In this digital age most of the government regulations are often available online, similarly with the advent of a number of electronic online forums the opportunity of gathering citizens' petitions and stakeholders' views on government policy has increased greatly, but the volume and the complexity of analyzing unstructured data makes difficult to extract useful information from this data. On the other hand, text mining(TM) has the capability to deal with this type of data. TM techniques can help policy makers by identifying the relatedness between existing regulations and proposed policy drafts. In this article we discuss how text-mining techniques can help in retrieval of information and relationships from unstructured data sources, thereby assisting policy makers in discovering associations between existing policies, proposed policies and citizens' opinions expressed in electronic public forums. In this article, an integrated text mining based architecture for e-governance decision support is presented along with a discussion on the Indian scenario. © 2011 Springer-Verlag.
CITATION STYLE
Rao, G. K., & Dey, S. (2011). Text mining based decision support system (TMbDSS) for E-governance: A roadmap for India. In Communications in Computer and Information Science (Vol. 198 CCIS, pp. 270–281). https://doi.org/10.1007/978-3-642-22555-0_29
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