An Efficient Minimal Text Segmentation Method for URL Domain Names

Yiqian Li,Lianjiang Zhu,Shouning Qu,Tao Du,Antonio J Peña

doi:10.1155/2021/9946729

Abstract

Text segmentation of the URL domain name is a straightforward and convenient method to analyze users’ online behaviors and is crucial to determine their areas of interest. However, the performance of popular word segmentation tools is relatively low due to the unique structure of the website domain name (such as extremely short lengths, irregular names, and no contextual relationship). To address this issue, this paper proposes an efficient minimal text segmentation (EMTS) method for URL domain names to achieve efficient adaptive text mining. We first designed a targeted hierarchical task model to reduce noise interference in minimal texts. We then presented a novel method of integrating conflict game into the two-directional maximum matching algorithm, which can make the words with higher weight and greater probability to be selected, thereby enhancing the accuracy of recognition. Next, Chinese Pinyin and English mapping were embedded in the word segmentation rules. Besides, we incorporated a correction factor that considers the text length into the F1-score to optimize the performance evaluation of text segmentation. The experimental results show that the EMTS yielded around 20 percentage points improvement with other word segmentation tools in terms of accuracy and topic extraction, providing high-quality data for the subsequent text analysis.

Highlights

In recent years, the internet has become one of the most important infrastructures in human society, having an increasingly broad and deep impact on people’s economic and social activities [1]
Since the URL domain name text has no context semantic relationship, word segmentation is the first step in the rapid extraction of web page attribute information and provides fast and accurate data support for analyzing the users network behaviors [4, 5]
In order to cope with the above challenge and promote the research on the behavioral emotion contained in URL, this paper proposes an efficient minimal text segmentation (EMTS) method for URL domain names

Summary

Introduction

The internet has become one of the most important infrastructures in human society, having an increasingly broad and deep impact on people’s economic and social activities [1]. Since the URL domain name text has no context semantic relationship, word segmentation is the first step in the rapid extraction of web page attribute information and provides fast and accurate data support for analyzing the users network behaviors [4, 5]. In order to cope with the above challenge and promote the research on the behavioral emotion contained in URL, this paper proposes an efficient minimal text segmentation (EMTS) method for URL domain names. Its primary goal is to perform text parsing on random website domain names and extract keywords with high accuracy because the prerequisite for quickly and accurately analyzing users’ online behavior preferences is to extract the emotional effects contained between samples [10].

Related Work

Experiments

Findings

Result