Volume – I, Issue – I, International Journal of Mathematical Sciences and Engineering (IJMSE), March 2012
Improving the Tamil E-Learning Using Tamil
Semantic Web
Kanimozhi.E1#, Anandkumar.M2#, Dr.Gunasekaran.S3#
1
2
PG scholar, Department of Computer Science and Engineering, e-mail: [email protected]
Assistant professor, Department of Computer Science and Engineering, e-mail: [email protected]
3
Assistant professor, Department of Computer Science and Engineering, e-mail: [email protected]
#
Coimbatore Institute of Engineering and Technology, Coimbatore - 641 109.
Abstract – E-learning is the most predominated approach in
Learning or studying a scientific concept using mother
modern education. E-learning becomes more popular because it
language can be easily grasped when compare to the foreign
uses the matters and materials available in the internet world.
languages or secondary languages. Japanese are best example
Identifying these resources in the internet uses Semantic Web
technology which is one of the pioneer technologies to search a
required resource by using English as a common language. This
paper explains the language specific semantic web to gain the
for this. Mother language provides direct understanding of the
content and avoids the rote knowledge acquisition. Other
significant advantages of learning via mother language are
language specific knowledge acquisition in E-learning. In this
improving the creativity and bringing more innovative ideas.
paper the concept is explained by using Tamil language which is
In early days most of the e-resources and contents in the
one of ancient language of India equal to Greek and Old Persian.
internet world are in English. After inventing regional
This paper also portrays the empirical study of searching Tamil
language Unicode fonts so many regional specific websites
language content by using Semantic Web 3.0.
and web resource materials are available in the internet using
Keywords – E-learning, Natural Language processing, Tamil
regional language Unicode fonts. Conversions between these
Semantic Web, Ontology.
fonts are also under research.
I. INTRODUCTION
A recent development in education pedagogy brings the E-
In this paper we are concentrating on our mother language
learning concepts as an essential learning practice, especially
Tamil and Tamil oriented E-learning concepts. Madurai
for science and engineering graduate students. Using internet
Project [15] and Tamil Virtual University [16] offer so many
as a master, student community can clench any type
Tamil literature works and books in Unicode Tamil format.
knowledge. Main disadvantages in internet based E-learning
Incredible development of Tamil blogs provides various kinds
process are lack of resources and searching of the correct
of knowledge and information in numerous fields. All the
resources. Appropriate searching result can be accomplished
Tamil newspapers and most of the Tamil magazine are freely
only if the exact phrase was given for that search using search
available in the internet using Unicode fonts. Identifying and
engines.
learning from these contents require Tamil semantic web
To improve the searching results and identifying the
technology using web3.0. We are portraying the development
resource in the internet, recent web technology web3.0 uses
of Tamil semantic web and we empirically prove that Tamil
the semantic web technology which represents any object or
content based searching improves the search efficiency and
resources in the web by both syntactically and semantically.
helps to improve the Tamil E-learning concepts.
This type of representation is very much useful for the
computer machines to search any content in the internet as like
human behaviour search and improve the internet based Elearning concept more effective and efficient.
II. E-LEARNING USING SEMANTIC WEB
A semantic web is a large collection of information that
describes the language and make machine to understand easily
Volume – I, Issue – I, International Journal of Mathematical Sciences and Engineering (IJMSE), March 2012
on a global scale. All statements in semantic web are about
how the syntax becomes semantic i.e., the way how computer
understand language. These web does not deal with links
about web page but explains the relationship between words
and its properties using RDF (Resource Description
Framework), OWL (Ontology Web Language) so that web
spider can easily search, pickup, collect, analyse and process
the information. Semantic web has influence in several
domains; E-learning is the significant domain which uses this
new web technology.
Fig. 2.1. Pyramid of semantic web language.
All the E-learning process are having fast, just in time,
Interactive: Software agents on the Semantic Web,
relevant nature along with subject oriented, dynamic and
enables
personalized. The significant characteristics of E-learning are
proactive delivery of learning materials in the
co-ordination
between
learners
and
Branded educational content.
context of actual problems.
Centralized tracking and administration.
Non-linear: User can describe the goal of learning,
Broad and easy access to information.
previous knowledge and perform semantic querying
Engaging user experience.
for the suitable learning material.
Collaborative and online communities.
Continuous: Active delivery of information creates a
Regular reinforcement.
dynamic learning environment.
Organizational
consulting,
implementation
and
Distributed: The Semantic Web will be as
decentralised as possible and helps for an effective
Integration.
Building upon RDF and RDFS (Resource Description
co-operative
content
management.
Distributed
Framework Schema), OWL defines the types of relationship
nature of the Semantic Web enables continuous
that can be expressed in RDF to indicate the hierarchies and
improvement of learning materials
relationships between different resources in other words it can
Personalized: A user (using personalised agent)
be referred as ontology. When RDF resource descriptions are
searches learning material customised for her/his
associated with an ontology defined somewhere on the Web,
needs. The ontology is the link between user needs
intranet, or extranet, it‟s possible for machines to retrieve the
and characteristics of the learning material.
semantic information associated with each resource.
