15,094 research outputs found
Overview of the Author Profiling Task at PAN 2013
No full text[EN] This overview presents the framework and results for the Author Profiling
task at PAN 2013. We describe in detail the corpus and its characteristics,
and the evaluation framework we used to measure the participants performance to
solve the problem of identifying age and gender from anonymous texts. Finally,
the approaches of the 21 participants and their results are described.The author profiling task @PAN-2013 was an activity of the WIQ-EI IRSES project (Grant No. 269180) within the FP 7 Marie Curie People Framework of the European Commission. We want to thank the Forensic Lab of the Universitat Pompeu Fabra Barcelona for sponsoring the award for the winner team. The work of the first author was partially funded by Autoritas Consulting SA and by Ministerio de Economía y Competitividad de España under grant ECOPORTUNITY IPT-2012-1220-430000. The work of the second author was in the framework the DIANA-APPLICATIONS-Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) project, and the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems. The work of fifth author was funded in part by the Swiss National Science Foundation (SNF) project "Mining Conversational Content for Topic Modelling and Author Identification (ChatMiner)" under grant number 200021_130208.Rangel, F.; Rosso, P.; Koppel, M.; Stamatatos, E.; Inches, G. (2013). Overview of the Author Profiling Task at PAN 2013. CLEF Conference on Multilingual and Multimodal Information Access Evaluation. 352-365. https://riunet.upv.es/handle/10251/46636S35236
Uncovering Plagiarism - Author Profiling at PAN
No full text[ES] PAN is a yearly workshop and evaluation lab on uncovering plagiarism, authorship, and social software misuse. Since 2009, PAN has been organizing benchmark activities on uncovering plagiarism, authorship, and social software misuse . An additional task - author profiling - has also recently been proposed. Author profiling, instead of focusing on individual authors, studies how language is shared by a class of people. Author profiling is a problem of growing importance in applications in forensics, security and marketing. For instance, a person working in the area of forensic linguistics may need to know the linguistic profile of a suspected text message (language used by a certain type of person) and identify characteristics (with language as evidence). Similarly, from a marketing viewpoint, companies may be interested in determining, through the analysis of blogs and online product reviews, what types of people like or dislike their products.Rosso, P.; Rangel Pardo, FM. (2014). Uncovering Plagiarism - Author Profiling at PAN. Ercim News. (96):49-49. https://riunet.upv.es/handle/10251/49303S49499
Overview of PAN 2018 : author identification, author profiling, and author obfuscation
No full textAbstract: PAN 2018 explores several authorship analysis tasks enabling a systematic comparison of competitive approaches and advancing research in digital text forensics. More specifically, this edition of PAN introduces a shared task in cross-domain authorship attribution, where texts of known and unknown authorship belong to distinct domains, and another task in style change detection that distinguishes between single-author and multi-author texts. In addition, a shared task in multimodal author profiling examines, for the first time, a combination of information from both texts and images posted by social media users to estimate their gender. Finally, the author obfuscation task studies how a text by a certain author can be paraphrased so that existing author identification tools are confused and cannot recognize the similarity with other texts of the same author. New corpora have been built to support these shared tasks. A relatively large number of software submissions (41 in total) was received and evaluated. Best paradigms are highlighted while baselines indicate the pros and cons of submitted approaches
Jonathan Scales Interview by Bob Danziger, 2019
No full textDr. Jeff Jones on Jonathan Scales:
I like this write up in Downbeat Magazine from earlier this year - http://downbeat.com/news/detail/jonathan-scales-extends-steel-pan-territory. Saying the same thing in my own words ... Jonathan Scales is an innovator. He has taken an instrument that is deeply connected to particular regional styles and is using it in a different context. In making his art he borrows freely from Caribbean styles, as well as jazz, classical, rock, funk, and more. This allows him to set expectations and then meet or subvert them at will. This keeps his music sounding fresh and exciting
E.: Overview of the Author Identification Task at PAN-2013
No full textAbstract. The author identification task at PAN-2014 focuses on author verification. Similar to PAN-2013 we are given a set of documents by the same author along with exactly one document of questioned authorship, and the task is to determine whether the known and the questioned documents are by the same author or not. In comparison to PAN-2013, a significantly larger corpus was built comprising hundreds of documents in four natural languages (Dutch, English, Greek, and Spanish) and four genres (essays, reviews, novels, opinion articles). In addition, more suitable performance measures are used focusing on the accuracy and the confidence of the predictions as well as the ability of the submitted methods to leave some problems unanswered in case there is great uncertainty. To this end, we adopt the c@1 measure, originally proposed for the question answering task. We received 13 software submissions that were evaluated in the TIRA framework. Analytical evaluation results are presented where one language-independent approach serves as a challenging baseline. Moreover, we continue the successful practice of the PAN labs to examine meta-models based on the combination of all submitted systems. Last but not least, we provide statistical significance tests to demonstrate the important differences between the submitted approaches.
