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Issue No.05 - May (2011 vol.17)
pp: 557-569
Steffen Koch , University of Stuttgart, Stuttgart
Harald Bosch , University of Stuttgart, Stuttgart
Mark Giereth , University of Stuttgart, Stuttgart
Thomas Ertl , University of Stuttgart, Stuttgart
Patents are of growing importance in current economic markets. Analyzing patent information has, therefore, become a common task for many interest groups. As a prerequisite for patent analysis, extensive search for relevant patent information is essential. Unfortunately, the complexity of patent material inhibits a straightforward retrieval of all relevant patent documents and leads to iterative, time-consuming approaches in practice. Already the amount of patent data to be analyzed poses challenges with respect to scalability. Further scalability issues arise concerning the diversity of users and the large variety of analysis tasks. With "PatViz,” a system for interactive analysis of patent information has been developed addressing scalability at various levels. PatViz provides a visual environment allowing for interactive reintegration of insights into subsequent search iterations, thereby bridging the gap between search and analytic processes. Because of its extensibility, we expect that the approach we have taken can be employed in different problem domains that require high quality of search results regarding their completeness.
Visual analytics, graphical user interfaces, information search and retrieval.
Steffen Koch, Harald Bosch, Mark Giereth, Thomas Ertl, "Iterative Integration of Visual Insights during Scalable Patent Search and Analysis", IEEE Transactions on Visualization & Computer Graphics, vol.17, no. 5, pp. 557-569, May 2011, doi:10.1109/TVCG.2010.85
[1] Economic Studies, Statistics and Analysis Division, World Intellectual Property Organization (WIPO), World Intellectual Property Indicators, 2009 Edition, 2009.
[2] S. Koch, H. Bosch, M. Giereth, and T. Ertl, “Iterative Integration of Visual Insights during Patent Search and Analysis,” Proc. IEEE Symp. Visual Analytics Science and Technology (VAST '09), pp. 203-210, Oct. 2009.
[3] C.D. Manning, P. Raghavan, and H. Schütze, Introduction to Information Retrieval. Cambridge Univ. Press, 2008.
[4] L. Wanner, R. Baeza-Yates, S. Brügmann, J. Codina, B. Diallo, E. Escorsa, M. Giereth, Y. Kompatsiaris, S. Papadopoulos, E. Pianta, G. Piella, I. Puhlmann, G. Rao, M. Rotard, P. Schoester, L. Serafini, and V. Zervaki, “Towards Content-Oriented Patent Document Processing,” World Patent Information, vol. 30, no. 1, pp. 21-33, 2008.
[5] Illuminating the Path: The Research and Development Agenda for Visual Analytics, J.J. Thomas and K.A. Cook, eds. Nat'l Visualization and Analytics Center, 2005.
[6] J. Codina, E. Pianta, S. Vrochidis, and S. Papadopoulos, “Integration of Semantic, Metadata and Image Search Engines with a Text Search Engine for Patent Retrieval,” Proc. Workshop SemSearch, S. Bloehdorn, M. Grobelnik, P. Mika, and D.T. Tran, eds., pp. 14-28, 2008.
[7] A. Potrich and E. Pianta, “L-ISA: Learning Domain Specific Isa-Relations from the Web,” Proc. Sixth Int'l Conf. Language Resources and Evaluation (LREC), 2008.
[8] B. Shneiderman, “The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations,” Proc. IEEE Symp. Visual Languages, pp. 336-343, Sept. 1996.
[9] J. Roberts, “State of the Art: Coordinated & Multiple Views in Exploratory Visualization,” Proc. Fifth Int'l Conf. Coordinated and Multiple Views in Exploratory Visualization 2007. (CMV '07), pp. 61-71, July 2007.
[10] H.G. Small, “Co-Citation in the Scientific Literature: A New Measure of the Relationship between Two Documents,” J. Am. Soc. for Information Science, vol. 24, no. 4, pp. 265-269, 1973.
[11] A. Jaffe and M. Trajtenberg, Patents, Citations & Innovations. MIT Press, 2002.
[12] L. Reeve, H. Han, and C. Chen, “Information Visualization and the Semantic Web,” Visualizing the Semantic Web, V. Geroimenko and C. Chen, eds., Springer, 2006.
[13] D. Kutz, “Examining the Evolution and Distribution of Patent Classifications,” Proc. Eighth Int'l Conf. Information Visualisation 2004 (IV '04), pp. 983-988, July 2004.
[14] B. Shneiderman, “Tree Visualization with Tree-Maps: 2-d Space-Filling Approach,” ACM Trans. Graphics, vol. 11, no. 1, pp. 92-99, 1992.
