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AKSW Colloquium: Tommaso Soru and Martin Brümmer on Monday, March 2 at 3.00 p.m.

February 27, 2015 - 1:57 pm by AmrapaliZaveri - No comments »

On Monday, 2nd of March 2015, Tommaso Soru will present ROCKER, a refinement operator approach for key discovery. Martin Brümmer will then present NIF annotation and provenance – A comparison of approaches.

Tommaso Soru – ROCKER – Abstract

As within the typical entity-relationship model, unique and composite keys are of central importance also when their concept is applied on the Linked Data paradigm. They can provide help in manifold areas, such as entity search, question answering, data integration and link discovery. However, the current state of the art does not count approaches able to scale while relying on a correct definition of key. We thus present a refinement-operator-based approach dubbed ROCKER, which has shown to scale to big datasets with respect to the run time and the memory consumption. ROCKER will be officially introduced at the 24th International Conference on World Wide Web.

Tommaso Soru, Edgard Marx, and Axel-Cyrille Ngonga Ngomo, “ROCKER – A Refinement Operator for Key Discovery”. [PDF]

Martin Brümmer - Abstract – NIF annotation and provenance – A comparison of approaches

The uptaking use of the NLP Interchange Format (NIF) reveals its shortcomings on a number of levels. One of these is tracking metadata of annotations represented in NIF – which NLP tool added which annotation with what confidence at which point in time etc.

A number of solutions to this task of annotating annotations expressed as RDF statements has been proposed over the years. The talk will weigh these solutions, namely annotation resources, reification, Open Annotation, quads and singleton properties in regard to their granularity, ease of implementation and query complexity.

The goal of the talk is presenting and comparing viable alternatives of solving the problem at hand and collecting feedback on how to proceed.

AKSW Colloquium: Edgard Marx and Tommaso Soru on Monday, February 23, 3.00 p.m.

February 19, 2015 - 10:53 pm by TommasoSoru - No comments »

On Monday, 23rd of February 2015, Edgard Marx will introduce Smart, a search engine designed over the Semantic Search paradigm; subsequently, Tommaso Soru will present ROCKER, a refinement operator approach for key discovery.

EDIT: Tommaso Soru’s presentation was moved to March 2nd.

Abstract – Smart

Since the conception of the Web, search engines play a key role in making content available. However, retrieving of the desire information is still significantly challenging. Semantic Search systems are a natural evolution of the traditional search engines. They promise more accurate interpretation by understanding the contextual meaning of the user query. In this talk, we will introduce our audience to Smart, a search engine designed over the Semantic Search paradigm. Smart incorporates two of our currently designed approaches of dealing with the problem of Information Retrieval, as well as a novel interface paradigm. Moreover, we will present some of the former, as well as more recent state-of-the-art approaches used by the industry – for instance by Yahoo!, Google and Facebook.

Abstract – ROCKER

As within the typical entity-relationship model, unique and composite keys are of central importance also when their concept is applied on the Linked Data paradigm. They can provide help in manifold areas, such as entity search, question answering, data integration and link discovery. However, the current state of the art does not count approaches able to scale while relying on a correct definition of key. We thus present a refinement-operator-based approach dubbed ROCKER, which has shown to scale to big datasets with respect to the run time and the memory consumption. ROCKER will be officially introduced at the 24th International Conference on World Wide Web.

Tommaso Soru, Edgard Marx, and Axel-Cyrille Ngonga Ngomo, “ROCKER – A Refinement Operator for Key Discovery”. [PDF]

AKSW Colloquium: Konrad Höffner and Michael Röder on Monday, February 16, 3.00 p.m.

February 16, 2015 - 1:45 pm by KonradHoeffner - No comments »

CubeQA—Question Answering on Statistical Linked Data by Konrad Höffner

Abstract

Question answering systems provide intuitive access to data by translating natural language queries into SPARQL, which is the native query language of RDF knowledge bases. Statistical data, however, is structurally very different from other data and cannot be queried using existing approaches. Building upon a question corpus established in previous work, we created a benchmark for evaluating questions on statistical Linked Data in order to evaluate statistical question answering algorithms and to stimulate further research. Furthermore, we designed a question answering algorithm for statistical data, which covers a wide range of question types. To our knowledge, this is the first question answering approach for statistical RDF data and could open up a new research area.
See also the paper (preprint, under review) and the slides.

News from the WSDM 2015 by Michael Röder

Abstract

The WSDM conference is one of the major conferences for Web Search and Data Mining. Michael Röder was attending this years WSDM conference in Shanghai and wants to present a short overview over the conference topics. After that, he wants to take a closer look at FEL – an entity linking approach for search queries peresented at the conference.

About the AKSW Colloquium

This event is part of a series of events about Semantic Web technology. Please see http://wiki.aksw.org/Colloquium for further information about previous and future events. As always, Bachelor and Master students are able to get points for attendance and there is complimentary coffee and cake after the session.

Kick-off of the FREME project

- 12:50 pm by AmrapaliZaveri - No comments »

Hi all !

A new InfAI project, FREME, kicked off in Berlin. FREME – Open Framework of E-Services for Multilingual and Semantic Enrichment of Digital Content is an H2020 funded project with the objective of building an open, innovative, commercial-grade framework of e-services for multilingual and semantic enrichment of digital content.

InfAI will play an important role in FREME by driving two of the six central FREME services, e-Link and the e-Entity. NIF will be used as a mediator between language services and data sources, serving as foundation for e-Link, while DBpedia Spotlight will be a prototype for e-Entity services, linking named entities in natural language texts to Linked Open Data sets like DBpedia.

InfAI will also help to identify and publish new Linked Data sets that can contribute to data value chains. Our partners in this open content enrichment effort will be DFKI, Tilde, Iminds, Agro-Know, Wripl, VistaTEC and ISBM.

Stay tuned for more info ! In the meanwhile join the conversation on twitter #FREMEH2020.

- Amrapali Zaveri on behalf of the NLP2RDF group

DL-Learner 1.0 (Supervised Structured Machine Learning Framework) Released

February 13, 2015 - 10:38 am by Jens Lehmann - No comments »

Dear all,

we are happy to announce DL-Learner 1.0.

DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. DL-Learner can use various RDF and OWL serialization formats as well as SPARQL endpoints as input, can connect to most popular OWL reasoners and is easily and flexibly configurable. It extends concepts of Inductive Logic Programming and Relational Learning to the Semantic Web in order to allow powerful data analysis.

Website: http://dl-learner.org
GitHub page: https://github.com/AKSW/DL-Learner
Download: https://github.com/AKSW/DL-Learner/releases
ChangeLog: http://dl-learner.org/development/changelog/

DL-Learner is used for data analysis in other tools such as ORE and RDFUnit. Technically, it uses refinement operator based, pattern based and evolutionary techniques for learning on structured data. For a practical example, see http://dl-learner.org/community/carcinogenesis/. It also offers a plugin for Protege, which can give suggestions for axioms to add. DL-Learner is part of the Linked Data Stack – a repository for Linked Data management tools.

We want to thank everyone who helped to create this release, in particular (alphabetically) An Tran, Chris Shellenbarger, Christoph Haase, Daniel Fleischhacker, Didier Cherix, Johanna Völker, Konrad Höffner, Robert Höhndorf, Sebastian Hellmann and Simon Bin. We also acknowledge support by the recently started SAKE project, in which DL-Learner will be applied to event analysis in manufacturing use cases, as well as the GeoKnow and Big Data Europe projects where it is part of the respective platforms.

Kind regards,

Lorenz Bühmann, Jens Lehmann and Patrick Westphal