Visual exploration of latent ranking evolutions in time series

Rankings are everywhere in the world and they change constantly. Detecting and analyzing ranking changes in a ranked list is of great importance for recommendation and information retrieval tasks. Common to existing approaches is that the latent correlations and trends of ranked lists are not taken into account. This paper introduces RankEvo, an integration of rank structuring and visualization techniques, for detecting and analyzing latent evolutions in ranking time series. We characterize the ranking changes by computing the similarities among the time series of ranked items and organizing similar items into itemsets, and further forming ranking evolutions. The integrated RankEvo system provides visualization and intuitive interactions for exploring correlated itemsets, concurrent ranking evolutions, as well as outlier items of ranked lists. The system also employs additional information windows on demand for evolution elaboration and verification. Case studies are conducted to demonstrate the effectiveness and usability of the RankEvo system in assisting users to understand ranking changes.Graphical abstract

[1]  B. Marx.  The Visual Display of Quantitative Information , 1985 .

[2]  M. Batty.  Rank clocks , 2006, Nature.

[3]  Xin Tong,et al.  TextFlow: Towards Better Understanding of Evolving Topics in Text , 2011, IEEE Transactions on Visualization and Computer Graphics.

[4]  Xiaohua Sun,et al.  Whisper: Tracing the Spatiotemporal Process of Information Diffusion in Real Time , 2012, IEEE Transactions on Visualization and Computer Graphics.

[5]  Kwan-Liu Ma,et al.  Visual cluster exploration of web clickstream data , 2012, 2012 IEEE Conference on Visual Analytics Science and Technology (VAST).

[6]  Tamara Munzner,et al.  LiveRAC: interactive visual exploration of system management time-series data , 2008, CHI.

[7]  Ben Shneiderman,et al.  LifeLines: visualizing personal histories , 1996, CHI.

[8]  Jarke J. van Wijk,et al.  Cluster and Calendar Based Visualization of Time Series Data , 1999, INFOVIS.

[9]  Mingxuan Sun,et al.  Visualizing differences in web search algorithms using the expected weighted hoeffding distance , 2010, WWW '10.

[10]  Marc Alexa,et al.  Visualizing time-series on spirals , 2001, IEEE Symposium on Information Visualization, 2001. INFOVIS 2001..

[11]  Chandler Stolp,et al.  The Visual Display of Quantitative Information , 1983 .

[12]  Ben Shneiderman,et al.  Dynamic Query Tools for Time Series Data Sets: Timebox Widgets for Interactive Exploration , 2004, Inf. Vis..

[13]  Edward R. Tufte,et al.  The Visual Display of Quantitative Information , 1986 .

[14]  Colin Ware,et al.  Information Visualization: Perception for Design , 2000 .

[15]  T. K. Vintsyuk.  Speech discrimination by dynamic programming , 1968 .

[16]  D. Critchlow.  Metric Methods for Analyzing Partially Ranked Data , 1986 .

[17]  Wei Chen,et al.  RankExplorer: Visualization of Ranking Changes in Large Time Series Data , 2012, IEEE Transactions on Visualization and Computer Graphics.

[18]  Heidrun Schumann,et al.  Visualization of Time-Oriented Data , 2011, Human-Computer Interaction Series.

[19]  Guy Lebanon,et al.  Visualizing Incomplete and Partially Ranked Data , 2008, IEEE Transactions on Visualization and Computer Graphics.

[20]  Ben Shneiderman,et al.  The eyes have it: a task by data type taxonomy for information visualizations , 1996, Proceedings 1996 IEEE Symposium on Visual Languages.

[21]  Xiaoru Yuan,et al.  TrajRank: Exploring travel behaviour on a route by trajectory ranking , 2015, 2015 IEEE Pacific Visualization Symposium (PacificVis).

[22]  Kwan-Liu Ma,et al.  Software evolution storylines , 2010, SOFTVIS '10.

[23]  Mayer Alvo,et al.  Rank correlation methods for missing data , 1995 .

[24]  Heidrun Schumann,et al.  Axes-based visualizations with radial layouts , 2004, SAC '04.

[25]  J. Marden.  Analyzing and Modeling Rank Data , 1996 .

[26]  P. Jaccard,et al.  Etude comparative de la distribution florale dans une portion des Alpes et des Jura , 1901 .