Characterising emergent semantics in Twitter lists

Twitter lists organise Twitter users into multiple, often overlapping, sets. We believe that these lists capture some form of emergent semantics, which may be useful to characterise. In this paper we describe an approach for such characterisation, which consists of deriving semantic relations between lists and users by analyzing the cooccurrence of keywords in list names. We use the vector space model and Latent Dirichlet Allocation to obtain similar keywords according to co-occurrence patterns. These results are then compared to similarity measures relying on WordNet and to existing Linked Data sets. Results show that co-occurrence of keywords based on members of the lists produce more synonyms and more correlated results to that of WordNet similarity measures.

Descubrimiento de mappings en recursos geoespaciales

La integración de fuentes de información heterogéneas ha sido un problema abordado en diferentes tipos de fuentes a lo largo de las décadas de diferentes maneras. Una de ellas es el establecimiento de unas relaciones semánticas que permitan poder unir la información de las fuentes relacionadas. A estos enlaces, claves en la integración, se les ha llamado generalmente mappings. Los mappings se han usado en multitud de trabajos y se han abordado, de manera más práctica que teórica en muchos casos, diferentes soluciones para su descubrimiento, su almacenaje, su explotación, etc. Sin embargo, aunque han sido muchas las contribuciones sobre mappings, no hay una definición generalizada y admitida por la comunidad que cubra todos los aspectos vinculados a los mappings. Además, en su proceso de descubrimiento, no existe un marco teórico que defina metódicamente los procesos a seguir y sus características. Igualmente, la actual forma de evaluar el descubrimiento de mappings no es suficiente para toda la casuística existente. En este trabajo se aporta una definición de mapping génerica que engloba todos los sistemas actuales, la especificación detallada del proceso de descubrimiento y el análisis y la propuesta de un proceso de evaluación del descubrimiento. La validez de estos aportes se comprueba con la formulación de hipótesis y su comprobación mediante un estudio cuantitativo sobre un caso de uso con recursos geoespaciales heterogéneos. ABSTRACT The integration of heterogeneous information resources has been an issue addressed in different types of sources over the decades in different ways. One of them is the establishment of semantic relations which allow information from different related resources to be linked. These links, crucial pieces of this integration, are usually known as mappings. These mappings have been widely used in many applications, and different solutions for their discovery, storing, explotation, etc. have been presented, following rather a more practical than theoretical way in many cases. However, although mappings have been widely applied by many researchers, there is a lack of a generally accepted definition that can cover all the aspects related to mappings. Moreover, in the process of mapping discovery, there is not a theoretical framework that defines methodically the processes to be followed and their characteristics. Similarly, the current way of assessing or evaluating the discovery of mappings is insufficient for all the existing use cases. The main contributions of this work are threefold. On the one hand, it presents a general definition of "mapping" which covers all current systems. On the other hand, it describes a detailed specification of the discovery process, and, finally, it faces the analysis and the purpose of the evaluation of this discovery process. The validity of these contributions has been checked with the formulation of hypothesis which have been verified by using heterogeneous geospatial resources in a quantitative study.

Enabling folksonomies for knowledge extraction: A semantic grounding approach

Folksonomies emerge as the result of the free tagging activity of a large number of users over a variety of resources. They can be considered as valuable sources from which it is possible to obtain emerging vocabularies that can be leveraged in knowledge extraction tasks. However, when it comes to understanding the meaning of tags in folksonomies, several problems mainly related to the appearance of synonymous and ambiguous tags arise, specifically in the context of multilinguality. The authors aim to turn folksonomies into knowledge structures where tag meanings are identified, and relations between them are asserted. For such purpose, they use DBpedia as a general knowledge base from which they leverage its multilingual capabilities.