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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (7): 35-43    DOI: 10.11925/infotech.2096-3467.2017.07.05
Orginal Article Current Issue | Archive | Adv Search |
Review of Information Retrieval Research: Case Study of Conference Papers
Yang Chaofan(), Deng Zhonghua, Peng Xin, Liu Bin
School of Information Management, Wuhan University, Wuhan 430072, China
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Abstract  

[Objective] This paper reviews conference papers on information retrieval, aiming to identify the research hotspots and development trends in this field. [Coverage] Papers published by ACL, ACMMM, ICML, KDD, and SIGIR from 2012 to 2016. [Methods] We first collected these papers’ abstracts and keywords to process them with word segmentation package. Then, we analyzed these data with statistic tests. [Results] We found that mobile search was the most popular topic and the information retrieval models had been optimized. Filtering and recommending received more attention from the researchers. Information retrieval studies established close ties with artificial intelligence. User’s privacy protection and health information retrieval were also popular. [Limitations] Only collected the abstracts and keywords. More research is needed to study the full texts and citations. [Conclusions] This paper presents the latest developments of information retrieval research.

Key wordsInformation Retrieval      Conference Papers      Research Hotspots      Development Trends     
Received: 22 May 2017      Published: 13 September 2017
ZTFLH:  G250  

Cite this article:

Yang Chaofan,Deng Zhonghua,Peng Xin,Liu Bin. Review of Information Retrieval Research: Case Study of Conference Papers. Data Analysis and Knowledge Discovery, 2017, 1(7): 35-43.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.07.05     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I7/35

序号 热点词 总词频 各年度热点词频次
2012 2013 2014 2015 2016
1 神经网络 394 9 19 81 110 175
2 机器学习 386 45 72 72 87 110
3 社交网络 379 109 81 56 83 50
4 社交媒体 358 66 76 51 71 66
5 搜索引擎 315 73 70 69 79 24
6 信息检索 196 35 41 65 55 39
7 数据挖掘 148 43 31 31 28 15
8 图像检索 128 41 28 22 24 11
9 自然语言处理 126 6 10 7 52 51
10 主题模型 112 22 48 13 13 26
11 监督式学习 109 30 20 22 16 21
12 网页搜索 101 11 30 29 22 10
13 推荐系统 100 20 25 23 20 12
14 深度学习 88 5 5 11 18 49
15 视频搜索 88 27 20 17 14 10
16 事件检测 87 14 18 6 28 21
17 音乐搜索 86 11 14 15 21 24
18 协同过滤 82 14 22 19 16 11
19 特征选择 75 27 14 14 12 8
20 矩阵分解 75 21 22 16 10 6
21 主动学习 73 26 21 13 7 6
22 情感分析 68 16 8 10 14 20
23 语言模型 67 17 19 10 12 9
24 分词技术 65 6 14 20 13 12
