- From: Michel Dumontier <michel.dumontier@gmail.com>
- Date: Mon, 20 Jan 2014 05:25:09 -0800
- To: w3c semweb hcls <public-semweb-lifesci@w3.org>
- Cc: Saeedeh Shekarpour <sa.shekarpour@gmail.com>
- Message-ID: <CALcEXf6h+Z0=k_UC-sSXPttCGOojdYF_sc3m4r=7pwoeWscaBw@mail.gmail.com>
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
Received on Monday, 20 January 2014 13:25:57 UTC