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MeaningCloud sponsors the award for Author Profiling Research at PAN also in 2018

Author Profiling and Text Forensics Research

CLEF Conference 2018Since 2009 the PAN Lab organizes shared tasks on digital text forensics in general, and in author profiling in particular. Pan Lab is part of CLEF, the European Conference and Evaluation Forum around Information Retrieval. CLEF consists of an independent peer-reviewed conference on a broad range of issues in the field of multilingual and multimodal information access evaluation, and a set of labs and workshops designed to test different aspects of mono and cross-language information retrieval systems. CLEF 2018 will be hosted by the University of Avignon, France, 10-14 September 2018.

MeaningCloud has been sponsoring the award to the best performing team in the author profiling task at CLEF since 2015.

Author profiling is a task that given a document has the aim to infer what are the traits of its author.
In 2017 the task focused on gender and language variety identification in Twitter addressing four languages and several of their varieties: English (Australia, Canada, Great Britain, Ireland, New Zealand, United States), Spanish (Argentina, Chile, Colombia, Mexico, Peru, Spain, Venezuela), Portuguese (Brazil, Portugal), and Arabic (Egypt, Gulf, Levantine, Maghrebi).

Paolo Rosso delivers the 2017 PAN Author Profiling Price to the team of University of Groningen

Paolo Rosso delivers the 2017 PAN Price to the team of University of Groningen

Twenty-two were the participating teams from all over the world in 2017 and the best results were obtained by Angelo Basile, Gareth Dwyer, Maria Medvedeva, Josine Rawee, Hessel Haagsma, and Malvina Nissim, from the University of Groningen, The Netherlands.

This year the task will go multimodal and not only textual information in tweets will be taken into account but also images of URLs will be used as information sources in order to infer gender demographics. Three will be the languages that will be addressed: English, Spanish and Arabic [http://pan.webis.de/clef18/pan18-web/author-profiling.html].

Paolo Rosso
Universitat Politècnica de València, Spain
Co-organizer of the author profiling task at PAN

References

Rangel F., Rosso P., Potthast M., Stein B. (2017). Overview of the 5th Author Profiling Task at PAN 2017: Gender and Language Variety Identification in Twitter. In: Cappellato L., Ferro N., Goeuriot L, Mandl T. (Eds.) CLEF 2017 Labs and Workshops, Notebook Papers. CEUR Workshop Proceedings. CEUR-WS.org, vol. 1866. [http://ceur-ws.org/Vol-1866/invited_paper_11.pdf]

Potthast M., Rangel F., Tschuggnall M., Stamatatos E., Rosso P., Stein B. (2017). Overview of PAN’17: Author Identification, Author Profiling, and Author Obfuscation. In: 8th Int. Conf. of CLEF on Experimental IR Meets Multilinguality, Multimodality, and Visualization, CLEF 2017,
Springer-Verlag, LNCS(10456), pp. 275–290 [http://www.uni-weimar.de/medien/webis/publications/papers/stein_2017k.pdf]


Applying text analytics to financial compliance

In one of our previous posts we talked about Financial Compliance, FinTech and its relation to Text Analytics. We also showed the need for normalized facts for mining text in search of suspects of financial crimes and proposed the form SVO (subject, verb, object) to do so.

financial crime

Financial crime

Thus, we had defined clause as the string within the sentence capable to convey an autonomous fact. Finally, we had explained how to integrate with the Lemmatization, PoS and Parsing API in order to get a fully syntactic and semantic enriched JSON-formatted tree for input text, from which we will work extracting SVO clauses.

In this post, we are going to continue with the extraction process, seeing in detail how to work to extract those clauses from the response returned by the Parsing API.

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How to build a Financial Compliance model ready for FinTech

What is Financial Compliance and what is FinTech?

financial crime

Financial crime

Financial crime has increasingly become of concern to governments throughout the world. The emergence of vast regulatory environments furthered the degree of compliance expected even from other non-governmental organizations that conduct financial transactions with consumers, including credit card companies, banks, credit unions, payday loan companies, and mortgage companies.

Technology has helped financial services address the increased burden of compliance in innovative ways which have also yielded other benefits, including improved decision-making, better risk management, and an enhanced user experience for the consumer or investor.

The rapid development and employment of AI (Artificial Intelligence) techniques within this specific domain have the potential to transform the financial services industry.

FinTech (Financial Technology) solutions have recently arised as the new applications, processes, products, or business models in the financial services industry, composed of one or more complementary financial services and provided as an end-to-end process via the Internet. You can find additional interesting information in this article.

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MeaningCloud sponsors prize for Author Profiling Research

Author Profiling ResearchCLEF Initiative and Conference

MeaningCloud sponsors the prize to the best team at the 5th International Competition on Author Profiling Research, PAN@CLEF 2017. This competition is part of PAN (Plagiarism, Authorship and Social Software Misuse), a series of scientific events and shared tasks on digital text forensics. The 17th evaluation lab on digital text forensics will be held as part of the CLEF conference in Dublin, Ireland, on September 11-14, 2017.

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