Overview of the author identification task at PAN 2014
No full textThe author identification task at PAN-2014 focuses on author verification. Similar to PAN-2013 we are given a set of documents by the same author along with exactly one document of questioned authorship, and the task is to determine whether the known and the questioned documents are by the same author or not. In comparison to PAN-2013, a significantly larger corpus was built comprising hundreds of documents in four natural languages (Dutch, English, Greek, and Spanish) and four genres (essays, reviews, novels, opinion articles). In addition, more suitable performance measures are used focusing on the accuracy and the confidence of the predictions as well as the ability of the submitted methods to leave some problems unanswered in case there is great uncertainty. To this end, we adopt the c@1 measure, originally proposed for the question answering task. We received 13 software submissions that were evaluated in the TIRA framework. Analytical evaluation results are presented where one language-independent approach serves as a challenging baseline. Moreover, we continue the successful practice of the PAN labs to examine meta-models based on the combination of all submitted systems. Last but not least, we provide statistical significance tests to demonstrate the important differences between the submitted approaches
Tweet Author Gender Identification. PAN 2016 Task
No full textThe paper presents an experiment of tweet’s author gender detection. We used PAN 2016 data and task description and have build an application that decides whether an analysed tweet has been written by man or woman. Multiple texts’ characteristics are used as features in the application, such as: references to pictures, to web pages, to other people, emojis, hashtags and a number of words that are associated with tweets written by women and men respectively. For 100 random tweets we obtained average accuracy 0.61. This is good result although it is not as good as the best one in PAN 2016 task
A historical comment about the GVT in short interval
No full textIn this article, the author introduces the history, progress and method in the Goldbach-Vinogradov Theorem in short interval by which every sufficiently large odd integer could be expressed as the sum of three almost equal prime numbers.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000183488400018&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701MathematicsCPCI-S(ISTP)
Electrospun Polyacrylonitrile Silver Nanoparticle (PAN-AgNP) Nanocomposites as Alternative Antimicrobial Materials
No full textInfectious microbial diseases can easily be transferred from person to person in the air or via high contact surfaces. As a result, researchers must aspire to create materials that can be implemented in surface contact applications to disrupt pathogen growth and transmission. Silver (Ag) is known to possess antimicrobial activity and has been used in the past in various pharmaceutical applications. Herein, we examine the antimicrobial properties of polyacrylonitrile (PAN) nanofibers coated with different concentrations of silver nanoparticles (AgNPs). Polyacrylonitrile (PAN) was homogenized with varied weight concentrations of silver nitrate (AgNO3) in N,N-Dimethylformamide (DMF) solution, a common organic solvent that serves as both an electrospinning solvent and as a reducing agent that forms AgNPs. The subsequent colloids were electrospun into nanofibers, which were then characterized via various analysis techniques, including Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Energy Dispersive X-Ray (EDX) Analysis, Dynamic Light Scattering (DLS), and X-Ray Photoelectron Spectroscopy (XPS). 10 microbes, including 7 strains of Gram-positive bacteria, 2 strains of Gram-negative bacteria, and Candida albicans were incubated with cutouts of various PAN-AgNP nanocomposites using disk diffusion methods to test for the nanocomposites’ antimicrobial efficiency. We report that PAN-AgNP nanocomposites retain a certain degree of antimicrobial longevity; samples stored for approximately 90 days demonstrate similar antimicrobial activity against Escherichia coli (E. coli) and Lactobacillus crispatus (L. crispatus) when compared to their newly electrospun counterparts. Moreover, our results indicate that PAN-AgNP nanocomposites successfully display antimicrobial activity against various bacteria and fungi strains regardless of their resistance to conventional antibiotics. Our study demonstrates that PAN-AgNP nanocomposites can potentially be applied to surfaces at risk of contracting microbial infections
Pan-Arctic land-ice and tundra meltwater discharge database from 1950 to 2021
No full textA high resolution (daily, 250m) land ice and tundra meltwater discharge dataset for the period 1950-2021 in an easily accessible and storage efficient database covering most of the Arctic and sub-Arctic North Atlantic (SNA) ocean region, i.e. Canadian Arctic Archipelago, Greenland, Iceland, Svalbard, Russian Arctic Islands. We distribute 3 files for each Randolph Glacier Inventory v.6.0 first order region studied. These regions are RGI-03 Arctic Canada North (CanadaN), RGI-04 Arctic Canada South (CanadaS), RGI-05 Greenland (Greenland), RGI-06 Iceland (Iceland), RGI-07 Svalbard and Jan Mayen (Svalbard), RGI-09 Russian Arctic (RussiaN). In addition, we distribute a single pan-Arctic file (panArctic_MonthlyBasinRunoff.nc). Meltwater discharge is derived from daily ~6 km regional climate model, Modéle Atmosphérique Régional (MAR), runoff simulations that are statistically downscaled and routed to the coastlines. The statistical downscaling algorithm uses native vertical gradients of the MAR data and high resolution (250 m) DEM, land mask (Copernicus GLO-90) and ice mask (GIMP, RGI) datasets. Routing to coastal outflow points is performed by a hydrological routing scheme applied to the high-resolution DEM and the downscaled runoff. Meltwater components from non-glaciated land, bare glacier ice and glaciated area above the snowline are separated to facilitate further analysis
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