Enrichment and ranking of the YouTube tag space and integration with the Linked Data cloud

The increase of personal digital cameras with video functionality and video-enabled camera phones has increased the amount of user-generated videos on the Web. People are spending more and more time viewing online videos as a major source of entertainment and “infotainment”. Social websites allow users to assign shared free-form tags to user-generated multimedia resources, thus generating annotations for objects with a minimum amount of effort. Tagging allows communities to organise their multimedia items into browseable sets, but these tags may be poorly chosen and related tags may be omitted. Current techniques to retrieve, integrate and present this media to users are deficient and could do with improvement. In this paper, we describe a framework for semantic enrichment, ranking and integration of web video tags using Semantic Web technologies. Semantic enrichment of folksonomies can bridge the gap between the uncontrolled and flat structures typically found in user-generated content and structures provided by the Semantic Web. The enhancement of tag spaces with semantics has been accomplished through two major tasks: a tag space expansion and ranking step; and through concept matching and integration with the Linked Data cloud. We have explored social, temporal and spatial contexts to enrich and extend the existing tag space. The resulting semantic tag space is modelled via a local graph based on co-occurrence distances for ranking. A ranked tag list is mapped and integrated with the Linked Data cloud through the DBpedia resource repository. Multi-dimensional context filtering for tag expansion means that tag ranking is much easier and it provides less ambiguous tag to concept matching

Challenges in Bridging Social Semantics and Formal Semantics on the Web

This paper describes several results of Wimmics, a research lab which names stands for: web-instrumented man-machine interactions, communities, and semantics. The approaches introduced here rely on graph-oriented knowledge representation, reasoning and operationalization to model and support actors, actions and interactions in web-based epistemic communities. The re-search results are applied to support and foster interactions in online communities and manage their resources

Semantic contextualisation of social tag-based profiles and item recommendations

Proceedigns of 12th International Conference, EC-Web 2011, Toulouse, France, August 30 - September 1, 2011.The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-23014-1_9We present an approach that efficiently identifies the semantic meanings and contexts of social tags within a particular folksonomy, and exploits them to build contextualised tag-based user and item profiles. We apply our approach to a dataset obtained from Delicious social bookmarking system, and evaluate it through two experiments: a user study consisting of manual judgements of tag disambiguation and contextualisation cases, and an offline study measuring the performance of several tag-powered item recommendation algorithms by using contextualised profiles. The results obtained show that our approach is able to accurately determine the actual semantic meanings and contexts of tag annotations, and allow item recommenders to achieve better precision and recall on their predictions.This work was supported by the Spanish Ministry of Science and Innovation (TIN2008-06566-C04-02), and the Community of Madrid (CCG10- UAM/TIC-5877

Improving folksonomies using formal knowledge: a case study on search

Search in folksonomies is impeded by lack of machine understandable descriptions for the meaning of tags and their relations. One approach to addressing this problem is the use of formal knowledge resources (KS) to assign meaning to the tags, most notably WordNet and (online) ontologies. However, there is no insight of how the different characteristics of such KS can contribute to improving search in folksonomies. In this work we compare the two KS in the context of folksonomy search, first by evaluating the enriched structures and then by performing a user study on searching the folksonomy content through these structures. We also compare them to cluster-based folksonomy search. We show that the diversity of ontologies leads to more satisfactory results compared to WordNet although the latter provides richer structures. We also conclude that the idiosyncrasies of folksonomies can not be addressed by only using formal KS

An investigation of the oral status and reported oral care of children with heart and heart-lung transplants

AIM: To investigate the oral health status and oral microflora of children who have received heart and heart-lung transplants. Parental knowledge and current practice of oral health procedures by the child were also investigated. SAMPLE AND METHOD: Thirty-five children attending the Cardio-Thoracic Transplant Unit, Great Ormond Street Hospital for Children were included. Measurements were compared with children matched by age and gender attending the trauma clinic at the Department of Paediatric Dentistry, Eastman Dental Hospital. Teeth were examined for the presence or absence of caries or enamel defects. Plaque deposition, gingivitis, gingival bleeding and gingival enlargement were measured and a swab was taken to look at the oral microbial flora. A questionnaire was used to assess parental knowledge of dental health procedures and the current practice of these. RESULTS: There were no significant differences between transplant and control children in caries experience, plaque or gingivitis. Children with heart or heart-lung transplants had significantly greater numbers of enamel defects and more gingival enlargement than control children, children in the heart transplant group had significantly more gingival bleeding. There was little difference in the dental knowledge and reported behaviour of the transplant group compared to the control group. CONCLUSION: The dental needs of heart and heart-lung transplant patients treated at the Great Ormond Street Hospital for Children were similar to those of the control group in this study, however further improvement could be made in educating parents and children on the importance of caries prevention and good oral hygiene.King Saud Universit

Investigating the Semantic Gap through Query Log Analysis

Abstract. Significant efforts have focused in the past years on bringing large amounts of metadata online and the success of these efforts can be seen by the impressive number of web sites exposing data in RDFa or RDF/XML. However, little is known about the extent to which this data fits the needs of ordinary web users with everyday information needs. In this paper we study what we perceive as the semantic gap between the supply of data on the Semantic Web and the needs of web users as expressed in the queries submitted to a major Web search engine. We perform our analysis on both the level of instances and ontologies. First, we first look at how much data is actually relevant to Web queries and what kind of data is it. Second, we provide a generic method to extract the attributes that Web users are searching for regarding particular classes of entities. This method allows to contrast class definitions found in Semantic Web vocabularies with the attributes of objects that users are interested in. Our findings are crucial to measuring the potential of semantic search, but also speak to the state of the Semantic Web in general.

How tagging pragmatics influence tag sense discovery in social annotation systems

Abstract. The presence of emergent semantics in social annotation systems has been reported in numerous studies. Two important problems in this context are the induction of semantic relations among tags and the discovery of different senses of a given tag. While a number of approaches for discovering tag senses exist, little is known about which factors influence the discovery process. In this paper, we analyze the influence of user pragmatic factors. We divide taggers into different pragmatic distinctions. Based on these distinctions, we identify subsets of users whose annotations allow for a more precise and complete discovery of tag senses. Our results provide evidence for a link between tagging pragmatics and semantics and provide another argument for including pragmatic factors in semantic extraction methods. Our work is relevant for improving search, retrieval and browsing in social annotation systems, as well as for optimizing ontology learning algorithms based on tagging data.

A step foreword historical data governance in information systems

From major companies and organizations to smaller ones around the world, databases are now one of the leading technologies for supporting most of organizational information assets. Their evolution allows us to store almost anything often without determining if it is in fact relevant to be saved or not. Hence, it is predictable that most information systems sooner or later will face some data management problems and consequently the performance problems that are unavoidably linked to. In this paper we tackle the data management problem with a proposal for a solution using machine-learning techniques, trying to understand in an intelligent manner the data in a database, according to its relevance for their users. Thus, identifying what is really important to who uses the system and being able to distinguish it from the rest of the data is a great way for creating new and efficient measures for managing data in an information system.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013