Re: invited talk: SINA:Semantic Interpretation of User Queries for Question Answering on Interlinked Data

Hi folks,
  Apologies, but we ran into some technical problems and we had to cancel
today's talk in favor of rescheduling it for next week Wednesday January 29
at 11:00am EDT.

See you then!

m.


On Mon, Jan 20, 2014 at 5:25 AM, Michel Dumontier <
michel.dumontier@gmail.com> wrote:

> Hi everybody,
>   Please join us on Tuesday at 11am EDT for a talk by Saeedeh Shekarpour.
>
> Dial-In #:     +1.617.761.6200 (Cambridge, MA)
> VoIP address:  sip:zakim@voip.w3.org
> Access Code: 4257 ("HCLS")
> IRC Channel:   irc.w3.org port 6665 channel #HCLS
>
> *Title: *SINA:Semantic Interpretation of User Queries for Question
> Answering on Interlinked Data
>
> *Abstract*:  The  Data  Web  contains  a  wealth  of  knowledge  on  a
>  large  number  of  domains. Question answering over interlinked data
>  sources  is  challenging  due  to   two   inherent  characteristics.
> First,   different  datasets  employ  heterogeneous  schemas  and each one
>  may  only  contain  a  part   of   the answer  for  a   certain  question.
>  Second,  constructing   a federated  formal  query across different
> datasets  requires   exploiting  links   between   the  different
> datasets   on   both  the   schema   and instance  levels.  We  present  a
>  question answering  system,  which  transforms  user  supplied  queries
> (i.e.  natural   language  sentences  or  keywords)   into  conjunctive
> SPARQL queries over a set of interlinked data sources. The contribution of
> this work is as follows:
> 1. A   novel  approach  for  determining  the  most  suitable   resources
>  for  a  user­supplied  query  from   different datasets  (disambiguation).
>  We   employ   a  hidden   Markov   model,   whose  parameters  were
>  bootstrapped  with   different distribution functions.
> 2. A  novel   method   for   constructing  a  federated  formal  queries
> using   the disambiguated resources  and leveraging the  linking  structure
>  of  the  underlying  datasets. This  approach  essentially relies on a
>  combination  of  domain  and range inference   as   well  as  a   link
>  traversal   method   for   constructing  a  connected  graph  which
> ultimately  renders  a corresponding  SPARQL  query. The results of our
> evaluation with three life­science  datasets  and 25 benchmark queries
> demonstrate the effectiveness of our approach.
>
> *Biography*: Saeedeh Shekarpour is a PhD student at the Institute  for
>  Applied  Computer  Science  at  University  of  Bonn  &  AKSW  research
>  group,  Institute  of Computer Science(IfI), Leipzig University,  Leipzig,
> Germany, under superviosn of Dr. Soren Auer. She spent the three and half
> years of my PhD in the field of “Question Answering on Interlinked Data”.
> Her research interests are the following fields: Question Answering,
> Semantic Search, Semantic Web, Information Retrieval. During her PhD, She
> worked with the AKSW research group [2] (a leading group in Semantic Web).
> In addition to gaining experience in the field of semantic web while
> working with this group, She initiated a project called SINA (a Semantic
> Search Engine over Interlinked Data).
>
> --
> Michel Dumontier
> Associate Professor of Medicine (Biomedical Informatics), Stanford
> University
> Chair, W3C Semantic Web for Health Care and the Life Sciences Interest
> Group
> http://dumontierlab.com
>



-- 
Michel Dumontier
Associate Professor of Medicine (Biomedical Informatics), Stanford
University
Chair, W3C Semantic Web for Health Care and the Life Sciences Interest Group
http://dumontierlab.com