This effective semantic web technology is used as follows
for effective E-learning
III. TAMIL SEMANTIC WEB
Tamil is one of the ancient and longest surviving classical
languages in the world. Tamil is inherited from Brahmi script
Pull: Learning materials are distributed on the
which has 12 vowels and 18 consonants combined together to
Web, but they are linked to commonly agreed
derive 216 character and one special character counting
ontology.
This enables construction of a user-
together to total 217 characters. Tamil is morphologically rich
specific course, by semantic querying for topics of
language. Tamil word consists of lexical root to which one or
interest.
more affixes are attached. Most Tamil affixes are suffixes
which can be derivational or inflectional .The derivational can
change the part of speech of word or its meaning and
inflectional suffixes mark categories as person, number, mood,
tense, etc. Also there is no limit on the length and extent of
Volume – I, Issue – I, International Journal of Mathematical Sciences and Engineering (IJMSE), March 2012
agglutination which can lead to long words with a large
number of suffixes.
All Tamil words are morphologically analysed and
sentences are pre-processed by POS Tagging, Chunking,
semantic role labelling .Each Tamil word in the query should
be pre-processed and query should be given weightage based
on context and concept level before the retrieval process. In
Tamil semantic web words are morphologically analysed by
following pre-processing steps.
A. Romanization
Data are converted to Romanized forms using the Unicode
Fig.3.1 Pre-processing steps.
to Roman mapping file. In Tamil, syllable exists as a single
character, where we cannot separate vowel and Consonants.
B. Segmentation
IV. PROCESS FLOW
In fig. 4.1 overall process flow for Tamil semantic web
used for E-learning is shown. When the user enters the query,
After Romanization each and every word is segmented
it is morphologically analysed and pre- processed to retrieve
based on the Tamil grapheme and additionally each syllable in
keywords. These keywords are the sources which are used to
the corresponding word is further segmented into consonants
match with knowledge base database for the retrieval of
and vowels. To the segmented syllable postfix “–C” and “–V”
required
are used to the consonant and vowel respectively. It is named
ontologically related then it retrieves all related E-resources.
E-resources.
If
the
matched
resources
are
as C-V representation i.e. Consonant – Vowel representation.
C. Alignment and mapping
The segmented words are aligned vertically as segments
using the gap between them. And the input segments are
consequently mapped with output segments.
D. Mapping mismatch segment
Input is mapped with output character but mismatch occur
in two cases either the input units are larger or smaller than
that of the output units.
The processed query is executed against the knowledge
base, which returns a list of instance tuples that satisfy the
query. This step of the process is purely Boolean (i.e., based
on an exact match), so that the returned instances must strictly
hold all the conditions in the formal query. Rather than
proposing a new approach for this operation, we reuse
techniques for the execution of the formal query by a standard
ontology-based query engine, such as the ones packaged with
popular ontology processing.
Fig. 4.1 Identifying E-resources using semantic ontology.
V. E-LEARNING IN TAMIL
In India the three language formula was implemented for
decades ago in order to bring the national integration, intra
state, interstate and international communication effectively.
According to three-language formula the language has
categories as follows
Volume – I, Issue – I, International Journal of Mathematical Sciences and Engineering (IJMSE), March 2012
The first language to be studied must be the mother
tongue or the regional language.
The second language will be some other modern
Indian language or English for Hindi speaking states
and Hindi or English for non-Hindi speaking states.
The third language will be English or a modern Indian
language which is not studied as the second language
for both Hindi speaking and Non Hindi speaking.
Fig.6.1 Web searching the Tamil pages using English language
When searching a Tamil content using secondary language
(i.e., English), the results are retrieved based on meta-tags
which displays the irrelevant result along with relevant result.
When Unicode Tamil language is used for searching expected
and relevant results are displayed as shown in Fig.6.2 Also
complexity occurs when certain letters like
Fig. 5.1 Components of E-learning
E-learning is one of the recent teaching learning
environments with the integration of computer technology and
in Tamil has
different way of writing in English language as „la‟ and „zh‟
etc.
Internet has created new dimensions to education. It plays
important role in filling the gap in education where teachers
are also considered as co-learners and guide to help the
students to learn lessons through different channels. With
introduction of Tamil digital classrooms through Internet
encourage
interaction
among
learners,
exchange
of
information, idea, materials, feedback with involvement which
makes the speed and efficiency of Tamil Language teaching
and learning process has reached greater extent irrespective of
geographical location.
VI. EMPRICAL STUDY
In this paper we have conducted a semantic based search
using Google search engine. In our first setup we have
searched the kadavul vazhthu part of Thirukkural using the
search engine. Fig.6.1 shows the search result achieved by the
Google.
Fig.6.2 Web searching the Tamil pages using Unicode Tamil language
Fig.6.3 shows the relevant result of web page when
searched in Tamil regional language. Thus retrieval of
information when performed in regional language will end up
in exact and good number of results.
Volume – I, Issue – I, International Journal of Mathematical Sciences and Engineering (IJMSE), March 2012
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