SemPub2016

From Openresearch
Revision as of 15:03, 28 April 2016 by Sahar (talk | contribs) (Submissions)
Jump to: navigation, search
SemPub2016
Semantic Publishing Challenge 2016
Event in series Semantic Publishing Challenge
Dates May 29 2016 (iCal) - June 02 2016
Homepage: https://github.com/ceurws/lod/wiki/SemPub2016
Location
Location: Crete, Heraklion, Greece
Loading map...

Important dates
Abstracts: 2016/01/18
Papers: 2016/03/11
Camera ready due: 2016/04/24
Table of Contents


The following coordinate was not recognized: Geocoding failed.
The following coordinate was not recognized: Geocoding failed.


Enter your description here. Maybe just paste in the call for papers.

Topics

This is the next iteration of the successful Semantic Publishing Challenge of ESWC 2014 and 2015. We continue pursuing the objective of assessing the quality of scientific output, evolving the dataset bootstrapped in 2014 and 2015 to take into account the wider ecosystem of publications.

To achieve that, this year’s challenge focuses on refining and enriching an existing linked open dataset about workshops, their publications and their authors. Aspects of “refining and enriching” include extracting deeper information from the HTML and PDF sources of the workshop proceedings volumes and enriching this information with knowledge from existing datasets.

Thus, a combination of broadly investigated technologies in the Semantic Web field, such as Information Extraction (IE), Natural Language Processing (NLP), Named Entity Recognition (NER), link discovery, etc., is required to deal with the challenge’s tasks.

Submissions

We ask challengers to automatically annotate a set of multi-format input documents and to produce a LOD that fully describes these documents, their context, and relevant parts of their content. The evaluation will consist of evaluating a set of queries against the produced dataset to assess its correctness and completeness.

The primary input dataset is the LOD that has been extracted from the CEURWS.org workshop proceedings using the winning extraction tools of the 2014 and 2015 challenges, plus its full original HTML and PDF source documents. In addition, the challenge uses (as linking targets) existing LOD on scholarly publications.

The input dataset will be split in two parts: a training dataset and an evaluation dataset, which will disclosed a few days before the submission deadline. Participants will be asked to run their tool on the evaluation dataset and to produce the final Linked Dataset and the output of the queries on that dataset.

Further details about the organization are provided in the general rules page.

The Challenge will include three tasks:

Task 1: Extraction and assessment of workshop proceedings information

Participants are required to extract information from a set of HTML tables of contents and PDF papers published in CEURWS.org workshop proceedings. The extracted information is expected to answer queries about the quality of these workshops, for instance by measuring growth, longevity, etc. The task is an extension of the Task 1 of the 2014 and 2015 Challenges: we will reuse the most challenging quality indicators from last year’s challenge, others will be defined more precisely, others will be completely new.

Task 2: Extracting information from the PDF full text of the papers

Participants are required to extract information from the textual content of the papers (in PDF). That information should describe the organization of the paper and should provide a deeper understanding of the context in which it was written. In particular, the extracted information is expected to answer queries about the internal organization of sections, tables, figures and about the authors’ affiliations and research institutions, and fundings source. The task mainly requires PDF mining techniques and some NLP processing.

Task 3: Interlinking

Participants are required to interlink the CEURWS.org linked dataset with relevant datasets already existing at the Linked Open Data cloud. In particular, they are expected to interlink persons, papers, events, organizations and publications. All these entities should be identified, disambiguated and interlinked to their correspondences at other LOD datasets. Task 3 can be accomplished either as a named entity recognition and disambiguation task (NLP based entity linking), or as an entity interlinking task, or as a combination of methods.

Important Dates

Committees

  • Local Organizing Co-Chairs