Soft Computing Techniques for Duplicate Question Detection in Transliterated Bilingual Data

By way of the increased penetration of the Internet, social networking websites have become a

constitutive and indispensable concern of our lives. Social networks make sharing of

information, communication and collaboration straightforward and opportune. Social

media websites have grown significantly popular over the last decade as the key open

source platforms for general information and knowledge sharing. Social media news feeds

and question answering sites are increasingly becoming popular and valuable resources for

enriching and enhancing the knowledge base. Teaching-learning process is now immensely influenced

by the emerging role of social media and cannot be ignored. Increased accessibility of the

internet and the ubiquitous networks are major factors to change the pedagogical and

learning ecosystem's dynamics . Community question answering (CQA) as a crowd-

sourced service has emerged as a collective intelligence social system which

facilitates participation of volunteers to express their knowledge and clear their

uncertainties regarding some topics. The alternate perspectives promotes

receptiveness in sharing and learning, interactions and collaborations which describe the

advantages of intensive use of a typical Q&A website as open source of information. But

on the flip side, it is laborious and long-drawn-out task to segregate the semantically duplicate

information, best answers/semantically matched questions and experts for better user

experience . These Q&A forums however facilitate instant information, comprehend

issues related to higher response time and compromised quality of answers with

the influx of questions and answers.



Furthermore, semantically duplicate content falsify the mechanism employed for filtering.

Thus the present needs shifted the point of focus towards the hitches of 'filter

failure' from the issues of 'information overload'. To build an intelligent, proficient

and semantic filtering solutions that can adjust, realign the responses and

give options as per user's interest has become pivotal.