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2015 | OriginalPaper | Buchkapitel

Automatic Estimation of Web Bloggers’ Age Using Regression Models

verfasst von : Vasiliki Simaki, Christina Aravantinou, Iosif Mporas, Vasileios Megalooikonomou

Erschienen in: Speech and Computer

Verlag: Springer International Publishing

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Abstract

In this article, we address the problem of automatic age estimation of web users based on their posts. Most studies on age identification treat the issue as a classification problem. Instead of following an age category classification approach, we investigate the appropriateness of several regression algorithms on the task of age estimation. We evaluate a number of well-known and widely used machine learning algorithms for numerical estimation, in order to examine their appropriateness on this task. We used a set of 42 text features. The experimental results showed that the Bagging algorithm with RepTree base learner offered the best performance, achieving estimation of web users’ age with mean absolute error equal to 5.44, while the root mean squared error is approximately 7.14.

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Vorheriges Kapitel Automatic Close Captioning for Live Hungarian Television Broadcast Speech: A Fast and Resource-Efficient Approach

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Titel: Automatic Estimation of Web Bloggers’ Age Using Regression Models
verfasst von: Vasiliki Simaki
Christina Aravantinou
Iosif Mporas
Vasileios Megalooikonomou
Verlag: Springer International Publishing
Buch: Speech and Computer
Print ISBN: 978-3-319-23131-0

Electronic ISBN: 978-3-319-23132-7

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-23132-7_14

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