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.
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。
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.
As hopes are raised that an open data commitment will feature in the G8’s final communiqué, Martin Tisné explains why such an initiative would benefit governments and citizens alike. Read more.
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
Ordnance Survey has released a new beta linked data site. You can read the official press release here. The most obvious change that is hopefully apparent as you navigate round the site is the much improved look and feel of the site. Including maps (!) showing where particular resources are located. Try this and this for example. Maps can be viewed at different levels of zoom. Read more.
Dr. Jeff Pan gave a seminar at iSOCO on 26th April, 2013. His talk is titled: Understanding and Exploiting Semantic Data.
Abstract: The talk will begin with some example to illustrate why and how ontology and linked data technologies can be useful for data integration. I will then present some recent results that are related to the Marie Curie K-Drive project, in particular on understanding and exploiting semantic data, including query generation, ontology authoring and streaming ontological reasoning.
Dr. Jeff Pan gave a seminar at the Department of Artefficial Intelligence at Universidad Politécnica de Madrid (UPM). His talk is title: Approximate Reasoning for OWL: Why? How? And what next?
Abstract: The talk will begin with some example to illustrate why reasoning is needed for linked data and semantic web applications. I will then further explain why approximate reasoning is need and how to perform faithful approximate reasoning, i.e, approximate reasoning with some level of quality control, by making use of tractable sub-languages in OWL 2. I will conclude the talk with discussions on some of our relevant recent work and future steps, including those in the distributed setting.
Some reckon that, currently, every two days, we create as much information as was created from the dawn of civilisation to 2003. Every two days! And it’s growing at 40% per year. We can’t miss out on that kind of growth opportunity. And this is an opportunity. In terms of economic value alone, this is a market worth tens if not hundreds of billions of euros per year. At a time when Europe desperately needs growth, this is exactly where we should be looking to create new jobs and new opportunities. Read more.
There are a growing number of governmental data portals in Europe but currently there is no consensus on how to exchange information about datasets listed on these portals. As a consequence businesses and citizens face difficulties in finding and re-using public sector information, in particular if the datasets are in another Member State where language barriers may apply and the structure of government is unfamiliar.
Therefore the European Commission sets up a working group to define a common metadata model for describing open data sets, based on the existing DCAT specification (i.e. a DCAT application profile). Read more.