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The aim of this experiment is to present an easy way to compare fragments of texts in order to detect (supposed) results of copy and paste operations between articles in the domain of Natural Language Processing (NLP), including Speech Processing. The search space of the comparisons is a corpus labeled as NLP4NLP, which includes 34 different conferences and journals and gathers a large part of the NLP activity over the past 50 years. This study considers the similarity between the papers of each individual event and the complete set of papers in the whole corpus, according to four different types of relationship (self-reuse, self-plagiarism, reuse and plagiarism) and in both directions: a paper borrowing a fragment of text from another paper of the corpus (that we will call the source paper), or in the reverse direction, fragments of text from the source paper being borrowed and inserted in another paper of the corpus. The results show that self-reuse is rather a common practice, but that plagiarism seems to be very unusual, and that both stay within legal and ethical limits. [ABSTRACT FROM AUTHOR]

Optimizing the production, maintenance and extension of lexical resources is one the crucial aspects impacting natural language processing (NLP). A second aspect involves optimizing the process leading to their integration in applications. With this respect, we believe that a consensual specification on monolingual, bilingual and multilingual lexicons can be a useful aid for the various NLP actors. Within ISO, one purpose of Lexical Markup Framework (LMF, ISO-24613) is to define a standard for lexicons that covers multilingual lexical data. [ABSTRACT FROM AUTHOR]

This paper analyzes the content of the proceedings of the Language Resources and Evaluation Conference (LREC) over the past 17 years (1998-2014), with the goal of gaining a picture of the LREC community and the topics that are most relevant to the field. We follow the methodology used in similar studies, including the survey of the IEEE ICASSP conference proceedings from 1976 to 1990, the survey of the Association of Computational Linguistics conference proceedings over 50 years, and the survey of the proceedings of the conferences contained in the ISCA Archive over 25 years (1987-2012). We expand on results originally presented at LREC 2014, but include the proceedings of LREC 2014 itself in the study together with an analysis of various citation graphs. We show the evolution over time of the number of papers and authors, including their distribution by gender and affiliation, as well as collaborations and citation patterns among authors and papers, funding sources for reported research, and plagiarism and reuse in LREC papers; results for LREC are compared with similar results for major conferences in related fields. We also consider the evolution of research topics over time and identify the authors who introduced key terms. Finally, we propose and apply a measure of a researcher's notability and provide the results for LREC authors. The study uses NLP methods that have been published in the corpus considered in the study. In addition to providing a revealing characterization of the LRE community, the study also demonstrates the need for establishing a system for unique identification of authors, papers and other sources to facilitate this type of analysis. [ABSTRACT FROM AUTHOR]