Soft Computing Techniques for Duplicate Question Detection in Transliterated Bilingual Data
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- Udgivet:
- 21. August 2023
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- 216x7x280 mm.
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- 319 g.
- 2-4 uger.
- 15. Oktober 2024
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Beskrivelse af 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.
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.
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