Heterogeneous Queries for Synoptic and Phrasal Search

This paper describes our approaches for the Plagiarism Detection – Source Retrieval task of PAN 2014. We combined and improved methodology used at PAN 2012 and PAN 2013. Our system combines three types of queries: The keywords-based queries; the paragraph-based queries; and the headers-based queries. The queries are distinguished also by other properties such as the phrase query or the positional query. The queries are submitted to two search engines – Chatnoir and Indri – according to their properties. The query’s position serves for the search control, minimization of the total number of executed queries is the system’s priority. Downloaded documents are textually compared with the suspicious document and if a similarity is found, the downloaded document is reported

Improving Synoptic Querying for Source Retrieval

Source retrieval is a part of plagiarism discovery process, where only a selected set of candidate documents are retrieved from a large corpus of potential source documents and passed for detailed document comparison in order to highlight potential plagiarism. This paper describes used methodology and the architecture of source retrieval system developed for PAN 2015 lab on uncovering plagiarism, authorship, and social software misuse. The system is based on our previous systems used at PAN since 2012. The majority of features were adopted with some improvements described in this paper. The paper analyzes used methodology and discuss the queries performance. The paper provides explanation for many implementation settings in the source retrieval process. The source retrieval subsystem forms an integral part of a modern system for plagiarism discovery.Source retrieval is a part of plagiarism discovery process, where only a selected set of candidate documents are retrieved from a large corpus of potential source documents and passed for detailed document comparison in order to highlight potential plagiarism. This paper describes used methodology and the architecture of source retrieval system developed for PAN 2015 lab on uncovering plagiarism, authorship, and social software misuse. The system is based on our previous systems used at PAN since 2012. The majority of features were adopted with some improvements described in this paper. The paper analyzes used methodology and discuss the queries performance. The paper provides explanation for many implementation settings in the source retrieval process. The source retrieval subsystem forms an integral part of a modern system for plagiarism discovery

Source Retrieval for Plagiarism Detection

Plagiarism has become a serious problem mainly because of the electronically available documents. An online document retrieval is a weighty part of a modern anti-plagiarism tool. This paper describes an architecture and concepts of a real-world document retrieval system, which is a part of a general anti-plagiarism software. Up to date systems for plagiarism detection are discussed from the source retrieval perspective. The key approaches of source retrieval are compared. The system recommendations stem from design, implementation, and several years of operation experience of a nationwide plagiarism solution at Masaryk University in the Czech Republic. The design can be adapted to many situations. Proper usage of such systems contributes to the gradual improvement of the quality of student theses.Plagiarism has become a serious problem mainly because of the electronically available documents. An online document retrieval is a weighty part of a modern anti-plagiarism tool. This paper describes an architecture and concepts of a real-world document retrieval system, which is a part of a general anti-plagiarism software. Up to date systems for plagiarism detection are discussed from the source retrieval perspective. The key approaches of source retrieval are compared. The system recommendations stem from design, implementation, and several years of operation experience of a nationwide plagiarism solution at Masaryk University in the Czech Republic. The design can be adapted to many situations. Proper usage of such systems contributes to the gradual improvement of the quality of student theses

Author Profiling and Plagiarism Detection

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-25485-2_6In this chapter we introduce the topics that we will cover in the RuSSIR 2014 course on Author Profiling and Plagiarism Detection (APPD). Author profiling distinguishes between classes of authors studying how language is shared by classes of people. This task helps in identifying profiling aspects such as gender, age, native language, or even personality type. In case of the plagiarism detection task we are not interested in studying how language is shared. On the contrary, given a document we are interested in investigating if the writing style changes in order to unveil text inconsistencies, i.e., unexpected irregularities through the document such as changes in vocabulary, style and text complexity. In fact, when it is not possible to retrieve the source document(s) where plagiarism has been committed from, the intrinsic analysis of the suspicious document is the only way to find evidence of plagiarism. The difficulty in retrieving the source of plagiarism could be due to the fact that the documents are not available on the web or the plagiarised text fragments were obfuscated via paraphrasing or translation (in case the source document was in another language). In this overview, we also discuss the results of the shared tasks on author profiling (gender and age identification) and plagiarism detection that we help to organise at the PAN Lab on Uncovering Plagiarism, Authorship, and Social Software Misuse.The PAN shared tasks on author profil-ing and on plagiarism detection have been organised in the framework of the WIQ-EIIRSES project (Grant No. 269180) within the EC FP 7 Marie Curie People. 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