[15] C. Stolte, D. Tang, and P. Hanrahan, “Polaris: A System for Query, Analysis, and Visualization of Multidimensional Relational Databases,” IEEE Trans. Visualization and Computer Graphics, vol. 8, no. 1, pp. 52-65, Jan.-Mar. 2002.
[16] R. Chang, A. Lee, M. Ghoniem, R. Kosara, W. Ribarsky, J. Yang, E. Suma, C. Ziemkiewicz, D. Kern, and A. Sudjianto, “Scalable and Interactive Visual Analysis of Financial Wire Transactions for Fraud Detection,” Information Visualization, vol. 7, no. 1, pp. 63-76, 2008.
[17] J. Stasko, C. Görg, and Z. Liu, “Jigsaw: Supporting Investigative Analysis through Interactive Visualization,” Information Visualization, vol. 7, no. 2, pp. 118-132, 2008.
[18] P.C. Wong, B. Hetzler, C. Posse, M. Whiting, S. Havre, N. Cramer, A. Shah, M. Singhal, A. Turner, and J. Thomas, “IN-SPIRE Infovis 2004 Contest Entry,” Proc. IEEE Symp. Information Visualization, Oct. 2004.
[19] C. Ahlberg and B. Shneiderman, “Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Starfield Displays,” Proc. ACM SIGCHI, pp. 313-317, 1994.
[20] A. Spoerri, “Infocrystal,” Proc. ACM SIGCHI, pp. 11-12, 1994.
[21] R. Baeza-Yates, G. Navarro, J. Vegas, and P. De La Fuente, “A Model and a Visual Query Language for Structured Text,” Proc. Symp. String Processing and Information Retrieval: A South Am. Symp., pp. 7-13, Sept. 1998.
[22] N. Elmqvist, J. Stasko, and P. Tsigas, “DataMeadow: A Visual Canvas for Analysis of Large-Scale Multivariate Data,” Information Visualization, vol. 7, no. 1, pp. 18-33, 2008.
[23] T. Catarci, M.F. Costabile, S. Levialdi, and C. Batini, “Visual Query Systems for Databases: A Survey,” J. Visual Languages and Computing, vol. 8, no. 2, pp. 215-260, 1997.
[24] Y. Chen, J. Yang, and W. Ribarsky, “Toward Effective Insight Management in Visual Analytics Systems,” Proc. IEEE Pacific Visualization Symp. 2009 (PacificVis '09), pp. 49-56, Apr. 2009.
[25] F. Viegas, M. Wattenberg, F. van Ham, J. Kriss, and M. McKeon, “ManyEyes: A Site for Visualization at Internet Scale,” IEEE Trans. Visualization and Computer Graphics, vol. 13, no. 6, pp. 1121-1128, Nov./Dec. 2007.
[26] Y.B. Shrinivasan and J.J. van Wijk, “Supporting the Analytical Reasoning Process in Information Visualization,” Proc. ACM SIGCHI, pp. 1237-1246, 2008.
[27] S.P. Callahan, J. Freire, E. Santos, C.E. Scheidegger, C.T. Silva, and H.T. Vo, “VisTrails: Visualization Meets Data Management,” Proc. 2006 ACM SIGMOD, pp. 745-747, 2006.
[28] C. Ahlberg, C. Williamson, and B. Shneiderman, “Dynamic Queries for Information Exploration: An Implementation and Evaluation,” Proc. SIGCHI, pp. 619-626, 1992.
[29] N. Wirth, Systematic Programming: An Introduction. Prentice Hall PTR, 1973.
[30] B. Shneiderman, “Dynamic Queries for Visual Information Seeking,” IEEE Software, vol. 11, no. 6, pp. 70-77, Nov. 1994.
[31] E. Gamma, R. Helm, R. Johnson, and J. Vlissides, Design patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley/Longman Publishing Co., Inc., 1995.
[32] B. Shneiderman and M. Wattenberg, “Ordered Treemap Layouts,” Proc. IEEE Symp. Information Visualization, pp. 73-78, 2001.
[33] M. Bruls, K. Huizing, and J. van Wijk, “Squarified Treemaps,” Proc. Joint Eurographics and IEEE VGTC Symp. Visualization (VisSym '00), pp. 33-42, 2000.
[34] M. Giereth and T. Ertl, “Visualization Enhanced Semantic Wikis for Patent Information,” Proc. 12th Int'l Conf. Information Visualisation (IV '08), pp. 185-190, 2008.
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