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New Paper Published at IJCAI 2013

A new paper funded by K-Drive – “Predicting Knowledge in An Ontology Stream” is published at this year’s International Joint Conference on Artificial Intelligence. Abstract. Recently, ontology stream reasoning has been introduced as a multidisciplinary approach, merging synergies from Artificial Intelligence, Database, World-Wide-Web to reason on semantic augmented data streams. Although knowledge evolution and real-time reasoning have been largely addressed in ontology streams, the challenge of predicting its future (or missing) knowledge remains open and yet unexplored. We tackle predictive reasoning as a correlation and interpretation of past semantics-augmented data over exogenous ontology streams. Consistent predictions are constructed as Description Logics entailments by selecting and applying relevant cross-streams association rules. The experiments have shown accurate prediction with real and live stream data from Dublin City in Ireland.

New Paper Published at ACL 2013

A new paper partially funded by K-Drive – “Transfer Learning Based Cross-lingual Knowledge Extraction for Wikipedia” is published at this year’s Annual Meeting of the Association for Computational Linguistics (ACL 2013).

Abstract. Wikipedia infoboxes are a valuable source of structured knowledge for global knowledge sharing. However, infobox information is very incomplete and imbalanced among the Wikipedias in different languages. It is a promising but challenging problem to utilize the rich structured knowledge from a source language Wikipedia to help complete the missing infoboxes for a target language. In this paper, we formulate the problem of cross-lingual knowledge extraction from multilingual Wikipedia sources, and present a novel framework, called WikiCiKE, to solve this problem. An instance-based transfer learning method is utilized to overcome the problems of topic drift and translation errors. Our experimental results demonstrate that WikiCiKE outperforms the monolingual knowledge extraction method and the translation-based method。

New Paper Published at K-CAP2013

A new paper funded by K-Drive – “Query Generation for Semantic Datasets” is published at this year’s International Conference on Knowledge Capture.

Abstract. Due to the increasing volume of and interconnections between semantic datasets, it becomes a challenging task for novice users to know what are included in a dataset, how they can make use of them, and particularly, what queries should be asked. In this paper we analyse several types of candidate insightful queries and propose a framework to generate such queries and identify their relations. To verify our approach, we implemented our framework and evaluated its performance with benchmark and real world datasets.

New Paper Published at AAMAS2013

A new paper partially funded by K-Drive – “Reasoning about Uncertain Information and Conflict Resolution through Trust Revision” is published at this year’s International Conference on Autonomous Agent and Multiagent Systems.

Abstract. In information driven MAS, information consumers collect information about their environment from various sources such as sensors. However, there is no guarantee that a source will provide the requested information truthfully and correctly. Even if information is provided only by trustworthy sources, it can contain conflicts that hamper its usability. In this paper, we propose to exploit such conflicts to revise trust in information. This requires a reasoning mechanism that can accommodate domain constraints, uncertainty, and trust. Our formalism — SDL-Lite — is an extension of a tractable subset of Description Logics with Dempster-Shafer theory of evidence. SDL-Lite allows reasoning about uncertain informa tion and enables conflict detection. Then, we propose methods for conflict resolution through trust revision and analyse them through simulations. We show that the proposed methods allow reasonably accurate estimations of trust in information in realistic settings

New Paper Published and Presented on ISWC 2012

A new paper partially funded by K-Drive – “RDFS Reasoning on Massively Parallel Hardware” is published and presented on this year’s International Semantic Web Conference.

Abstract. Recent developments in hardware have shown an increase in parallelism as opposed to clock rates. In order to fully exploit these new avenues of performance improvement, computationally expensive workloads have to be expressed in a way that allows for fine-grained parallelism. In this paper, we address the problem of describing RDFS entailment in such a way. Different from previous work on parallel RDFS reasoning, we assume a shared memory architecture. We analyze the problem of duplicates that naturally occur in RDFS reasoning and develop strategies towards its mitigation, exploiting all levels of our architecture. We implement and evaluate our approach on two real-world datasets and study its performance characteristics on different levels of parallelization. We conclude that RDFS entailment lends itself well to parallelization but can benefit even more from careful optimizations that take into account intricacies of modern parallel hardware.

You can view a draft of this paper on our Publications page.

New Paper Published and Presented on AAAI 2012

A new paper partially funded by K-Drive – “Querying Linked Ontological Data through Distributed Summarization” is published and presented on this year’s AAAI conference.

Abstract. As the semantic web expands, ontological data becomes distributed over a large network of data sources on the Web. Consequently, evaluating queries that aim to tap into this distributed semantic database necessitates the ability to consult multiple data sources eciently. In this paper, we propose methods and heuristics to efficiently query distributed ontological data based on a series of properties of summarized data. In our approach, each source summarizes its data as another RDF graph, and relevant section of these summaries are merged and analyzed at query evaluation time. We show how the analysis of these summaries enables more efficient source selection, query pruning and transformation of expensive distributed joins into local joins

You can view a draft of this paper on our Publications page.

New Paper Published and Presented on DL 2012

A new paper partially funded by K-Drive – Optimising Parallel ABox Reasoning of EL Ontologies is published and presented on the 25th International Workshop on Description Logics.

Abstract. The success of modern multi-core processors makes it possible to develop parallel ABox reasoning algorithms to facilitate efficient reasoning on large scale ontological data sets. In this paper, we extend a parallel TBox reasoning algorithm for ELHR+ to a parallel ABox reasoning algorithm for ELHbotR+, which also supports the bottom concept so as to model disjointness and inconsistency. In design of algorithms, we exploit the characteristic of ABox reasoning in ELHbotR+ to improve parallelisation and reduce unnecessary resource cost. Particularly, we separate the TBox reasoning, ABox reasoning on types and ABox reasoning on relations. Our evaluation shows that a naive implementation of our approach can compute all ABox entailments of a Not-Galen ontology with about 1 million individuals and 9 million axioms in about 3 minutes.

You can view a draft of this paper on our Publications page.

New Paper Published in IEEE CIM

A new paper partially funded by K-Drive  – Exploiting Tractable Fuzzy and Crisp Reasoning in Ontology Applications is published in IEEE Computational Intelligence Magazine.

Abstract. The Semantic Web movement has led to the publication of thousands of ontologies online. These ontologies present and mediate information and knowledge on the Semantic Web. How to provide tractable reasoning services for fuzzy and crisp ontologies has been a pressing research problem over the last five years. In this paper, we present a reusable semantic infrastructure that comprises a tractable reasoning system TrOWL, an ontological search engine ONTOSEARCH2 and a folksonomy extension component Taggr. We show that such an infrastructure can be used to support different ontology applications with tractable reasoning services by making use of tractable profiles in OWL 2 and some of their fuzzy extension.

You can view a draft of this paper on our Publications page.