Top

Journal of Visualization

Published in:

10-07-2020 | Regular Paper

TargetingVis: visual exploration and analysis of targeted advertising data

Authors: Di Peng, Wei Tian, Min Zhu, Yukun Ren, Xiaojian Lin, Mingzhao Li

Published in: Journal of Visualization | Issue 6/2020

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Targeted advertising is a dominant form of online advertising. It considers advertisers’ major concern of their customers, including the consumers’ certain traits, interests and individual preferences. To promote the effectiveness of advertisement delivery, advertising analysts need to understand advertiser delivery behavior and problems in targeting structure. However, statistical methods cannot meet analytical requirements completely, and analysts have to spend a lot of time reading countless data reports. Concretely, there is no efficient tool accomplishing analysis tasks such as exploring targeting usage at different levels, discovering useful or abnormal targeting combination patterns, finding competition from user behavior. In this paper, we design and implement an interactive visual analytics system named TargetingVis to visualize targeted advertising delivery data to face the challenges. After conducting a detailed requirements analysis with the domain experts from Tencent Inc., we design TargetingVis with four linked views: a novel chord diagram for cross-level exploration of targeting relations, a view for delving into the analysis of targeting combination patterns, an auxiliary view for displaying data indicators and a view to help gain insights into the behavior of advertisers. Finally, we evaluate the usability and efficiency through experiments based on real-world datasets.

Graphic abstract

previous article Visual extraction system for insulators on power transmission lines from UAV photographs using support vector machine and color models

next article AirExplorer: visual exploration of air quality data based on time-series querying

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Addis A, Armano G, Giuliani A, Vargiu E (2010) A recommender system based on a generic contextual advertising approach. In: Proceedings of the 15th IEEE symposium on computers and communications, pp 859–861. https://doi.org/10.1109/ISCC.2010.5546548

Armano G, Giuliani A, Vargiu E (2011) Studying the impact of text summarization on contextual advertising. In: 2011 database and expert systems applications, pp 172–176. https://doi.org/10.1109/DEXA.2011.78

Bergemann D, Bonatti A (2011) Targeting in advertising markets: implications for offline versus online media. RAND J Econ 42(3):417–443. https://doi.org/10.1111/j.1756-2171.2011.00143.xCrossRef

Blascheck T, Beck F, Baltes S, Ertl T, Weiskopf D (2016) Visual analysis and coding of data-rich user behavior. In: 2016 IEEE conference on visual analytics science and technology, pp 141–150. https://doi.org/10.1109/VAST.2016.7883520

Chen Y, Pavlov D, Canny JF (2009) Large-scale behavioral targeting. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining, pp 209–218. https://doi.org/10.1145/1557019.1557048

Chen H, Chen W, Mei H, Liu Z, Zhou K, Chen W, Gu W, Ma K (2014) Visual abstraction and exploration of multi-class scatterplots. IEEE Trans Vis Comput Graph 20(12):1683–1692. https://doi.org/10.1109/TVCG.2014.2346594CrossRef

Chen Y, Zhang X, Feng Y, Liang J, Chen H (2015) Sunburst with ordered nodes based on hierarchical clustering: a visual analyzing method for associated hierarchical pesticide residue data. J Vis 18(2):237–254. https://doi.org/10.1007/s12650-014-0269-3CrossRef

Chen W, Lu J, Kong D, Liu Z, Shen Y, Chen Y, He J, Liu S, Qi Y, Wu Y (2017) GameLifeVis: visual analysis of behavior evolutions in multiplayer online games. J Vis 20(3):651–665. https://doi.org/10.1007/s12650-016-0416-0CrossRef

Chen Q, Yue X, Plantaz X, Chen Y, Shi C, Pong TC, Qu H (2018) ViSeq: visual analytics of learning sequence in massive open online courses. IEEE Trans Vis Comput Graph. https://doi.org/10.1109/TVCG.2018.2872961CrossRef

Chen S, Chen S, Wang Z, Liang J, Wu Y, Yuan X (2019a) D-Map+: interactive visual analysis and exploration of ego-centric and event-centric information diffusion patterns in social media. ACM TIST 10(1):11:1–11:26

Chen W, Xia J, Wang X, Wang Y, Chen J, Chang L (2019b) Relationlines: visual reasoning of egocentric relations from heterogeneous urban data. ACM TIST 10(1):2:1–2:21. https://doi.org/10.1145/3200766CrossRef

Gou L, Zhang XL (2011) Treenetviz: revealing patterns of networks over tree structures. IEEE Trans Vis Comput Graph 17(12):2449–2458. https://doi.org/10.1109/TVCG.2011.247CrossRef

Hofmann J, Größler M, Rubio-Sánchez M, Pichler P, Lehmann DJ (2017) Visual exploration of global trade networks with time-dependent and weighted hierarchical edge bundles on GPU. Comput Graph Forum 36(3):273–282. https://doi.org/10.1111/cgf.13186CrossRef

