Semantics, sensors, and the social web: The live social semantics experiments

The Live Social Semantics is an innovative application that encourages and guides social networking between researchers at conferences and similar events. The application integrates data and technologies from the Semantic Web, online social networks, and a face-to-face contact sensing platform. It helps researchers to find like-minded and influential researchers, to identify and meet people in their community of practice, and to capture and later retrace their real-world networking activities at conferences. The application was successfully deployed at two international conferences, attracting more than 300 users in total. This paper describes this application, and discusses and evaluates the results of its two deployment

Live Social Semantics

Social interactions are one of the key factors to the success of conferences and similar community gatherings. This paper describes a novel application that integrates data from the semantic web, online social networks, and a real-world contact sensing platform. This application was successfully deployed at ESWC09, and actively used by 139 people. Personal profiles of the participants were automatically generated using several Web~2.0 systems and semantic academic data sources, and integrated in real-time with face-to-face contact networks derived from wearable sensors. Integration of all these heterogeneous data layers made it possible to offer various services to conference attendees to enhance their social experience such as visualisation of contact data, and a site to explore and connect with other participants. This paper describes the architecture of the application, the services we provided, and the results we achieved in this deployment

Semantic modelling of user interests based on cross-folksonomy analysis

The continued increase in Web usage, in particular participation in folksonomies, reveals a trend towards a more dynamic and interactive Web where individuals can organise and share resources. Tagging has emerged as the de-facto standard for the organisation of such resources, providing a versatile and reactive knowledge management mechanism that users find easy to use and understand. It is common nowadays for users to have multiple profiles in various folksonomies, thus distributing their tagging activities. In this paper, we present a method for the automatic consolidation of user profiles across two popular social networking sites, and subsequent semantic modelling of their interests utilising Wikipedia as a multi-domain model. We evaluate how much can be learned from such sites, and in which domains the knowledge acquired is focussed. Results show that far richer interest profiles can be generated for users when multiple tag-clouds are combine

Interlinking English and Chinese RDF data sets using machine translation

lesnikova2014aInternational audienceData interlinking is a difficult task particularly in a multilingual environment like the Web. In this paper, we evaluate the suitability of a Machine Translation approach to interlink RDF resources described in English and Chinese languages. We represent resources as text documents, and a similarity between documents is taken for similarity between resources. Documents are represented as vectors using two weighting schemes, then cosine similarity is computed. The experiment demonstrates that TF*IDF with a minimum amount of preprocessing steps can bring high results

Linked data and libraries

U radu je dan prikaz koncepta povezanih podataka (linked data) kao semantičke nadogradnje postojeće mreže te razmotrena mogućnost integracije knjižničnih kataloga i usluga pomoću spomenutog koncepta u globalnu inteligentno povezanu mrežu – semantički web. Na početku rada govori se općenito o semantičkom webu i osnovnim načelima na kojima počiva. U dijelu rada koji razmatra koncept povezanih podataka, obrađene su njegove glavne sastavnice – URI (Uniform Resource Identifiers) i RDF (Resource Description Framework) – načela, koraci za objavu povezanih podataka na mreži te licenciranje i neka sigurnosna pitanja u vezi istih. U posebnom dijelu rada objašnjena je prednost pretraživanja povezanih podataka u odnosu na klasično pretraživanje mreže kao i problem primjene koncepta povezanih podataka na knjižničnim zapisima. Analiziraju se svojstva MARC zapisa u mrežnom okruženju te razlika između povezanih podataka i tradicionalnih kataloga. Pokazano je da je knjižnični zapis u MARC formatu samo čitljiv dok bi isti takav zapis u RDF/XML obliku, integriran u povezane podatke, bio ne samo čitljiv, nego i stroju “razumljiv” u semantičkom smislu. Na kraju rada zaključeno je kako je tehnologija povezanih podataka velika prigoda za razvoj knjižničnih kataloga i usluga koje bi svoju ulogu u globalnoj inteligentno povezanoj mreži – semantički webu – ispunjavale na mnogo učinkovitiji način.The paper brings a review of the linked data concept as a semantic upgrade of the existing World Wide Web. It also analyzes the possibility of integrating library catalog and services into the intelligently linked network – semantic web. The first part of the paper presents some basic principles of the semantic web in general. Then we discuss the main elements of the linked data (URI - Uniform Resource Identifiers and RDF - Resource Description Framework), its principal concepts, publishing procedure, licensing and some security issues. The next section explains the main advantage of linked data searching in comparison with the conventional web search. Furthermore, we discuss the application of linked data on library catalogue records. MARC properties are analyzed in a network environment as well as the difference between catalogue with linked data and traditional library catalogue. The analysis has shown that MARC record is only readable, while the same record in RDF/XML format integrated into linked data is also understandable in the semantic sense. The conclusion is that the linked data technology presents a great opportunity for further development of library catalogues and library services, but also a was to improve efficiency in the intelligently linked global network

