Mapping User Information with Cognitive Skills by Hybrid IR Models with Inference Engine

doi:10.23940/ijpe.20.09.p3.13411350

Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (9): 1341-1350.doi: 10.23940/ijpe.20.09.p3.13411350

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Mapping User Information with Cognitive Skills by Hybrid IR Models with Inference Engine

Parul Kalra^a,*, Deepti Mehtrotra^a, and Abdul Wahid^b

^aAmity University Uttar Pradesh, Noida, 201313, India;
^bMaulana Azad National Urdu University, Gachibowli, Hyderabad, 500032, India

Submitted on ; Revised on ; Accepted on
Contact: * E-mail address: parulkalra18@gmail.com
About author:Parul Kalra is an assistant professor at Amity University and currently pursuing her Ph.D. in the Department of Computer Science at Amity School of Engineering and Technology, Noida, UP. She received her BCA, M.Sc. CSE, and M.Tech. CSE from Banasthali Vidyapeeth, Rajasthan. She has more than 15 years of teaching and research experience. Her research interests include information retrieval, cognitive science, and data mining.
Dr. Deepti Mehrotra received her Ph.D. from Lucknow University and is currently working as a professor in the Amity School of Engineering and Technology at Amity University, Noida. Earlier, she worked as a director of the Amity School of Computer Science. She has more than 20 year of experience in research, teaching, and content writing. She is an editor and reviewer for many books, referred journals, and conferences. She also enjoys guiding research scholars and advises many Ph.D. and M.Tech students.
Dr. Abdul Wahid received his Ph.D. in computer science from Jamia Millia Islamia (A Central University), New Delhi, India. He is currently a professor at the Maulana Azad National Urdu University (A Central University), where he is also the dean of the School of Computer Science and Information. He is an expert member in several academic and administrative committees. His research areas are software and web engineering, e-learning, and machine translation. He is a professional member of IEEE. He is also a lifetime member of the Institution of Electronics and Telecommunication Engineers (IETE) and India Society for Technical Education (ISTE). Finally, he is a member of the Scientific and Technical Committee & Editorial Review Board, World Academy of Science, Engineering and Technology.

Abstract

Abstract: Retrieval of information is the presumption of a real-world user declaration based on the concept of storing, representing, and searching information. It also uses the database to easily access the repository of information. Developing a system that can come up with the ambiguous user needs is a complex task, as each of the incoming queries from the user to the system is unique. The expectations from the system are high in order to fulfill the information needs of the user. The fluidity of the human brain is extremely high, because each person has different cognitive abilities, values, thinking, interpretations, situations, intent, instincts, and domains. Such various characteristics lead to a user's query about or need for data; hence, it could be said that individual users have different apprehensions of query. The key requirement is to consider the users' query to provide the individual with effective and appropriate results according to the knowledge required. This paper implemented BB2 hybrid with a fuzzy logic inference. The purpose of the system is to map the IR model using the fuzzy approach with the cognitive abilities of the user. The similarity between the file, depending on the graininess of the user, was calculated using fuzzy logic to evaluate the query results.

Key words: information retrieval, models, fuzzy logic, Terrier, TREC, hybrid IR

Parul Kalra,Deepti Mehtrotra,and Abdul Wahid. Mapping User Information with Cognitive Skills by Hybrid IR Models with Inference Engine [J]. Int J Performability Eng, 2020, 16(9): 1341-1350.

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Mapping User Information with Cognitive Skills by Hybrid IR Models with Inference Engine

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