25 增强学习 63 18 7 9 6 23
年度

会议 主题
2012 2013 2014 2015 2016
ACL 机器翻译; 数据挖掘; 信息抽取; 问答系统; 文本分类; 自然语言处理应用 观点挖掘; 机器翻译; 自然语言处理应用; 问答系统; 机器学习; 文本分类; 信息抽取; 机器翻译; 自然语言处理; 分词技术与词性标注; 情感分析; 机器学习; 问答系统 神经网络; 机器学习; 信息抽取; 机器翻译; 问答系统; 自然语言处理; 主题模型 问答系统; 信息抽取; 神经网络; 机器翻译; 深度学习; 语义分析; 情感分析; 文本分类;
ACMMM 多媒体推荐; 持续性情感分析; 基于内容的图像检索; 大规模搜索; 人脸识别; 社交媒体 行为与事件识别; 多峰分析; 社会动力学; 相似性搜索; 情境感知; 音乐与戏剧分析 行为与事件识别; 深度学习; 人机交互; 多媒体分析与挖掘; 隐私与健康; 多媒体推荐; 移动搜索 多媒体标引与搜索; 行为与事件识别; 多媒体质量感知; 人机交互; 虚拟现实与增强现实; 移动设备 人脸与情感识别; 视频搜索; 深度学习; 虚拟现实与增强现实; 隐私与健康; 人机
交互
ICML 聚类分析; 增强学习; 神经网络与深度学习; 优化算法; 隐私与保密; 监督式学习; 概率模型 增强学习; 深度学习; 社交网络; 主题模型; 支持向量机与决策树; 聚类分析; 优化算法; 矩阵分解 深度学习; 增强学习; 结构化预测; 聚类分析; 特征选择; 神经网络; 矩阵分解; 主题模型 深度学习; 概率模型; 增强学习; 结构化预测; 时间序列分析; 特征选择; 隐私研究; 聚类分析 神经网络与深度学习; 增强学习; 矩阵分解; 大数据; 监督式学习; 隐私研究; 图解模型; 聚类分析
KDD 网页级别与社交媒体; 模式挖掘; 概率模型; 监督式学习; 网站应用; 个性化推荐 文档与主题模型; 社交媒体; 大数据框架; 图像挖掘; 医疗与生活; 深度学习; 推荐系统 医疗与安全; 监督式学习; 社交媒体; 特征选择; 文本挖掘; 隐私与保密; 主题模型; 移动设备 大数据; 主题模型; 隐私与保密; 移动设备; 知识发现; 医疗健康; 模式挖掘; 推荐系统; 电子商务 图像与社交网络; 深度学习; 聚类分析; 推荐系统; 用户行为模型; 优化算法; 电子商务
SIGIR 多媒体; 检索评价; 推荐系统; 搜索日志分析; 社交媒体; 个性化与用户模型; 搜索效率; 文本分类 社交媒体; 推荐系统; 主题模型; 多媒体检索; 用户行为; 文本分类; 电子商务; 相似性搜索; 移动搜索 社交媒体; 移动搜索; 标引与搜索效率; 用户与模型; 情感分析; 引用推荐; 搜索满意度; 搜索风险评估; 哈希算法 多媒体搜索; 搜索体验; 社交媒体; 用户模型; 分类与排名; 深度学习; 任务与设备; 电子商务; 移动搜索 检索模型; 音乐与数学; 隐私、广告与产品; 行为模型与应用; 移动设备; 实体与知识图谱; 问答系统; 多媒体搜索
[1] 司莉, 庄晓喆, 贾欢. 近10年来国外多语言信息组织与检索研究进展与启示[J]. 中国图书馆学报, 2015, 41(4): 112-126.
doi: 10.13530/j.cnki.jlis.150022
[1] (Si Li, Zhuang Xiaozhe, Jia Huan.A Review of Multilingual Information Organization and Retrieval Research Abroad in the Last Ten Years[J]. Journal of the Library Science in China, 2015, 41(4): 112-126.)
doi: 10.13530/j.cnki.jlis.150022
[2] 吴丹, 邱瑾. 国外协同信息检索行为研究述评[J]. 中国图书馆学报, 2012, 38(6): 100-110.
doi: 10.3969/j.issn.1001-8867.2012.06.011
[2] (Wu Dan, Qiu Jin.A Review on Foreign Studies of Collaborative Information Seeking Behavior[J]. Journal of the Library Science in China, 2012, 38(6): 100-110.)
doi: 10.3969/j.issn.1001-8867.2012.06.011
[3] 杨海锋. 用户行为在信息检索中的研究现状及发展动态评述[J]. 图书情报知识, 2015(6): 79-88.
doi: 10.13366/j.dik.2015.06.079
[3] (Yang Haifeng.Review on the Research Status and Development Trend of Users Behavior in Information Retrieval[J]. Document, Information & Knowledge, 2015(6): 79-88.)
doi: 10.13366/j.dik.2015.06.079
[4] 窦永香, 苏山佳, 赵捧未. 信息检索研究的发展与动向——对 ACM SIGIR信息检索年会的主题分析[J]. 情报理论与实践, 2010, 33(7): 124-128.
[4] (Dou Yongxiang, Su Shanjia, Zhao Pengwei.Progress and Development Trend in the Study of Information Retrieval[J]. Information Studies: Theory & Application, 2010, 33(7): 124-128.)
[5] 陈少涌, 李广建. 近十年来信息检索研究发展动向——基于SIGIR年会主题及论文集的统计分析[J]. 情报科学, 2015, 33(5): 150-156.
