Adaptive and Personalized Web Blog Searching Technique Using S-ANFIS

Abstract

Day by day, the number of blog users and microblog users is increasing worldwide. It is easy to say that blogs have captured a significant portion of other web services. In the past few years, the number of users has exponentially increased. User count of Facebook, Twitter, and Instagram applications is not hidden from anyone. Users on such platforms share ideas, experiences, stories, opinions, and views and want to interact with people with the same set of interests. As per the user’s expectation, there is a requirement of two things: content curation and recommendations. The content curation algorithm will find the people and their posts on personalized search results. In addition, the recommendation system will help to find the most appropriate match to interact with. In this paper, both approaches are combined to show the user’s curated and recommended results. The article focuses on the hybrid model named S-ANFIS, and the results are compared with the well-known approaches like ANN, Deep Neural Network (DNN), and Recurrent Neural Network (RNN).

A Hybrid Convolutional Network and Long Short-Term Memory (HBCNLS) model for Sentiment Analysis on Movie Reviews

“…The output of the LSTM is then be concatenated with the output of the CNN and passed through a fully-connected layer to make a prediction. This hybrid model combines the strengths of CNNs and LSTMs by using the CNN [25] to capture local patterns in the data and the LSTM to capture long-term dependencies. Figure 3 displays detailed methodology of our proposed hybrid model.…”

Retracted: Adaptive and Personalized Web Blog Searching Technique Using S‐ANFIS

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”