 时态摘要任务(TREC Temporal Summarization Track)(②http://trec.nist.gov/pubs/call2016.html.) 提取某事件相关的实时性摘要信息 TREC 知识库扩展
数据集(TREC KBA Stream Corpus):
来自于新闻或者其他社交媒体中带有时间戳的文档
2011年10月-
2013年2月中旬
(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)(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 )(①https://sites.google.com/site/ntcirtemporalia/.) 时态意图消歧(Temporal Intent Disambiguation: TID); 时态信息
检索(Temporal Information Retrieval, TIR)
时态多样化检索(Temporally Diversified Retrieval:
TDR)
英文数据集: 由LivingKnowledge
项目创建的“LivingKnowledge
新闻和博客标注子
数据集”;
中文数据集: Sogou
全网新闻数据集(SogouCA)与Sogou
互联网语料库(SogouT)
英文数据集: 2011年
5月-2013年3月;
中文数据集: SogouCA, 2012年6月-2013年
7月; SogouT, 2008年
11月
TID子任务的评测指标: 平均每类别的绝对损失(Averaged Per-class Absolute Lose)与平均余弦相似度(Averaged Cosine Similarity);
TIR 子任务的评测指标: P@20、 nDCG@20与Q@20指标;
TDR子任务的评测指标: a-nDCG与D#nDCG指标
TREC微博任务中Tweet 时间表生成任务(Tweet TimeLine Generation Task of the TREC Microblog Track: TTG)(②https://github.com/lintool/twitter-tools/wiki/TREC-2015-Track-Guidelines.) 返回在时间点t之前
与查询Q相关Tweet
的摘要信息
TREC 微博数据集
(TREC Microblog Dataset)
2014年 聚类准确率(Cluster Precision))、加权聚类召回率(Weighted Cluster Recall)与非加权聚类召回率(Unweighted Cluster Recall )
  与T-IR 相关的主要评测平台
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