International Journal of Scientific and Research Publications

IJSRP, Volume 4, Issue 8, August 2014 Edition [ISSN 2250-3153]


Optimizing the relevancy of Predictions using Machine Learning and NLP of Search Query
      Kilari Murali krishna Teja
Abstract: One of the most important and promising branches of Artificial Intelligence (AI) is Machine Learning (ML),which strive to make a machine intelligent by “learning” from the data. Information Retrieval is also a popular and predominant technique having as one of its application, the ubiquitous Search Engine. Search Engine optimization (SEO) has seen remarkable advancements during the recent years. The objective of this paper is to optimize the existing predictive search mechanism by incorporating pattern based Machine Learning techniques, the association with a Semantic Database, Natural Language Processing of search query to produce more relevant predictions to the user. The main intention is to provide diversified but apt, intelligent predictions for both the diversified set of users whose domain of search queries is not constrained, as well as for the dedicated researchers whose domain will be confined, coupled with an optimal balance between the Response times, Relevancy of predictions.

Reference this Research Paper (copy & paste below code):

Kilari Murali krishna Teja (2018); Optimizing the relevancy of Predictions using Machine Learning and NLP of Search Query; Int J Sci Res Publ 4(8) (ISSN: 2250-3153). http://www.ijsrp.org/research-paper-0814.php?rp=P323049
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