[5] (Chen Shaoyong, Li Guangjian.Research on Information Retrieval over the Last Decade: Analysis of SIGIR Annual Conferences’ Research Topics and Proceedings[J]. Information Science, 2015, 33(5): 150-156.)
[6] Casey M A, Veltkamp R, Goto M, et al.Content-Based Music Information Retrieval: Current Directions and Future Challenges[J]. Proceedings of the IEEE, 2008, 96(4): 668-696.
doi: 10.1109/JPROC.2008.916370
[7] Kishida K.Technical Issues of Cross-language Information Retrieval: A Review[J]. Information Processing and Management, 2005, 41(3): 433-455.
doi: 10.1016/j.ipm.2004.06.007
[8] Enser P.The Evolution of Visual Information Retrieval[J]. Journal of Information Science, 2008, 34(4): 531-546.
doi: 10.1177/0165551508091013
[9] Smeaton A F, Keogh G, Gurrin C, et al.Analysis of Papers from Twenty-Five Years of SIGIR Conferences: What Have We been Doing for the Last Quarter of a Century?[J]. ACM SIGIR Forum, 2002, 36(2): 39-43.
doi: 10.1145/792550
[10] Hiemstra D, Hauff C, Jong F.SIGIR’s 30th Anniversary: An Analysis of Trends in IR Research and the Topology of Its Community[J]. ACM SIGIR Forum, 2007, 41(2): 18-24.
doi: 10.1145/1328964.1328966
[11] Christopher D, Surdeanu M, Bauer J, et al.The Stanford CoreNLP Natural Language Processing Toolkit[C]// Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations.2014.
[12] Park D C, El-Sharkawi M A, Marks R J, et al. Electric Load Forecasting Using an Artificial Neural Network[J]. IEEE Transactions on Power Engineering, 1991, 6(2): 442-449.
[13] Pineda F J.Generalization of Back-Propagation to Recurrent Neural Networks[J]. Physical Review Letters, 1987, 59(19): 2229-2232.
doi: 10.1103/PhysRevLett.59.2229 pmid: 10035458
[14] Krizhevsky A, Sutskever, B, Hinton G E. ImageNet Classification with Deep Convolutional Neural Networks[C]// Proceedings of the 2012 Advances in Neural Information Processing Systems.2012.
[15] Yann L, Bengio Y, Hinton G.Deep Learning[J]. Nature, 2015, 521: 436-444.
doi: 10.1038/nature14539
[16] Guyon I, Elisseeff A.An Introduction to Variable and Feature Selection[J]. Journal of Machine Learning Research, 2003, 3(6): 1157-1182.
[17] Koren Y, Bell R, Volinsky C.Matrix Factorization Techniques for Recommender Systems[J]. IEEE Computer Society, 2009, 42(8): 30-37.
doi: 10.1109/MC.2009.263
[18] 董士海. 人机交互的进展及面临的挑战[J]. 计算机辅助设计与图形学学报, 2004, 16(1): 1-12.
doi: 10.3321/j.issn:1003-9775.2004.01.001
[18] (Dong Shihai.Progress and Challenge of Human-Computer Interaction[J]. Journal of Computer-Aided Design & Computer Graphics, 2004, 16(1): 1-12.)
doi: 10.3321/j.issn:1003-9775.2004.01.001
[19] Steuer J.Defining Virtual Reality: Dimensions Determining Telepresence[J]. Journal of Communication, 1992, 42(4): 73-93.
doi: 10.1111/j.1460-2466.1992.tb00812.x
[20] Azuma R T.A Survey of Augmented Reality[J]. Teleoperators and Virtual Environments, 1997, 6(4): 355-385.
doi: 10.1162/pres.1997.6.4.355
[21] Davis J, Costa V S, Peissig P, et al.Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events[C]//Proceedings of the 29th International Conference on Machine Learning, Edinburgh, Scotland, UK. 2012.
[22] Wang Y, Wipf D, Ling Q, et al.Multi-Task Learning for Subspace Segmentation[C]//Proceedings of the 32nd International Conference on Machine Learning, Lille, France. 2015.
[23] 任磊. 推荐系统关键技术研究[D]. 上海: 华东师范大学, 2012.
