This is the vignette of the Bioconductor compliant packege adSplit . We describe our implementation of annotationdriven clustering for microarray gene expression profiling studies. Corresponding author: [email protected]

Author Profiling (AP) is a method of identifying the demographic profiles such as age, gender, location, native language and personality traits an author by processing their written texts. The AP techniques are used in multiple applications literary research, marketing, forensics security. researchers identified various differences authors writing styles analysing datasets. represented stylisti...

This paper describes the participation of INSA Lyon and UNI Passau at the PAN 2017 Author Profiling task. Given the language and tweets from an author, the goal is to predict his/her gender and language variety. We consider two strategies : a "loose" classification that learns one predictive model for the gender and another one for the variety, and a "successive" classification that first predi...

Author profiling can be considered a form of text analysis of which the objective is to ascertain characteristics of the author behind a text sample. This paper describe the design and implementation of an approach for determining the age group (10s, 20s, or 30s) and gender (male/female) of text samples for the author profiling task in PAN 2013. Evaluation is then based on the compounded accura...

In recent years, author profiling (AP) has become a very relevant task for natural language processing (NLP). The main goal of 43 Research in Computing Science 115 (2016) pp. 43–56; rec. 2016-04-22; acc. 2016-05-15 AP is automatically determine demographic aspects from an author, for example, genre and age. In this paper we present a method for author profiling; particularly, we are interested ...

The paper gives a brief overview of the three shared tasks organized at PAN 2021 lab on digital text forensics and stylometry hosted CLEF conference. include authorship verification across domains, author profiling for hate speech spreaders, style change detection multi-author documents. In part are new in they continue advance past tasks, with overall goal advancing state art, providing an obj...

This paper describes the methods we have employed to solve the author profiling task at PAN-2013. Our goal was to use simple features to identify the age group and the gender of the author of a given text. We introduce the features, detail how the classifiers were trained, and how the experiments were run.

In this paper we present the approach we took in our participation to the PAN 2013 Author Profiling task. It is an adaptation of our system submitted for author identification, assuming that a profile category (authors belonging to the same gender and age group categories) can be analyzed in the same way as an author’s style.