Hojjat SA, Turner J, Cetintas S, Yang J (2017) A unified framework for the scheduling of guaranteed targeted display advertising under reach and frequency requirements. Oper Res 65(2):289–313. https://doi.org/10.1287/opre.2016.1567MathSciNetCrossRefMATH

Holten D (2006) Hierarchical edge bundles: visualization of adjacency relations in hierarchical data. IEEE Trans Vis Comput Graph 12(5):741–748. https://doi.org/10.1109/TVCG.2006.147CrossRef

Jin Y, Seipp K, Duval E, Verbert K (2016) Go with the flow: effects of transparency and user control on targeted advertising using flow charts. In: Proceedings of the international working conference on advanced visual interfaces, pp 68–75. https://doi.org/10.1145/2909132.2909269

Lu M, Meng D, Peng Y, Li Y, Zhao Y, Fan X, Zhou F (2016) A visual analytics approach for exploring individual behaviors in smartphone usage data. In: 2016 IEEE pacific visualization symposium, pp 224–228. https://doi.org/10.1109/PACIFICVIS.2016.7465275

Malheiros M, Jennett C, Patel S, Brostoff S, Sasse MA (2012) Too close for comfort: a study of the effectiveness and acceptability of rich-media personalized advertising. In: CHI conference on human factors in computing systems, pp 579–588. https://doi.org/10.1145/2207676.2207758

Nguyen PH, Henkin R, Chen S, Andrienko NV, Andrienko GL, Thonnard O, Turkay C (2020) VASABI: hierarchical user profiles for interactive visual user behaviour analytics. IEEE Trans Vis Comput Graph 26(1):77–86. https://doi.org/10.1109/TVCG.2019.2934609CrossRef

O’Donnell K, Cramer H (2015) People’s perceptions of personalized ads. In: Proceedings of the 24th international conference on world wide web companion, pp 1293–1298. https://doi.org/10.1145/2740908.2742003

Saia R, Boratto L, Carta S (2015) A latent semantic pattern recognition strategy for an untrivial targeted advertising. In: 2015 IEEE international congress on big data, pp 491–498. https://doi.org/10.1109/BigDataCongress.2015.78

Vargiu E, Giuliani A, Armano G (2013) Improving contextual advertising by adopting collaborative filtering. TWEB 7(3):13:1–13:22. https://doi.org/10.1145/2516633.2516635CrossRef

Vehlow C, Beck F, Weiskopf D (2016) Visualizing dynamic hierarchies in graph sequences. IEEE Trans Vis Comput Graph 22(10):2343–2357. https://doi.org/10.1109/TVCG.2015.2507595CrossRef

Wang G, Zhang X, Tang S, Zheng H, Zhao BY (2016) Unsupervised clickstream clustering for user behavior analysis. In: Proceedings of the 2016 CHI conference on human factors in computing systems, pp 225–236. https://doi.org/10.1145/2858036.2858107

Yan J, Liu N, Wang G, Zhang W, Jiang Y, Chen Z (2009) How much can behavioral targeting help online advertising? In: Proceedings of the 18th international conference on world wide web, pp 261–270. https://doi.org/10.1145/1526709.1526745

Yue X, Shu X, Zhu X, Du X, Yu Z, Papadopoulos D, Liu S (2019) Bitextract: interactive visualization for extracting bitcoin exchange intelligence. IEEE Trans Vis Comput Graph 25(1):162–171. https://doi.org/10.1109/TVCG.2018.2864814CrossRef

Zhang Z, Wang B, Ahmed F, Ramakrishnan IV, Zhao R, Viccellio A, Mueller K (2013) The five Ws for information visualization with application to healthcare informatics. IEEE Trans Vis Comput Graph 19(11):1895–1910. https://doi.org/10.1109/TVCG.2013.89CrossRef

Title: TargetingVis: visual exploration and analysis of targeted advertising data
Authors: Di Peng
Wei Tian
Min Zhu
Yukun Ren
Xiaojian Lin
Mingzhao Li
Publication date: 10-07-2020
Publisher: Springer Berlin Heidelberg
Published in: Journal of Visualization / Issue 6/2020
Print ISSN: 1343-8875
Electronic ISSN: 1875-8975
DOI: https://doi.org/10.1007/s12650-020-00671-w

Springer Professional

Abstract

Graphic abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Other articles of this Issue 6/2020

Application of feature matching trajectory detection algorithm for particle streak velocimetry

Visual analysis of retailing store location selection

Flow patterns of dual-incident shock waves/turbulent boundary layer interaction

Visual analytics and prediction system based on deep belief networks for icing monitoring data of overhead power transmission lines

Transient mapping of high-pressure impinging spray boundary contour on stepped geometries

SADIRE: a context-preserving sampling technique for dimensionality reduction visualizations

Premium Partner