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Hi,<br>
<br>
During the community bonding period of the GSoC program, the
participants are expected to interact with the community to
understand about the basic work flow of the community, make some
small small contributions to the projects that the community
maintain like bugfix patches and documentations, understand the
coding standards, deployment models, version control systems etc
that are being used by the community, familiarize with the
communication methods used by the community etc. <br>
<br>
<b>0. Blog</b><br>
I will be maintaining a blog for documenting and summarizing the
work I do for the GSoC Program, which may be found as a category in
my personal blog[0]<br>
<br>
<b>1. Community Contribution</b><br>
I have been contributing to the community before GSoC, in form of
localization and packaging etc. Still, as a contribution to the
community during the GSoC Community Bonding period, I have written a
small library in Python, that can be used to generate different
Vibhakthi forms of Malayalam words (like രാമൻ -> രാമന്റെ, രാമനെ,
രാമനോട്, രാമനാൽ etc). The project was inspired by Santhoshettan's
similar project[1] using jQuery.i18n library. The code is available
in my personal repo[2] now and I will be pushing it to the
organization's repo soon. <br>
<br>
The library now uses a rule based approach to generate the Vibhakthi
forms, which is not 100% efficient. It will fail in words ending
with those letters (usually Chillu characters) whose base forms are
still ambiguous. Example, the words ending with ർ whose base form
can be either ര or റ. Different words ending with ർ, that have
similar structure has different results when applying the same
vibhakthi.<br>
<br>
Example :<br>
അനിവർ + സംബന്ധിക = അനിവറിന്റെ<br>
മലർ + സംബന്ധിക = മലരിന്റെ<br>
കൗരവർ + സംബന്ധിക = കൗരവരുടെ<br>
<br>
(Thanks to Santhoshettan for the following info)This shows a
drawback of rule based method and we need to develop a method where
the word etymology is also considered . That can be expected to be
done when Machine Learning techniques become more clear and usable
for Malayalam. For now, since no such library exists, I follow the
concept of "99% is better than 0%" and guess the library is worth
using until we can find something better. I have a plan to use this
library during the development of the spell checker (I will post its
proposal in detail, soon), which I have to dig more on. For now, you
can try out the library at this online demo[3]. Happy if you people
can test and report issues/suggestions etc.<br>
<br>
[0] <a class="moz-txt-link-freetext" href="http://balasankarc.in/tech/category/gsoc/">http://balasankarc.in/tech/category/gsoc/</a><br>
[1] <a class="moz-txt-link-freetext" href="http://thottingal.in/projects/js/jquery.i18n/demo/mlgrammar.html">http://thottingal.in/projects/js/jquery.i18n/demo/mlgrammar.html</a><br>
[2] <a class="moz-txt-link-freetext" href="http://gitlab.com/balasankarc/vibhakthi-generator">http://gitlab.com/balasankarc/vibhakthi-generator</a><br>
[3] <a class="moz-txt-link-freetext" href="http://vibhakthi.balasankarc.in/">http://vibhakthi.balasankarc.in/</a><br>
<pre class="moz-signature" cols="72">--
Balasankar C
<a class="moz-txt-link-freetext" href="http://balasankarc.in">http://balasankarc.in</a></pre>
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