Publishing Chinese medicine knowledge as Linked Data on the Web

<p>Abstract</p> <p>Background</p> <p>Chinese medicine (CM) draws growing attention from Western healthcare practitioners and patients. However, the integration of CM knowledge and Western medicine (WM) has been hindered by a barrier of languages and cultures as well as a lack of scientific evidence for CM's efficacy and safety. In addition, most of CM knowledge published with relational database technology makes the integration of databases even more challenging.</p> <p>Methods</p> <p>Linked Data approach was used in publishing CM knowledge. This approach was applied to publishing a CM linked dataset, namely RDF-TCM <url>http://www.open-biomed.org.uk/rdf-tcm/</url> based on TCMGeneDIT, which provided association information about CM in English.</p> <p>Results</p> <p>The Linked Data approach made CM knowledge accessible through standards-compliant interfaces to facilitate the bridging of CM and WM. The open and programmatically-accessible RDF-TCM facilitated the creation of new data mash-up and novel federated query applications.</p> <p>Conclusion</p> <p>Publishing CM knowledge in Linked Data provides a point of departure for integration of CM databases.</p

Interlinking English and Chinese RDF data sets using machine translation

lesnikova2014aInternational audienceData interlinking is a difficult task particularly in a multilingual environment like the Web. In this paper, we evaluate the suitability of a Machine Translation approach to interlink RDF resources described in English and Chinese languages. We represent resources as text documents, and a similarity between documents is taken for similarity between resources. Documents are represented as vectors using two weighting schemes, then cosine similarity is computed. The experiment demonstrates that TF*IDF with a minimum amount of preprocessing steps can bring high results

User geospatial context for music recommendation in microblogs

Music information retrieval and music recommendation are seeing a paradigm shift towards methods that incorporate user context aspects. However, structured experiments on a standardized music dataset to investigate the effects of do-ing so are scarce. In this paper, we compare performance of various combinations of collaborative filtering and geospatial as well as cultural user models for the task of music recom-mendation. To this end, we propose a geospatial model that uses GPS coordinates and a cultural model that uses seman-tic locations (continent, country, and state of the user). We conduct experiments on a novel standardized music collec-tion, the “Million Musical Tweets Dataset ” of listing events extracted from microblogs. Overall, we find that modeling listeners ’ location via Gaussian mixture models and comput-ing similarities from these outperforms both cultural user models and collaborative filtering. Categories and Subject Descriptors Information systems [Information retrieval]: Music rec-ommendation; Human-centered computing [Collaborative and social computing]: Social medi

A Survey of the First 20 Years of Research on Semantic Web and Linked Data

International audienceThis paper is a survey of the research topics in the field of Semantic Web, Linked Data and Web of Data. This study looks at the contributions of this research community over its first twenty years of existence. Compiling several bibliographical sources and bibliometric indicators , we identify the main research trends and we reference some of their major publications to provide an overview of that initial period. We conclude with some perspectives for the future research challenges.Cet article est une étude des sujets de recherche dans le domaine du Web sémantique, des données liées et du Web des données. Cette étude se penche sur les contributions de cette communauté de recherche au cours de ses vingt premières années d'existence. En compilant plusieurs sources bibliographiques et indicateurs bibliométriques, nous identifions les principales tendances de la recherche et nous référençons certaines de leurs publications majeures pour donner un aperçu de cette période initiale. Nous concluons avec une discussion sur les tendances et perspectives de recherche