| More Information: | TITLE: "Mining, Processing, and Reasoning over Textual Arguments"
Description:
Large amounts of text are added to the Web daily from social media, web-based
commerce, scientific papers, eGovernment consultations, etc. Such texts are used
to make decisions in the sense that people read the texts, carry out some
informal analysis, and then (in the best case) make a decision; for example, a
consumer might read the comments on an Amazon website about a camera before
deciding what camera to buy. The problem is that such information is
distributed, unstructured, and not cumulative. In addition, the argument
structure - justifications for a claim and criticisms - might be implicit or
explicit within some document, but harder to discern across documents. The sheer
volume of information overwhelms users. Given all these problems, reasoning
about arguments on the web is currently unfeasible.
A solution to these problems would be to develop tools to aggregate, synthesize,
structure, summarize, and reason about arguments in texts. Such tools would
enable users to search for particular topics and their justifications, trace
through the argument (justifications for justifications and so on), as well as
to systematically and formally reason about the graph of arguments. By doing so,
a user would have a better, more systematic basis for making a decision.
However, deep, manual analysis of texts is time-consuming, knowledge intensive,
and thus unscalable. To acquire, generate, and transmit the arguments, we need
scalable machine-based or machine-supported approaches to extract arguments. The
application of tools to mine arguments would be very broad and deep given the
variety of contexts where arguments appear and the purposes they are put to.
In this context, the goal of the Ph.D. is to address the following challenges:
I) define algorithms for automatically identifying arguments in texts. Th e goal
is to detect, at an abstract level, the argumentative structures in texts . In
addition, challenges like the automated discrimination between argumentative and
non-argumentative text units, and the identification of reused, but manipulated,
arguments which convey a different meaning than what was intended by their
source, will be addressed .
ii) propose i ntra-argument mining algorithms, to automatically detect the
internal structure of arguments. The goal is to analy ze and formaliz e the
internal structure of the retrieved arguments, i.e., the identification of the
relations that may hold between the arguments’ premises and conclusion, using
the RTE (Recognizing Textual Entailment) framework.
i ii) propose inter-argument mining algorithms, to automatically detect
relations between arguments. T he goal is to identif y the relations between
arguments, extending RTE to account for more sophisticated relations like
support, partial support, attack.
References:
- Proceedings of the Workshop on Frontiers and Connections between Argumentation
Theory and Natural Language Processing http://ceur-ws.org/Vol-1341/
- Lippi, M., Torroni, P., Argumentation Mining: State of the Art and Emerging
Trends , ACM Transactions on Internet Technology, 2015.
- Elena Cabrio, Serena Villata :A natural language bipolar argumentation
approach to support users in online debate interactions†. Argument &
Computation 4(3) : 209-230 (2013)
- Available resources for Argument mining
http://argumentationmining.disi.unibo.it/resources.html
Skills and profile:
• Master degree in Computer Science or Computational Linguistics is required.
• Programming skills.
• Basic knowledge of logic (propositional, first order) is preferred.
• Basic knowledge of Natural Language Processing and Machine Learning is
preferred.
• Fluent English required, both oral and written. French is not mandatory.
Doctoral scholarship content:
The Université Côte d’Azur (UCA) Doctoral Program of Excellence offers
scholarships consisting of an annual service-free contract with a salary of 2500
€ per month, guaranteed for a maximum duration of four years.
This includes a three-year doctoral contract, plus an extra year that can be
split between a pre-doctoral training and a post-doctoral project in order to
value the thesis research results.
This comes with a support of up to 1500 € / year to defray the costs of
participation in international conferences or workshops, together with funding
for a six-month extra-doctoral activity consisting either of a collaborative
visit to a foreign research institute or a collaborative study with a
non-academic partner. Privileged conditions of accommodation will be offered.
Hosting team:
WIMMICS (http://wimmics.inria.fr/) is a research team of Université Côte
d’Azur (UCA). The research fields of this team are graph-oriented knowledge
representation, reasoning and operationalization to model and support actors,
actions and interactions in web-based epistemic communities.
Location: I3S laboratory, Sophia Antipolis, France.
Applications : a curriculum vitae together with a motivation letter should be
sent to Serena Villata: villata@i3s.unice.fr and Elena Cabrio:
elena.cabrio@unice.fr .
Deadline for applications: March 1 st , 2017. |