[23] (Ren Lei.Research on Some Key Issues of Recommender Systems [D]. Shanghai: East China Normal University, 2012.)
[24] Grbovic M, Djuric N, Radosavljevic V, et al.Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising[C]//Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval.2016: 375-384.
[25] Cheng Z, Shen J, Hoi S.On Effective Personalized Music Retrieval by Exploring Online User Behaviors[C]// Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2016: 125-134.
[26] Lv Y, Lymberopoulos D, Wu Q.An Exploration of Ranking Heuristics in Mobile Local Search[C]//Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2012: 295-304.
[27] Lagun D, Hsieh C H, Webster D, et al.Towards Better Measurement of Attention and Satisfaction in Mobile Search[C]//Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2014: 113-122.
[28] Williams K, Kiseleva J, Crook A C, et al.Is This Your Final Answer? Evaluating the Effect of Answers on Good Abandonment in Mobile Search[C]//Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval.2016: 889-892.
[29] 孙坦, 周静怡. 近几年来国外信息检索模型研究进展[J]. 图书馆建设, 2008(3): 82-85.
[29] (Sun Tan, Zhou Jingyi.The Review of Information Retrieval Models in Recent Years[J]. Library Development, 2008 (3): 82-85.)
[30] Tsagkias M, Blanco R.Language Intent Models for Inferring User Browsing Behavior[C]//Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval.2012: 335-344.
[31] Chen H, Cooper M, Joshi D, et al.Multi-modal Language Models for Lecture Video Retrieval[C]//Proceedings of the 22nd ACM International Conference on Multimedia.2014: 1081-1084.
[32] Raviv H, Kurland O, Carmel D.Document Retrieval Using Entity-Based Language Models[C]//Proceedings of the 39th International ACM SIGIR Conference on Research & Development in Information Retrieval.2016: 65-74.
[33] Zhao J, Huang J.An Enhanced Context-Sensitive Proximity Model for Probabilistic Information Retrieval[C]// Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval. 2014: 1131-1134.
[34] Goldberg D, Nichols D, Oki B M, et al.Using Collaborative Filtering to Weave an Information Tapestry[J]. Communications of the ACM, 1992, 35(12): 61-70.
[35] Shih T Y, Hou T C, Jiang J D, et al.Dynamically Integrating Item Exposure with Rating Prediction in Collaborative Filtering[C]//Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval.2016: 813-816.
[36] Hayashi K, Maehara T, Toyoda M, et al.Real-Time Top-R Topic Detection on Twitter with Topic Hijack Filtering[C]// Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2015: 417-426.
[37] Lu W, Chung F.Computational Creativity Based Video Recommendation[C]//Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2016: 793-796.
[38] Mao K, Fan J, Shou L, et al.Song Recommendation for Social Singing Community[C]//Proceedings of the 22nd ACM International Conference on Multimedia. 2014: 127-136.
[39] Lu Y C, Wu C W, Lu C W, et al.An Unsupervised Approach to Anomaly Detection in Music Datasets[C]//Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval.2016: 749-752.
[40] Zhou G, Zeng Z, Huang J, et al.Transfer Learning for Cross-Lingual Sentiment Classification with Weakly Shared Deep Neural Networks[C]//Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval.2016: 245-254.
[41] Yan R, Song Y, Wu H.Learning to Respond with Deep Neural Networks for Retrieval-Based Human-Computer Conversation System[C]//Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval.2016: 55-64.
[42] Zerr S, Siersdorfer S, Hare J, et al.Privacy-Aware Image Classification and Search[C]//Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval.2012: 35-44.
[43] Dwork C, McSherry F, Nissim K, et al. Calibrating Noise to Sensitivity in Private Data Analysis[C]//Proceedings of the 3rd Theory of Cryptography Conference. 2006: 265-284.
[44] Zhang S, Yang H, Singh L.Anonymizing Query Logs by Differential Privacy[C]//Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2016: 753-756.
[45] Ahmad W U, Wang H.Topic Model Based Privacy Protection in Personalized Web Search[C]//Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2016: 1025-1028.
[46] Schoenherr G P, White R W.Interactions Between Health Searchers and Search Engines[C]//Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2014: 143-152.
[47] Sidana S, Mishra S, Amer-Yahia S, et al.Health Monitoring on Social Media over Time[C]//Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2016: 849-855.
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