Apologies for multiple posting.

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LD4IE 2016
The 4th international Workshop on Linked Data for Information Extraction
in conjunction with The 14th International Semantic Web Conference (ISWC 2016)
Kobe, Japan October 17-21, 2016
http://iswc2016.semanticweb.org/

Workshop website: http://web.informatik.uni-mannheim.de/ld4ie2016
Twitter: @LD4IE #LD4IE #LD4IE2016
Facebook page: Ld4ie2016 (at https://www.facebook.com/Ld4ie2014)


*************** Call for Papers ***************

This workshop focuses on the exploitation of Linked Data for Web Scale Information Extraction (IE), which concerns extracting structured knowledge from unstructured/semi-structured documents on the Web.
One of the major bottlenecks for the current state of the art in IE is the availability of learning materials (e.g., seed data, training corpora), which, typically are manually created and are expensive to build and maintain.
Linked Data (LD) defines best practices for exposing, sharing, and connecting data, information, and knowledge on the Semantic Web using uniform means such as URIs and RDF.
It has so far been created a gigantic knowledge source of Linked Open Data (LOD), which constitutes a mine of learning materials for IE.
However, the massive quantity requires efficient learning algorithms and the unguaranteed quality of data requires robust methods to handle redundancy and noise.
LD4IE intends to gather researchers and practitioners to address multiple challenges arising from the usage of LD as learning material for IE tasks, focusing on (i) modelling user defined extraction tasks using LD; (ii) gathering learning materials from LD assuring quality (training data selection, cleaning, feature selection etc.); (ii) robust learning algorithms for handling LD; (iv) publishing IE results to the LOD cloud.

*************** Research Topics ***************

Topics of interest include, but are not limited to:

* Modelling Extraction Tasks
**** modelling extraction tasks (e.g. defining IE templates using LD ontologies)
**** extracting and building knowledge patterns based on LD
**** user friendly approaches for querying LD

* Information Extraction
**** selecting relevant portions of LD as training data
**** selecting relevant knowledge resources from LD
**** IE methods robust to noise in LD as training data
**** IE tasks/applications exploiting LD (Wrapper induction, Table interpretation, IE from unstructured data, Named Entity Recognition, Relation Extraction, Topic Modelling…)
**** linking extracted information to existing LD datasets

* Linked Data for Learning
**** assessing the quality of LD data for training
**** select optimal subset of LD to seed learning
**** managing heterogeneity, incompleteness, noise, and uncertainty of LD
**** scalable learning methods using LD
**** pattern extraction from LD

* Special interest: IE using Web Data Commons corpus
**** any IE tasks using (part of) the Web Data Commons corpus [1]

[1] http://webdatacommons.org/structureddata/


*************** Important Dates ***************

Abstract submission deadline: July 1, 2016
Paper submission deadline: July 7, 2016
Acceptance Notification: July 31, 2016
Camera-ready versions: August 7, 2016
Workshop date: to be announced (17-21 October 2016)


*************** Submission ********************

We accept the following formats of submissions:
Research Papers
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Full paper with a maximum of 12 pages including references.
Short paper with a maximum of 6 pages including references.
Two formats are possible for the submission: PDF and HTML.

All submissions must be written in English.
PDF submissions must be formatted according to the information for LNCS Authors (http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0.).

We would like to encourage you to submit your paper as HTML, in which case you need to submit a zip archive containing an HTML file and all used resources.
If you are new to HTML submission these are good places to start:
- Linked Research: Example paper using LNCS layout is at http://linked-research.270a.info/
- Research Articles in Simplified HTML (RASH) format: documentation and stylesheets at https://github.com/essepuntato/rash

In order to check if your HTML submission is compliant with the page limit constraint, please use one of the LNCS layouts and printing/storing it as PDF.

Please submit your contributions electronically in PDF or HTML format to EasyChair at https://www.easychair.org/conferences/?conf=ld4ie2016
When submitting your paper, select the appropriate topic between:
* Research - long paper
* Research - short paper

Accepted papers will be published online via CEUR-WS.

*************** Workshop Chairs ***************

Anna Lisa Gentile, University of Mannheim, Germany
Claudia d'Amato, University of Bari, Italy
Ziqi Zhang, University of Sheffield, UK
Heiko Paulheim, University of Mannheim, Germany