AKSW Publishes Survey on Challenges of Question Answering in the Semantic Web

Semantic Web Journal Logo
We are happy to announce that our Survey on Challenges of Question Answering in the Semantic Web (Konrad  Höffner, Sebastian Walter, Edgard Marx, Ricardo Usbeck, Jens Lehmann and Axel Ngonga) has been accepted.

Abstract

Semantic Question Answering (SQA) removes two major access requirements to the Semantic Web: the mastery of a formal query language like SPARQL and knowledge of a specific vocabulary. Because of the complexity of natural language, SQA presents difficult challenges and many research opportunities. Instead of a shared effort, however, many essential components are redeveloped, which is an inefficient use of researcher’s time and resources. This survey analyzes 62 different SQA systems, which are systematically and manually selected using predefined inclusion and exclusion criteria, leading to 72 selected publications out of 1960 candidates. We  identify common challenges, structure solutions, and provide recommendations for future systems. This work is based on publications from the end of 2010 to July 2015 and is also compared to older but similar surveys.

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AKSW Colloquium, 30.05.2016, PARIS: Probabilistic Alignment of Relations, Instances, and Schema

Mohamed Sherif

In the incoming colloquium, Mohamed Ahmed Sherif will present the paper “PARIS: Probabilistic Alignment of Relations, Instances, and Schema” from Suchanek et al., published in the proceedings of VLDB 2012 [PDF].

Abstract

One of the main challenges that the Semantic Web faces is the integration of a growing number of independently designed ontologies. In this work, we present PARIS, an approach for the automatic alignment of ontologies. PARIS aligns not only instances, but also relations and classes. Alignments at the instance level cross-fertilize with alignments at the schema level. Thereby, our system provides a truly holistic solution to the problem of ontology alignment. The heart of the approach is probabilistic, i.e., we measure degrees of matchings based on probability estimates. This allows PARIS to run without any parameter tuning. We demonstrate the efficiency of the algorithm and its precision through extensive experiments. In particular, we obtain a precision of around 90% in experiments with some of the world’s largest ontologies.

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.

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AKSW Colloquium, 23.05.2016, Instance Matching and RDF Dataset Similarity

In the incoming colloquium, Mofeed Hassan will present the paper “Semi-supervised Instance Matching Using Boosted Classifiers” from Kejriwal et al., published in the proceedings of ESWC 2015 [PDF].

Abstract

Instance matching concerns identifying pairs of instances that refer to the same underlying entity. Current state-of-the-art instance matchers use machine learning methods. Supervised learning systems achieve good performance by training on significant amounts of manually labeled samples. To alleviate the labeling effort, this paper presents a minimally supervised instance matching approach that is able to deliver competitive performance using only 2% training data and little parameter tuning. As a first step, the classifier is trained in an ensemble setting using boosting. Iterative semi-supervised learning is used to improve the performance of the boosted classifier even further, by re-training it on the most confident samples labeled in the current iteration. Empirical evaluations on a suite of six publicly available benchmarks show that the proposed system outcompetes optimization-based minimally supervised approaches in 1-7 iterations. The system’s average F-Measure is shown to be within 2.5% of that of recent supervised systems that require more training samples for effective performance.

After that, Michael Röder will present his paper “Detecting Similar Linked Datasets Using Topic Modelling” that has been accepted by the upcoming ESWC 2016 [PDF].

Abstract

The Web of data is growing continuously with respect to both the size and number of the datasets published. Porting a dataset to five-star Linked Data however requires the publisher of this dataset to link it with the already available linked datasets. Given the size and growth of the Linked Data Cloud, the current mostly manual approach used for detecting relevant datasets for linking is obsolete. We study the use of topic modelling for dataset search experimentally and present TAPIOCA, a linked dataset search engine that provides data publishers with similar existing datasets automatically. Our search engine uses a novel approach for determining the topical similarity of datasets. This approach relies on probabilistic topic modelling to determine related datasets by relying solely on the metadata of datasets. We evaluate our approach on a manually created gold standard and with a user study. Our evaluation shows that our algorithm outperforms a set of comparable baseline algorithms including standard search engines significantly by 6% F1-score. Moreover, we show that it can be used on a large real world dataset with a comparable performance.

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.

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AKSW Colloquium, 09.05.2016: Hebrew MMoOn inventory, federated SPARQL query processing

In this week’s colloquium Bettina Klimek will give a practice talk of the paper ‘Creating Linked Data Morphological Language Resources with MMoOn – The Hebrew Morpheme Inventory‘, which she will present at the LREC conference 2016, 23-28 May 2016, Slovenia, Portorož.

Abstract

The development of standard models for describing general lexical resources has led to the emergence of numerous lexical datasets of various languages in the Semantic Web. However, there are no models that describe the domain of morphology in a similar manner. As a result, there are hardly any language resources of morphemic data available in RDF to date. This paper presents the creation of the Hebrew Morpheme Inventory from a manually compiled tabular dataset comprising around 52.000 entries. It is an ongoing effort of representing the lexemes, word-forms and morphologigal patterns together with their underlying relations based on the newly created Multilingual Morpheme Ontology (MMoOn). It will be shown how segmented Hebrew language data can be granularly described in a Linked Data format, thus, serving as an exemplary case for creating morpheme inventories of any inflectional language with MMoOn. The resulting dataset is described a) according to the structure of the underlying data format, b) with respect to the Hebrew language characteristic of building word-forms directly from roots, c) by exemplifying how inflectional information is realized and d) with regard to its enrichment with external links to sense resources.

