8 June: FYI -- NLP PhD funding, France
Index of June 2016 | Index of year: 2016 | Full index
PhD position at University Paris Saclay, Orsay (near Paris), France
More and more information on individuals (e.g., persons, events, biological
objects) are available electronically in a structured or semi-structured form.
However, selecting individuals satisfying certain complex constraints manually
is a complex, error-prone, and time and personnel-consuming effort. To this
end, tools that can (semi-)automatically answer questions based on
heterogeneous data need to be developed, as exampled by IBM Watson system.
This Ph.D project is to deal with instance extraction problem for applications
that involve rich background domain knowledge, such as searching electronic
patient records for eligible patients satisfying non-trivial combinations of
certain properties, e.g., eligibility criteria for clinical trials. We name
this task complex question answering.
While simple questions can directly be expressed and answered using keywords
in natural language, complex questions that can refer to type and relational
information will increase the precision of retrieved results, and thus reduce
the effort for posterior manual verification of the results.
Formal queries are powerful in this context, in representing complex questions
and exploring background knowledge; however they are often difficult to
master, which makes such an advanced answering system impractical if without a
user adapted interface. To resolve the problem, this PhD project is to
provide a user with the possibility to formulate her need with natural
language questions that can be complex pieces of texts. Apart from this easier
interface, natural language will enable us to formulate constraints that
cannot be represented formally due to the expressiveness limits of formal
languages, but that can be directly verified using textual data.
***Ph.D Work***
To achieve the complex question answering, this PhD project is to develop a
novel answering question paradigm that integrates both formal database-like
query answering and texts based question answering by information extraction
methods. This is because these are two important approaches for complex
question answering, but of each own advantages. To benefit from both methods,
a key contribution of this PhD work will be the approaches for combining
answers to a formal query with answers found based on information retrieval
techniques, which has been identified as a challenge in question answering
systems.
It is to study the hybrid complex question answering systems by taking into
account the limits of both ontological reasoning and text processing
approaches alone. In particular, the following approaches
need to be developed:
- Text-for-ontology search: selecting relevant cases by text-based retrieval
for defining a subset of individuals to reduce the calculation complexity of
formal queries.
- Ontology driven search: querying the populated ontology for selecting
potential relevant individuals and related texts, and reranking these
individuals by verifying remaining unstructured information on them.
- Hybrid answer production: producing final answers to a question by comparing
and then combining the results from ontology based reasoning method and text
based processing method.
***Required profile***
Master in Computer Science or related domain
Knowledge in Semantic Web, Information Extraction, and/or Artificial
Intelligence is required. Background in Natural Language Processing,
Automatic Reasoning or Information Retrieval is desired.
Programming: Java, python
Language: good English level, French is not required
Ability to work in team, motivation on multidiscipline studies
***Documents required for application***
CV, motivation letter, and recommendation letters
Transcripts for Master and undergraduate courses
Please send your applications to brigitte.grau_at_limsi.fr and
yue.ma_at_lri.fr as soon as possible.
--
http://perso.limsi.fr/Individu/bg/
Groupe ILES - LIMSI
Bât. 508, rue John von Neumann 91405 ORSAY Cedex
tel. 01 69 85 80 03, fax 01 69 85 80 88
et
ENSIIE
Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise
1 square de la résistance, 91025 EVRY Cedex
tel. 01 69 36 73 44, fax 01 69 36 73 09
Index of June 2016 | Index of year: 2016 | Full index