  Information and communication technology has the capability to improve the
process by which governments involve citizens in formulating public policy and
public projects. Even though much of government regulations may now be in
digital form (and often available online), due to their complexity and
diversity, identifying the ones relevant to a particular context is a
non-trivial task. Similarly, with the advent of a number of electronic online
forums, social networking sites and blogs, the opportunity of gathering
citizens' petitions and stakeholders' views on government policy and proposals
has increased greatly, but the volume and the complexity of analyzing
unstructured data makes this difficult. On the other hand, text mining has come
a long way from simple keyword search, and matured into a discipline capable of
dealing with much more complex tasks. In this paper we discuss how text-mining
techniques can help in retrieval of information and relationships from textual
data sources, thereby assisting policy makers in discovering associations
between policies and citizens' opinions expressed in electronic public forums
and blogs etc. We also present here, an integrated text mining based
architecture for e-governance decision support along with a discussion on the
Indian scenario.

Databases;Information Retrieval