Paper Info
Title
Prediction of Domain Values: High throughput screening of domain names using Support Vector Machines.
Abstract
As connected devices multiply and the internet matures into a ubiquitous platform for exchange and communication, the question of what makes a domain name valuable is ever more significant. Due to the scarcity of meaningful vocabulary and the persistence of domain-related data, the buying and selling of previously owned domain names, also known as the domain aftermarket, has evolved into a billion dollar industry. Each day over a 100,000 domain names expire and become available for re-registration. Manual appraisal is impossible at such a volume; thus a method for the automated identification of valuable domain names is called for. The aim of our study was to develop a method for high throughput screening of domain names for rapid identification of the valuable ones. Five different aspects that make a domain name valuable were identified: name quality, domain authority, domain traffic, active domain age and domain health. An SVM method was developed for high throughput screening of domain names. Our method was able to identify valuable domain names with 97% accuracy for the test set and 93% for the external set and can be used for routinely screening the domain aftermarket.
Year
Venue
Field
2017
arXiv: Computers and Society
Data mining,Domain name,Computer science,Support vector machine,Vocabulary,Domain Authority,The Internet,Test set
DocType
Volume
Citations 
Journal
abs/1707.00906
0
PageRank 
References 
Authors
0.34
9
3
Name
Order
Citations
PageRank
Zsolt Bikádi181.44
Sapumal Ahangama202.70
Eszter Hazai3222.80