Wednesday, June 20, 2012

JWS preprint: A Configurable Translation-Based Cross-Lingual Ontology Mapping System to Adjust Mapping Outcome


The following research paper is now on the Journal of Web Semantics preprint server.

Bo Fu, Rob Brennan and Declan O’Sullivan, A Configurable Translation-Based Cross-Lingual Ontology Mapping System to Adjust Mapping Outcome, Journal of Web Semantics, Elsevier, to appear.

Abstract: Ontologies are widely considered as the building blocks of the semantic web, and with them, comes the data interoperability issue. As ontologies are not necessarily always labelled in the same natural language, one way to achieve semantic interoperability is by means of cross-lingual ontology mapping. Translation techniques are often used as an intermediate step to translate the conceptual labels within an ontology. This approach essentially removes the natural language barrier in the mapping environment and enables the application of monolingual ontology mapping tools. This paper shows that the key to this translation-based approach to cross-lingual ontology mapping lies with selecting appropriate ontology label translations in a given mapping context. Appropriateness of the translations in the context of cross-lingual ontology mapping differs from the ontology localisation point of view, as the former aims to generate correct mappings whereas the latter aims to adapt specifications of conceptualisations to target communities. This paper further demonstrates that the mapping outcome using the translation-based cross-lingual ontology mapping approach is conditioned on the translations selected for the intermediate label translation step. In particular, this paper presents the design, implementation and evaluation of a novel cross-lingual ontology mapping system: SOCOM++. SOCOM++ provides configurable properties that can be manipulated by a user in the process of selecting label translations in an effort to adjust the subsequent mapping outcome. It is shown through the evaluation that for the same pair of ontologies, the mappings between them can be adjusted by tuning the translations for the ontology labels. This finding is not yet shown in previous research.

Monday, June 18, 2012

JWS preprint: Georeferencing Flickr Photos Using Language Models at Different Levels of Granularity: an Evidence Based Approach


The following research paper has been added to the Journal of Web Semantics preprint server.

Olivier Van Laere, Steven Schockaert and Barth Dhoedt, Georeferencing Flickr Photos Using Language Models at Different Levels of Granularity: an Evidence Based Approach, Journal of Web Semantics, to appear.

The topic of automatically assigning geographic coordinates to Web 2.0 resources based on their tags has recently gained considerable attention. However, the coordinates that are produced by automated techniques are necessarily variable, since not all resources are described by tags that are sufficiently descriptive. Thus there is a need for adaptive techniques that assign locations to photos at the right level of granularity, or, in some cases, even refrain from making any estimations regarding location at all. To this end, we consider the idea of training language models at different levels of granularity, and combining the evidence provided by these language models using Dempster and Shafer’s theory of evidence. We provide experimental results which clearly confirm that the increased spatial awareness that is thus gained allows us to make better informed decisions, and moreover increases the overall accuracy of the individual language models.

JWS preprint: The SSN Ontology of the W3C Semantic Sensor Network Incubator Group

The following ontology paper is available on the the Journal of Web Semantics preprint server.

Michael Compton, Payam Barnaghi, Luis Bermudez, Raul Garcia-Castro, Oscar Corcho, Simon Cox, John Graybeal, Manfred Hauswirth, Cory Henson, Arthur Herzog, Vincent Huang, Krzysztof Janowicz, W. David Kelsey, Danh Le Phuoc, Laurent Lefort, Myriam Leggieri, Holger Neuhaus, Andriy Nikolov, Kevin Page, Alexandre Passant, Amit Sheth, Kerry Taylor, The SSN Ontology of the W3C Semantic Sensor Network Incubator Group, Journal of Web Semantics, Elsevier, to appear.

The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations — the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects.

Sunday, June 17, 2012

JWS preprint: Community Analysis through Semantic Rules and Role Composition Derivation

The following paper has been added to the Journal of Web Semantics preprint server.

Matthew Rowe, Miriam Fernandez, Sofia Angeletou, Harith Alani, Community Analysis through Semantic Rules and Role Composition Derivation, Journal of Web Semantics, Elsevier, to appear.

Online communities provide a useful environment for web users to communicate and interact with other users by sharing their thoughts, ideas and opinions, and for resolving problems and issues. Companies and organisations now host online communities in order to support their products and services. Given this investment such communities are required to remain healthy and flourish. The behaviour that users exhibit within online communities is associated with their actions and interactions with other community users while the role that a user assumes is the label associated with a given type of behaviour. The domination of one type of behaviour within an online community can impact upon its health, for example, it might be the case within a question-answering community that there is a large portion of expert users and very few users asking questions, thereby reducing the involvement of and the need for experts. Understanding how the role composition - i.e. the distribution of users assuming different roles - of a community affects its health informs community managers with the early indicators of possible reductions or increases in community activity and how the community is expected to change. In this paper we present an approach to analyse communities based on their role compositions. We present a behaviour ontology that captures user behaviour within a given context (i.e. time period and community) and a semantic-rule based methodology to infer the role that a user has within a community based on his/her exhibited behaviour. We describe a method to tune roles for a given community-platform through the use of statistical clustering and discretisation of continuous feature values. We demonstrate the utility of our approach through role composition analyses of the SAP Community Network by: a) gauging the differences between communities, b) predicting community activity increase/decrease, and c) performing regression analysis of the post count within each community. Our findings indicate that communities on the SAP Community Network differ in terms of their average role percentages and experts, while being similar to one another in terms of the dominant role in each community - being a novice user. The findings also indicate that an increase in expert users who ask questions and initiate discussions was associated with increased community activity and that for 23 of the 25 communities analysed we were able to accurately detect a decrease in community activity using the community’s role composition.