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

slides for today's talk are available at

http://www.slideshare.net/shekarpour/sina-presentation-in-ibm

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