Abstract
The quality of the web page classification process has a huge impact on information retrieval systems. In this paper, we proposed to combine the results of text and image data classifiers to get an accurate representation of the web pages. To get and analyse the data we created the complicated classifier system with data miner, text classifier, and aggregator. The process of image and text data classification has been achieved by the deep learning models. In order to represent the common view onto the web pages, we proposed three aggregation techniques that combine the data from the classifiers.
Highlights
Information retrieval (IR) systems play an important role in modern-day society [1]
Information retrieval systems have come a long way from the Boolean model [2] systems for Artificial Intelligence (AI) based [3] complicated models
The article organized as follows: The problem definition in Section 2 where we explain the reason why do we need to use different web page classification algorithms and combine them to get the consistent representation of the target classes, we discuss some related works in Section 3, The classifiers system discussed in Section 4 where we cover the work principles of text classifier and image caption generator
Summary
Information retrieval (IR) systems play an important role in modern-day society [1]. The goal of an information retrieval system is to collect, store, and provide an efficient search mechanism for the client. The most common web page classification methods are based on text [4][5] and graph data [6] analysing. The article organized as follows: The problem definition in Section 2 where we explain the reason why do we need to use different web page classification algorithms and combine them to get the consistent representation of the target classes, we discuss some related works, The classifiers system discussed in Section 4 where we cover the work principles of text classifier and image caption generator.
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