As a second talk, Muhammad Saleem will present his thesis titled “Efficient Source Selection For SPARQL Endpoint Federation” . This thesis addresses two key areas of federated SPARQL query processing: (1) efficient source selection, and (2) comprehensive SPARQL benchmarks to test and ranked federated SPARQL engines as well as triple stores.

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. The colloquium will take place in room P701.

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AKSW Colloquium, 25.04.2016, DISPONTE, Workbench for Big Data Dev

In this colloquium, Frank Nietzsche will present his master thesis titled “Game Theory- distributed solving”

Game theory analyzes the behavior of individuals in complex situations. One popular game in Europe and North America with such a complex situation is Skat. For the analysis of the game, the counterfactual regret minimization algorithm (CFR algorithm) was applied. Unfortunately, there is no guarantee that the algorithm works in three-person games. In general, it is difficult to solve three-person games. In addition, the algorithm calculates only a epsilon-Nash equilibrium. But for Skat, the Perfect Bayesian equilibrium would be a better solution. In fact, the Perfect Bayesian equilibrium is a subset of the Nash equilibrium. This raises the question of whether a Perfect Bayesian equilibrium can be calculated using the CFR algorithm. The analysis of this problem will be the last part of the presentation.

The second talk of the colloquium,  Dr. Michael Martin will  announce the student thesis on the AKSW website.

 

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.

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AKSW Colloquium, 18.04.2016, DISPONTE, Workbench for Big Data Dev

In this week’s Colloquium, today 18th of April at 3 PM, Patrick Westphal will present the paper ‘Probabilistic Description Logics under the Distribution Semantics‘ by Riguzzi et. al.

Abstract

Representing uncertain information is crucial for modeling real world domains. In this paper we present a technique for the integration of probabilistic information in Description Logics (DLs) that is based on the distribution semantics for probabilistic logic programs. In the resulting approach, that we called DISPONTE, the axioms of a probabilistic knowledge base (KB) can be annotated with a real number between 0 and 1. A probabilistic knowledge base then defines a probability distribution over regular KBs called worlds and the probability of a given query can be obtained from the joint distribution of the worlds and the query by marginalization. We present the algorithm BUNDLE for computing the probability of queries from DISPONTE KBs. The algorithm exploits an underlying DL reasoner, such as Pellet, that is able to return explanations for queries. The explanations are encoded in a Binary Decision Diagram from which the probability of the query is computed. The experimentation of BUNDLE shows that it can handle probabilistic KBs of realistic size.

The second talk of the colloquium will be Spark/HDFS Big Data Workbench, which enables developers to easily setup HDFS/Spark cluster and run Spark jobs over it (presented by Ivan Ermilov).

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AKSW Colloquium, 11.04.2016, METEOR with DBnary

Depiction of Diego MoussallemIn this week’s Colloquium, today 11th of April at 3 PM, Diego Moussallem will present the paper by Zied Elloumi et al. titled “METEOR for Multiple Target Languages using DBnary.” [PDF].

Abstract

This paper proposes an extension of METEOR, a well-known MT evaluation metric, for multiple target languages using an in-house lexical resource called DBnary (an extraction from Wiktionary provided to the community as a Multilingual Lexical Linked Open Data). Today, the use of the synonymy module of METEOR is only exploited when English is the target language (use of WordNet). A synonymy module using DBnary would allow its use for the 21 languages (covered up to now) as target languages. The code of this new instance of METEOR, adapted to several target languages, is provided to the community. We also show that our DBnary augmented METEOR increases the correlation with human judgements on the WMT 2013 and 2014 metrics dataset for English-to-(French, Russian, German, Spanish) language pairs.

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AKSW Colloquium, 04.04.2016, AMIE + Structured Feedback

Depiction of Lorenz BühmannIn this week’s Colloquium, today 4th of April at 3 PM, Lorenz Bühmann will present the paper by Galárraga et al. titled “AMIE: Association Rule Mining under Incomplete Evidence in Ontological Knowledge Bases.” [PDF].

Abstract

Recent advances in information extraction have led to huge knowledge bases (KBs), which capture knowledge in a machine-readable format. Inductive Logic Programming (ILP) can be used to mine logical rules from the KB. These rules can help deduce and add missing knowledge to the KB. While ILP is a mature field, mining logical rules from KBs is different in two aspects: First, current rule mining systems are easily overwhelmed by the amount of data (state-of-the art systems cannot even run on today’s KBs). Second, ILP usually requires counterexamples. KBs, however, implement the open world assumption (OWA), meaning that absent data cannot be used as counterexamples. In this paper, we develop a rule mining model that is explicitly tailored to support the OWA scenario. It is inspired by association rule mining and introduces a novel measure for confidence. Our extensive experiments show that our approach outperforms state-of-the-art approaches in terms of precision and coverage. Furthermore, our system, AMIE, mines rules orders of magnitude faster than state-of-the-art approaches.

