Juan Pane

S-match: an open source framework for matching lightweight ontologies

Achieving automatic interoperability among systems with diverse data structures and languages expressing different viewpoints is a goal that has been difficult to accomplish. This paper describes S-Match, an open source semantic matching framework that tackles the semantic interoperability problem by transforming several data structures such as business catalogs, web directories, conceptual models and web services descriptions into lightweight ontologies and establishing semantic correspondences between them. The framework is the first open source semantic matching project that includes three different algorithms tailored for specific domains and provides an extensible API for developing new algorithms, including possibility to plug-in specific background knowledge according to the characteristics of each application domain.

Approximate Structure-Preserving Semantic Matching

Typical ontology matching applications, such as ontology integration, focus on the computation of correspondences holding between the nodes of two graph-like structures, e.g., between concepts in two ontologies. However, there are applications, such as web service integration, where we may need to establish whether full graph structures correspond to one another globally, preserving certain structural properties of the graphs being considered. The goal of this paper is to provide a new matching operation, called structure preserving matching. This operation takes two graph-like structures and produces a set of correspondences between those nodes of the graphs that correspond semantically to one another, (i) still preserving a set of structural properties of the graphs being matched, (ii) only in the case if the graphs are globally similar to one another. We present a novel approximate structure preserving matching approach that implements this operation. It is based on a formal theory of abstraction and on a tree edit distance measure. We have evaluated our solution with encouraging results.

A classification of semantic annotation systems

The Subject-Predicate-Object triple annotation system is now well adopted in the research community, however, it does not always speak to end-users. In fact, explaining all the complexity of semantic annotation systems to laymen can sometime be difficult. We believe that this communication can be simplified by providing a meaningful abstraction of the state of the art in semantic annotation models and thus, in this article, we describe the issue of semantic annotation and review a number of research and end-user tools in the field. Doing so, we provide a clear classification scheme of the features of annotation systems. We then show how this scheme can be used to clarify requirements of end-user use cases and thus simplify the communication between semantic annotation experts and the actual users of this technology.

An evaluation of ontology matching in geo-service applications

Matching between concepts describing the meaning of services representing heterogeneous information sources is a key operation in many application domains, including web service coordination, data integration, peer-to-peer information sharing, query answering, and so on. In this paper we present an evaluation of an ontology matching approach, specifically of structure-preserving semantic matching (SPSM) solution. In particular, we discuss the SPSM approach used to reduce the semantic heterogeneity problem among geo web services and we evaluate the SPSM solution on real world GIS ESRI ArcWeb services. The first experiment included matching of original web service method signatures to synthetically alterated ones. In the second experiment we compared a manual classification of our dataset to the automatic (unsupervised) classification produced by SPSM. The evaluation results demonstrate robustness and good performance of the SPSM approach on a large (ca. 700 000) number of matching tasks.

Semantic disambiguation in folksonomy: a case study

Social annotation systems such as del.icio.us, Flickr and others have gained tremendous popularity among Web 2.0 users. One of the factors of success was the simplicity of the underlying model, which consists of a resource (e.g., a web page), a tag (e.g., a text string), and a user who annotates the resource with the tag. However, due to the syntactic nature of the underlying model, these systems have been criticised for not being able to take into account the explicit semantics implicitly encoded by the users in each tag. In this article we: a) provide a formalisation of an annotation model in which tags are based on concepts instead of being free text strings; b) describe how an existing annotation system can be converted to the proposed model; c) report on the results of such a conversion on the example of a del.icio.us dataset; and d) show how the quality of search can be improved by the semantic in the converted dataset.

Trust and matching algorithms for selecting suitable agents

This article addresses the problem of finding suitable agents to collaborate with for a given interaction in distributed open systems, such as multiagent and P2P systems. The agent in question is given the chance to describe its confidence in its own capabilities. However, since agents may be malicious, misinformed, suffer from miscommunication, and so on, one also needs to calculate how much trusted is that agent. This article proposes a novel trust model that calculates the expectation about an agents future performance in a given context by assessing both the agents willingness and capability through the semantic comparison of the current context in question with the agents performance in past similar experiences. The proposed mechanism for assessing trust may be applied to any real world application where past commitments are recorded and observations are made that assess these commitments, and the model can then calculate ones trust in another with respect to a future commitment by assessing the others past performance.

Sense induction in folksonomies: a review

Folksonomies, often known as tagging systems, such as the ones used on the popular Delicious or Flickr websites, use a very simple Knowledge Organisation System. Users have thus been quick to adopt this system and create extensive annotations on the Web. However, because of the simplicity of the folksonomy model, the semantics of the tags used is not explicit and can only be inferred from their context of use. This is a barrier for the automatic use of such Knowledge Organisation Systems by computers and new techniques have been developed to extract the semantic of the tags. In this article we discuss the drawbacks of some of these approaches and propose a generalization of the different approaches to detect new senses of terms in a folksonomy. Another weak point of the current state of the art in the field is the lack of formal evaluation methodology; we thus propose a novel evaluation framework. We introduce a dataset and evaluation methodology that enable the comparison of results between different approaches to sense induction in folksonomies. Finally we discuss the performances of different approaches to the task of homonymous/polysemous tag detection and synonymous identification.

Toward Open Government in Paraguay

The authors outline Paraguays journey toward open government and the technical and organizational challenges it faces in promoting transparency and providing open data.

Adopting semantic annotation systems for corporate portal management: a Telefonica case study

Corporate portals, such as the one used by the Telefónica group, make an important integral part of the enterprise infrastructure, facilitating the creation, sharing, discovery and consumption of enterprise assets through blogs, news, forums, documents and information in general. However, as the amount of data grows, it becomes much more difficult to access the right asset in the precise moment when it is needed. Annotation systems try to address this problem to a certain extent by allowing the users to collaboratively annotate assets using tags so they can be found more easily by reusing these tags in queries. However, this model often falls short due to mismatches in the vocabularies of different users who use synonymous, polysemous, or more specific (or general) terms in tagging and searching. In this paper we: (a) provide a description of the corporate portal of the Telefónica group; (b) define a semantic annotation model that was developed to address the above-mentioned problems; (c) provide details of the implementation of the annotation model for the Telefónica portal; and (d) report the results of an initial evaluation of a concept-based search enabled by the model.

Supporting semantic annotations in Flickr

In this paper we propose an extension to the tripartite folksonomy model to explicitly encode the semantics of tags. This enables stronger semantic services for the user such as search taking into account synonymy and hypernymy in a knowledge organisation system. However, automatic disambiguation is not yet possible and inputting the semantics of tags manually should not be a chore for the users. We thus propose a set of user interfaces features, illustrated in a working uploader for Flickr, that simplify the semantic annotation of photos before their publication. Finally, we discuss the enabling services for such interfaces, thus providing a complete description of the theoretical and practical issues of semantic annotations on Flickr.