Ad Text Optimization Using Interactive Evolutionary Computation Techniques

Madera, Quetzali; García-Valdéz, Mario; Mancilla, Alejandra

doi:10.1007/978-3-319-05170-3_47

Cited by 5 publications

(5 citation statements)

References 14 publications

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“…OPT typically employ artificial intelligence approaches to paraphrase a text, e.g., by replacing words with their synonyms [45]. The tools were initially designed for Search Engine Optimization [22] by inflating a website's PageRank. The idea is to re-use the content of the promoted website to create numerous bogus websites that link to the advertised website.…”

Section: Introductionmentioning

confidence: 99%

Detecting Machine-Obfuscated Plagiarism

Foltýnek

Ruas

Scharpf

et al. 2020

Sustainable Digital Communities

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Research on academic integrity has identified online paraphrasing tools as a severe threat to the effectiveness of plagiarism detection systems. To enable the automated identification of machineparaphrased text, we make three contributions. First, we evaluate the effectiveness of six prominent word embedding models in combination with five classifiers for distinguishing human-written from machine-paraphrased text. The best performing classification approach achieves an accuracy of 99.0% for documents and 83.4% for paragraphs. Second, we show that the best approach outperforms human experts and established plagiarism detection systems for these classification tasks. Third, we provide a Web application that uses the best performing classification approach to indicate whether a text underwent machine-paraphrasing. The data and code of our study are openly available.

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Section: Introductionmentioning

confidence: 99%

Detecting Machine-Obfuscated Plagiarism

Foltýnek

Ruas

Scharpf

et al. 2020

Sustainable Digital Communities

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“…To test the presented method, an experiment based on the work by Hsieh and Chen [11] was performed, and is explained in the Section 4, and is an extension to a previous work by the authors of this paper, and it can be found in [13]. In Section 2, an overview of related work is presented.…”

Section: Introductionmentioning

confidence: 97%

A Method Based on Interactive Evolutionary Computation for Increasing the Effectiveness of Advertisement Texts

Madera

García-Valdéz

Castillo

et al. 2015

Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

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Interactive Evolutionary Computation (IEC) is used in this work in order to perform the optimization of several advertisement blocks of text. The advertisement texts follow a format similar to the one used in a technique called Article Spinning. This format allows an IEC algorithm to evolve the text, using words and phrases as variable parts which change according to the subjective evaluation of people interacting with the algorithm. After several generations, the IEC algorithm provides a version of the advertisement text that, in theory, should exhibit an increased performance, according to the subjective evaluation function it was evolved with. In order to demonstrate the efficiency of the texts, these are compared against a version determined by an expert in a field related to marketing. For this comparison, three tests are performed: recall, recognition, and persuasion tests. The results obtained show that IEC could effectively be used to increase the impact of an advertisement text.

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“…Spinning techniques would allow, for example, the same text to be placed on ten different websites, all with slight variants, but not be detected as duplicated content through Google, something often referred to as a black hat approach. Madera et al (2014) have discussed this in more detail.…”

Section: Introductionmentioning

confidence: 99%

Automatic paraphrasing tools: an unexpected consequence of addressing student plagiarism and the impact of COVID in distance education settings

et al. 2023

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Text matching tools employed to detect plagiarism are widely used in universities, but their availability may have pushed students to find ways to evade detection. One such method is the use of automatic paraphrasing software, where assignments can be rewritten with little effort required by students. This paper uses the search engine analytics methodology with data from SEMrush and Google Trends to estimate the level of interest in online automatic paraphrasing tools, focusing on the period 2016 to 2020 and the four countries: the USA, UK, Canada and Australia. The results show a concerning trend, with the number of searches for such tools growing during the period, especially during COVID-19, and notable increases observed during the months where assessment periods take place in universities. The method employed in this study opens up a new avenue of analysis to enrich and supplement the existing knowledge in the field of academic integrity research. The data obtained demonstrates that faculty should be alert for student use of automatic paraphrasing tools and that academic integrity interventions need to be in place across the sector to address this problem.

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Ad Text Optimization Using Interactive Evolutionary Computation Techniques

Cited by 5 publications

References 14 publications

Detecting Machine-Obfuscated Plagiarism

Detecting Machine-Obfuscated Plagiarism

A Method Based on Interactive Evolutionary Computation for Increasing the Effectiveness of Advertisement Texts

Automatic paraphrasing tools: an unexpected consequence of addressing student plagiarism and the impact of COVID in distance education settings

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