Depiction of Natanael Arndt Subsequently Natanael Arndt will practice the presentation of his paper “Structured Feedback: A Distributed Protocol for Feedback and Patches on the Web of Data” (Natanael Arndt, Kurt Junghanns, Roy Meissner, Philipp Frischmuth, Norman Radtke, Marvin Frommhold and Michael Martin) [PDF] which is accepted for presentation at the WWW2016 workshop: Linked Data on the Web (LDOW2016) in Montréal.

Abstract

The World Wide Web is an infrastructure to publish and retrieve information through web resources. It evolved from a static Web 1.0 to a multimodal and interactive communication and information space which is used to collaboratively contribute and discuss web resources, which is better known as Web 2.0. The evolution into a Semantic Web (Web 3.0) proceeds. One of its remarkable advantages is the decentralized and interlinked data composition. Hence, in contrast to its data distribution, workflows and technologies for decentralized collaborative contribution are missing. In this paper we propose the Structured Feedback protocol as an interactive addition to the Web of Data. It offers support for users to contribute to the evolution of web resources, by providing structured data artifacts as patches for web resources, as well as simple plain text comments. Based on this approach it enables crowd-supported quality assessment and web data cleansing processes in an ad-hoc fashion most web users are familiar with.

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.

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International Semantic Web Community meets in Leipzig, Sept. 12-15, 2016

logo-semantics-16-blogpost

At the annual SEMANTiCS Conference, experts from academia and industry meet to discuss semantic computing, its benefits and future business implications. Since 2005, SEMANTiCS has been attracting the opinion leaders in semantic web and big data technology, ranging from information managers and software engineers, to commerce experts and business developers as well as researchers and IT architects, when it comes to defining the future of information technology.

The SEMANTiCS 2016 takes place from September 12th to 15th at the second oldest university of Germany – the Leipzig University. Leipzig University hosts several departments in particular AKSW focused on Linked Data and Semantic Web and is therefore THE European hotspot, when it comes to graph-based technologies and knowledge engineering.

You want to be a part of the SEMANTiCS Conference and are interested to get in touch with the following audiences?

  • IT professionals & IT architects
  • Software developers
  • Knowledge Management Executives
  • Innovation Executives
  • R&D Executives

Calls are open now. Industrial presentation offer a platform to reach a huge network of practicioners and users to get feedback and academic submission are published in the well-known ACM-ICPS series (deadline 21st April, 23% acceptance rate). To submit your contribution, please visit the section calls on our website. To attend the workshops, the tutorials or to enjoy the talks in one of the offered sessions, please visit our registration site.

You want to partner with SEMANTiCS 2016? Then get a sponsor package or become an exhibitor! For more details, please click here.

We are looking forward to meeting you! Come and join us in Leipzig!

To be up-to-date, stay tuned and follow us on facebook, twitter (@SemanticsConf) or visit our website for the latest news.

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AKSW takes part in BMWi-funded GEISER project

GEISER

The AKSW group is the technical lead of the recently started GEISER (from sensor data towards internet-based geospatial services) project funded by the Federal Ministry for Economic Affairs and Energy (BMWi) under grant agreement number 01MD16014E. The GEISER project will run from March 1st, 2016 to February 28th, 2019.

Many applications of cyberphysical systems rely on an integration of geospatial data and sensor data. In the engineering industry, dynamic mission planning of service technicians and locating suppliers can benefit from such integrated data. Other potential applications include intelligent parking and refueling by finding available parking spots and fuel pumps or charging spots nearby. Sensors of satellite navigation systems in cars and intelligent fuel pumps, connected charging points and industrial machinery generate terabytes of industry-relevant data every day. Combining many data sources is the most promising approach, but this is difficult. Relevant geospatial data is distributed among structured (e.g., sensors), semi-structured (e.g., OpenStreetMap) and unstructured (e.g., Twitter) data sources. Due to the significant volume and variety of data sources, innovative solutions are required for the acquisition of geospatial data, integrating them with sensor data and building intelligent services on top.

The GEISER project aims to design and implement innovative functionality for developing services for transforming, storing, integrating and processing geospatial and sensor data.Here, machine learning approaches will be applied for tasks such as computing topological relations between resources and time-efficient generation of link specifications. The resulting tools will be integrated as microservices in an open cloud-based platform. The AKSW group of Universität Leipzig particularly works on the extraction and integration of geospatial data. We will develop and evaluate scalable methods for analysing, extracting and fusing RDF from various data sources.

Our partners in this project are USU Software AG (Coordinator), Yellow Map, metaphacts GmbH, Frauenhofer IAIS and TomTom.

The project kick-off meeting will take place March, 14th in Karlsruhe at the office of USU Software AG, so stay tuned for futher project updates and follow us on aksw-blog for the latest news.

The project is funded by:

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