[DL] PhD position in Ontology and NLp

Yue Ma yue.ma at lri.fr
Mon Jun 20 18:59:47 CEST 2016


PhD position at University Paris Saclay, Orsay (near Paris), France

Title: Hybrid Question Answering over Heterogeneous Data
Laboratories:
         LRI, CNRS UMR 8623, Université Paris Sud, France
         LIMSI, CNRS, Université Paris-Saclay, France
Supervisors: Brigitte Grau (LIMSI);  Yue Ma (LRI)
Project context: GoASQ (ANR international project with TU Dresden, Germany)
Financial support: ANR
Start Date: as soon as possible (latest December 1, 2016)
Duration:  three years
Application Deadline:  open until filled (1st round of interview will be by
the end of June, 2016)

***Motivations***
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.


-- 
Maître de Conférences
Laboratoire de Recherche en Informatique (LRI - CNRS) <http://www.lri.fr/>
Université Paris-Sud <http://www.u-psud.fr/>
91405 Orsay Cedex
Tel : 01 69 15 57 54
Bureau : 175/PCRI-S



-- 
Maître de Conférences
Laboratoire de Recherche en Informatique (LRI - CNRS) <http://www.lri.fr/>
Université Paris-Sud <http://www.u-psud.fr/>
91405 Orsay Cedex
Tel : 01 69 15 66 80
Bureau : 175/PCRI-S
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