Time-Aware Exploratory Search: Exploring Word Meaning through Time

With more longitudinal archives becoming digitized and publicly available, new uses emerge. Collections that span centuries call for a time-aware exploration approach, a coordinated environment supporting understanding the development of word usage and meaning through time, with the means to leverage this for exploration. We present ongoing work on a coordinated time-aware exploratory search approach and present a case study on a prototype system. With this approach, a user is able to gain a deeper understanding of the relevant parts of the collection.

[1]  Gary Marchionini,et al.  Exploratory search , 2006, Commun. ACM.

[2]  Erez Lieberman Aiden,et al.  Quantitative Analysis of Culture Using Millions of Digitized Books , 2010, Science.

[3]  M. de Rijke,et al.  A subjunctive exploratory search interface to support media studies researchers , 2012, SIGIR '12.

[4]  Daniel A. Keim,et al.  Visual Analytics: Definition, Process, and Challenges , 2008, Information Visualization.

[5]  Heidrun Schumann,et al.  Visualizing time-oriented data - A systematic view , 2007, Comput. Graph..

[6]  Jeffrey Heer,et al.  SpanningAspectRatioBank Easing FunctionS ArrayIn ColorIn Date Interpolator MatrixInterpola NumObjecPointI Rectang ISchedu Parallel Pause Scheduler Sequen Transition Transitioner Transiti Tween Co DelimGraphMLCon IData JSONCon DataField DataSc Dat DataSource Data DataUtil DirtySprite LineS RectSprite , 2011 .

[7]  Maarten de Rijke,et al.  Exploratory Search in an Audio-Visual Archive: Evaluating a Professional Search Tool for Non-Professional Users , 2011, EuroHCIR.

[8]  M. de Rijke,et al.  Semantic Document Selection - Historical Research on Collections That Span Multiple Centuries , 2012, TPDL.

[9]  Edward Rolf Tufte,et al.  The visual display of quantitative information , 1985 .

[10]  R. Darnell Translation , 1873, The Indian medical gazette.

[11]  Hans-Peter Kriegel,et al.  'Circle Segments': A Technique for Visually Exploring Large Multidimensional Data Sets , 1996 .

[12]  Michael Gertz,et al.  Temporal Information Retrieval: Challenges and Opportunities , 2011, TWAW.

[13]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[14]  HeerJeffrey,et al.  D3 Data-Driven Documents , 2011 .

[15]  Daniel A. Keim,et al.  Visual Analytics Challenges , 2009 .

[16]  J. R. Firth,et al.  A Synopsis of Linguistic Theory, 1930-1955 , 1957 .

[17]  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.

[18]  E. LESTER SMITH,et al.  AND OTHERS , 2005 .

[19]  Jock D. Mackinlay,et al.  The structure of the information visualization design space , 1997, Proceedings of VIZ '97: Visualization Conference, Information Visualization Symposium and Parallel Rendering Symposium.