Application of the KDD Process for the Visualization of Integrated Geo-Referenced Textual Data from the Pre-processing Phase
Pages 41 - 50
Abstract
Geo-referenced textual data has been the subject of multiple investigations, by providing opportunities to better understand certain phenomena according to the content that is shared, either on-line such as social networks, blogs, and news; or through repositories such as scientific research articles, geo-referenced virtual books, among others. However, the characteristics of this information are studied, analyzed and processed separately, either through its textual components or its geo-spatial components, which offers a separate understanding of the results.
In this paper, we propose an integration of textual and geo-spatial components from the pre-processing phase to the visualization stage, As a part of the Document Mapping process based on the phases of the Knowledge Discovery in Databases (KDD). Achieving two main results (1) minimize the problems that arise in the visual phase, such as data occlusion and (2) provide a more detailed understanding between the textual relationships of the data when plotted in a geo-spatial map.
References
[1]
Aggarwal CC and Zhai C Aggarwal C and Zhai C A survey of text clustering algorithms Mining Text Data 2012 Boston Springer 77-128
[2]
Bao, J., Zheng, Y., Mokbel, M.F.: Location-based and preference-aware recommendation using sparse geo-social networking data. In: Proceedings of the 20th International Conference on Advances in Geographic Information Systems, pp. 199–208. ACM (2012)
[3]
Cong, G., Feng, K., Zhao, K.: Querying and mining geo-textual data for exploration: challenges and opportunities. In: IEEE 32nd International Conference on Data Engineering Workshops (ICDEW), 2016, pp. 165–168. IEEE (2016)
[4]
De Oliveira MCF and Levkowitz H From visual data exploration to visual data mining: a survey IEEE Trans. Vis. Comput. Graph. 2003 9 3 378-394
[5]
Doytsher, Y., Galon, B., Kanza, Y.: Querying geo-social data by bridging spatial networks and social networks. In: Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks, pp. 39–46. ACM (2010)
[6]
Dykes, J., MacEachren, A.M., Kraak, M.J.: Moving geovisualization toward support for group work. In: Exploring Geovisualization, p. 445 (2005)
[7]
Jain, S.: Real-Time Social Network Data Mining for Predicting the Path for a Disaster (2015)
[8]
Lee, C.-H., Yang, H.-C., Wang, S.-H.: A location based text mining approach for geospatial data mining. In: Fourth International Conference on Innovative Computing, Information and Control (ICICIC), 2009, pp. 1172–1175. IEEE (2009)
[9]
Liu S, Cui W, Yingcai W, and Liu M A survey on information visualization: recent advances and challenges Vis. Comput. 2014 30 12 1373-1393
[10]
Ltifi, H., Ayed, M.B., Alimi, A.M., Lepreux, S.: Survey of information visualization techniques for exploitation in KDD. In: IEEE/ACS International Conference on Computer Systems and Applications, 2009, AICCSA 2009, pp. 218–225. IEEE (2009)
[11]
Lwin, K.K., Zettsu, K., Sugiura, K.: Geovisualization and correlation analysis between geotagged Twitter and JMA rainfall data: case of heavy rain disaster in Hiroshima. In: 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM), pp. 71–76. IEEE (2015)
[12]
Mislove, A., Lehmann, S., Ahn, Y.-Y., Onnela, J.-P., Rosenquist, J.N.: Understanding the demographics of twitter users. In: ICWSM, 11:5th (2011)
[13]
Mohamed EB, Ltifi H, and Ayed MB Integration of temporal data visualization techniques in a KDD-based DSS application in the medical field J. Netw. Innovative Comput. 2014 2 061-070
[14]
Paulovich, F.V., Oliveira, M.C.F., Minghim, R.: The projection explorer: a flexible tool for projection-based multidimensional visualization. In: XX Brazilian Symposium on Computer Graphics and Image Processing, 2007, SIBGRAPI 2007, pp. 27–36. IEEE (2007)
[15]
Paulovich, F.V., Minghim, R.: Text map explorer: a tool to create and explore document maps. In: Tenth International Conference on Information Visualisation (IV 2006), pp. 245–251. IEEE (2006)
[16]
Sakaki, T., Okazaki, M., Matsuo, Y.: Earthquake shakes Twitter users: real-time event detection by social sensors. In: Proceedings of the 19th International Conference on World Wide Web, pp. 851–860. ACM (2010)
[17]
Tsou M-H, Yang J-A, Lusher D, Han S, Spitzberg B, Gawron JM, Gupta D, and An L Mapping social activities and concepts with social media (Twitter) and web search engines (Yahoo and Bing): a case study in 2012 US presidential election Cartography Geogr. Inf. Sci. 2013 40 4 337-348
[18]
Wüthrich, B.: Knowledge Discovery in Databases (1995)
[19]
Zhao K, Liu Y, Yuan Q, Chen L, Chen Z, and Cong G Towards personalized maps: mining user preferences from geo-textual data Proc. VLDB Endow. 2016 9 13 1545-1548
Recommendations
TimeLine and visualization of multiple-data sets and the visualization querying challenge
Data in its raw form can potentially contain valuable information, but much of that value is lost if it cannot be presented to a user in a way that is useful and meaningful. Data visualization techniques offer a solution to this issue. Such methods are ...
Effective Big Data Visualization
IDEAS '17: Proceedings of the 21st International Database Engineering & Applications SymposiumIn the last several years, big data analytics has found an increasing role in our everyday lives. Data visualization has long been accepted as an integral part of data analytics. However, data visualization systems are not equipped to handle the ...
Real-time Data Visualization of Intelligent Networked Vehicles
CNIOT '20: Proceedings of the 2020 International Conference on Computing, Networks and Internet of ThingsIn recent years, with the advent of the Internet of Things era of "Internet of Everything", the amount of data generated by human society has exploded. Visualization provides an intuitive, vivid, and effective way to visualize complex data in a visual ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
May 2018
181 pages
© Springer International Publishing AG, part of Springer Nature 2018.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 21 May 2018
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 12 Dec 2024