{"id":1509,"date":"2015-02-19T12:05:55","date_gmt":"2015-02-19T12:05:55","guid":{"rendered":"https:\/\/www.arg.tech\/?page_id=1509"},"modified":"2015-02-19T12:05:55","modified_gmt":"2015-02-19T12:05:55","slug":"argument-analytics-project","status":"publish","type":"page","link":"https:\/\/www.arg.tech\/index.php\/argument-analytics-project\/","title":{"rendered":"“Argument Analytics” project"},"content":{"rendered":"
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The R&D project \u201cArgument Analytics\u201d is funded by the Technology Strategy Board (TSB)<\/a> and the Engineering and Physical Sciences Research Council (EPSRC)<\/a> within the scope of Technology-inspired innovation \u2013 ICT, and specifically in the area of \u201cBig data exploration\u201d<\/strong>. The research sits on the border of the areas of computer models of argument, natural language processing and big data. Our aim is to provide technologies for processing, navigating, manipulating and exploring argument structures through the big datasets of texts in natural language.<\/p>\n

The research is led by Dr. Katarzyna Budzynska<\/a> with regular contact with the industrial partner of the project. We are working with Prof. Chris Reed<\/a> and a PhD student who will start on an EPSRC DTG-funded project \u201cRecognizing Trust in Natural Language\u201d<\/a>, as well as with our collaborators in IRIT Toulouse<\/a> (discourse processing and opinion mining, computational linguistics); University of Potsdam<\/a> (discourse generation and speech act theory, computational linguistics); Polish National Academy of Sciences<\/a> at Warsaw (logic and philosophy of communication); and Universit\u00e0 della Svizzera italiana<\/a> in Lugano (pragmatics of financial communication, communication studies).<\/p>\n

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The project selects two of the most promising technologies with differing risk profiles \u2013 argument mapping and argument mining \u2013 and aims to develop industrial proof of concept demonstrators that integrate them as Argument Analytics platform technologies<\/strong> in a commercial market estimated to be worth \u00a311bn in 2013.<\/p>\n

Argument mining<\/strong> exploits the techniques and methods of natural language processing, or more specifically \u2013 text and opinion mining, for semi-automatic and automatic recognition and extraction of structured argument data from unstructured natural language texts. Where opinion mining has focused on the identification of broad sentiment from a text (popular with corporate marketing departments in large companies eager to know if comments online are positive or negative about their products), argument mining aims to identify reason-conclusion structures that can lead to models of why people hold the positions they do (which provides even more desirable information for developing of marketing strategies).<\/p>\n

The group in Dundee has a strong record in developing technologies for argument mapping<\/strong>, in particular software tools that allow for the representation and the visualisation of argument structures. The project aims to expand the functionality of these tools in order to adopt them for the needs of a commercial domain targeted by the industrial partner, as well as to allow for the exploration of the space of massive datasets semi-automatically analysed by argument mining tool against deep argument structures.<\/p>\n

We adopt an agile approach to the software engineering, with a focus on rapid prototyping<\/strong> combined with frequent and regular evaluation and feedback from engineers working for the industrial partner. The consortium is committed to maintaining strong links with its potential users.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

The R&D project \u201cArgument Analytics\u201d is funded by the Technology Strategy Board (TSB) and the Engineering and Physical Sciences Research Council (EPSRC) within the scope of Technology-inspired innovation \u2013 ICT, and specifically in the area of \u201cBig data exploration\u201d. The research sits on the border of the areas of computer models of argument, natural language […]<\/p>\n","protected":false},"author":8,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1509","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.arg.tech\/index.php\/wp-json\/wp\/v2\/pages\/1509","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.arg.tech\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.arg.tech\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.arg.tech\/index.php\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/www.arg.tech\/index.php\/wp-json\/wp\/v2\/comments?post=1509"}],"version-history":[{"count":6,"href":"https:\/\/www.arg.tech\/index.php\/wp-json\/wp\/v2\/pages\/1509\/revisions"}],"predecessor-version":[{"id":1690,"href":"https:\/\/www.arg.tech\/index.php\/wp-json\/wp\/v2\/pages\/1509\/revisions\/1690"}],"wp:attachment":[{"href":"https:\/\/www.arg.tech\/index.php\/wp-json\/wp\/v2\/media?parent=1509"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}