An intelligent personalized web blog searching technique using fuzzy-based feedback recurrent neural network
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METHODOLOGIES AND APPLICATION
An intelligent personalized web blog searching technique using fuzzybased feedback recurrent neural network Harsh Khatter1 • Anil Ahlawat2
Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract In web information retrieval, every single user has a unique contextual objective when searching for information on web blogs. Based on the given query, the task of the web search engine is to fetch the most related information from the collection of web blogs. In order to enhance the searching ability, efficient semantic matching models, richer training, and evaluation resources are required. The conventional keyword-based search algorithms have a minimum efficiency in knowing users’ intentions compared to machine learning algorithms. Recently, neural networks are well-recognized in information retrieval due to the ability of vector representation learning. This paper proposes an adaptive fuzzy feedback recurrent neural network-based web blog searching technique which follows inverse filtering (IF) algorithm using Word2Vec representation. Initially, the user query is pre-processed, and then given to the IF for accelerating the search process. Inside the IF, the web blog content is labelled according to their blog information and stored in the hash table, and then relevant contents are extracted by TF–IDF; this result is given to the similarity estimation to obtain the similarity score. Finally, the proposed technique considers the feedback got from users and performs re-ranking by fuzzy-based RNN to achieve rich user intention satisfaction. The implementation is performed in Python, and statistical measures such as accuracy, precision, and recall are utilized for performance evaluation. The results demonstrate that the proposed technique has enhanced accuracy (94%) compared to conventional techniques, namely deep auto-encoder, deep neural networks, and artificial neural networks. Keywords World Wide Web (WWW) CCSN Web personalized RNN
1 Introduction Many people in the world are influenced by an improvement and update of web technology, explicitly the students from the university. It also frequently disturbs the personal and social activity. The improvement of network technology is the main reason for improving the web (Hadley 2009; Englar et al. 2017). A progression of computer software and hardware is another motivation for developing web technology. From the primary browser ‘‘WWW’’
Communicated by V. Loia. & Harsh Khatter [email protected] 1
ABES Engineering College, Affiliated from Dr. APJ Abdul Kalam Technical University, Lucknow, Ghaziabad, India
2
KIET Group of Institutions, Affiliated from Dr. APJ Abdul Kalam Technical University, Lucknow, Ghaziabad, India
to the most recent ‘‘Google Chrome’’, the software is the main phase for browser side. The ‘‘Opera’’, ‘‘Firefox’’, ‘‘Safari’’, ‘‘Netscape’’, ‘‘Mosaic’’, ‘‘Mozilla’’, and ‘‘IE’’ are the commonly used browsers amid the process time (Mu¨ller and Rudova´ 2016).
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