Social tags and linked data for ontology development: a case study in the financial domain

We describe a domain ontology development approach that extracts domain terms from folksonomies and enrich them with data and vocabularies from the Linked Open Data cloud. As a result, we obtain lightweight domain ontologies that combine the emergent knowledge of social tagging systems with formal knowledge from Ontologies. In order to illustrate the feasibility of our approach, we have produced an ontology in the financial domain from tags available in Delicious, using DBpedia, OpenCyc and UMBEL as additional knowledge sources

The Semantic Web Revisited

The original Scientific American article on the Semantic Web appeared in 2001. It described the evolution of a Web that consisted largely of documents for humans to read to one that included data and information for computers to manipulate. The Semantic Web is a Web of actionable information--information derived from data through a semantic theory for interpreting the symbols.This simple idea, however, remains largely unrealized. Shopbots and auction bots abound on the Web, but these are essentially handcrafted for particular tasks; they have little ability to interact with heterogeneous data and information types. Because we haven't yet delivered large-scale, agent-based mediation, some commentators argue that the Semantic Web has failed to deliver. We argue that agents can only flourish when standards are well established and that the Web standards for expressing shared meaning have progressed steadily over the past five years. Furthermore, we see the use of ontologies in the e-science community presaging ultimate success for the Semantic Web--just as the use of HTTP within the CERN particle physics community led to the revolutionary success of the original Web. This article is part of a special issue on the Future of AI

Review of the state of the art: discovering and associating semantics to tags in folksonomies

This paper describes and compares the most relevant approaches for associating tags with semantics in order to make explicit the meaning of those tags. We identify a common set of steps that are usually considered across all these approaches and frame our descriptions according to them, providing a unified view of how each approach tackles the different problems that appear during the semantic association process. Furthermore, we provide some recommendations on (a) how and when to use each of the approaches according to the characteristics of the data source, and (b) how to improve results by leveraging the strengths of the different approaches

Learning Structured Knowledge from Social Tagging Data A critical review of methods and techniques

For more than a decade, researchers have been proposing various methods and techniques to mine social tagging data and to learn structured knowledge. It is essential to conduct a comprehensive survey on the related work, which would benefit the research community by providing better understanding of the state-of-the-art and insights into the future research directions. The paper first defines the spectrum of Knowledge Organization Systems, from unstructured with less semantics to highly structured with richer semantics. It then reviews the related work by classifying the methods and techniques into two main categories, namely, learning term lists and learning relations. The method and techniques originated from natural language processing, data mining, machine learning, social network analysis, and the Semantic Web are discussed in detail under the two categories. We summarize the prominent issues with the current research and highlight future directions on learning constantly evolving knowledge from social media data

On the Complexity of Shared Conceptualizations

In the Social Web, folksonomies and other similar knowledge organization techniques may suffer limitations due to both different users’ tagging behaviours and semantic heterogeneity. In order to estimate how a social tagging network organizes its resources, focusing on sharing (implicit) conceptual schemes, we apply an agent-based reconciliation knowledge system based on Formal Concept Analysis. This article describes various experiments that focus on conceptual structures of the reconciliation process as applied to Delicious bookmarking service. Results will show the prevalence of sharing tagged resources in order to be used by other users as recommendations.Ministerio de Ciencia e Innovación TIN2009-09492Junta de Andalucía TIC-606

ConceptMapWiki - a collaborative framework for agglomerating pedagogical knowledge

We propose a new educational framework,ConceptMapWiki, that is a wiki representing pedagogicalknowledge with a collection of concept maps which iscollaboratively created, edited and browsed. The learners andeducators provide complementing contribution to evolvingshared knowledge structures that are stored in a relationaldatabase forming together inter-connected overlappingontologies. Every contribution is stored supplied with timestamps and a user profile enabling to analyze maturing ofknowledge according to various learner-driven criteria.Pedagogically motivated learning paths can be collaborativelydefined and evaluated, and educational games can beincorporated based on browsing and editing concept maps.The proposed framework is believed to be the first wikiarchitecture of it's kind, designed for personalized learningwith an evolving knowledge repository relying on adaptivevisual representations and sound pedagogical motivation.Initial experiments with a functional online prototype indicatepromising educational gain and suggest further research.Peer reviewe

Callimachus DL: using semantics to enhance search and etrieval in a digital library.

Proceedings of: First World Summit on the Knowledge Society, (WSKS 2008), Athens, Greece, September 24-26, 2008Among the challenges of classifying, locating and accessing knowledge in Digital Libraries tackling with the huge amount of resources the Web provides, improving Digital Libraries by means of different strategies, particularly, using semantics remains a promising and interesting approach. In this paper, we present CallimachusDL, a semantics-based Digital Library which provides faceted search, enhanced access possibilities and a proof-of-concept implementation.Publicad

Linking Folksonomies and Ontologies for Supporting Knowledge Sharing: a State of the Art

Deliverable of ISICIL ANR-funded projectSocial tagging systems have recently become very popular as a means to classify large sets of resources shared among on-line communities over the social Web. However, the folksonomies resulting from the use of these systems revealed limitations: tags are ambiguous and their spelling may vary, and folksonomies are difficult to exploit in order to retrieve or exchange information. This report compares the recent attempts to overcome these limitations and to support the use of folksonomies with formal languages and ontologies from the Semantic Web

Enhancing information retrieval in folksonomies using ontology of place constructed from Gazetteer information

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesFolksonomy (from folk and taxonomy) is an approach to user metadata creation where users describe information objects with a free-form list of keywords (‘tags’). Folksonomy has have proved to be a useful information retrieval tool that support the emergence of “collective intelligence” or “bottom-up” light weight semantics. Since there are no guiding rules or restrictions on the users, folksonomy has some drawbacks and problems as lack of hierarchy, synonym control, and semantic precision. This research aims at enhancing information retrieval in folksonomy, particularly that of location information, by establishing explicit relationships between place name tags. To accomplish this, an automated approach is developed. The approach starts by retrieving tags from Flickr. The tags are then filtered to identify those that represent place names. Next, the gazetteer service that is a knowledge organization system for spatial information is used to query for the place names. The result of the search from the gazetteer and the feature types are used to construct an ontology of place. The ontology of place is formalized from place name concepts, where each place has a “Part-Of” relationship with its direct parent. The ontology is then formalized in OWL (Web Ontology Language). A search tool prototype is developed that extracts a place name and its parent name from the ontology and use them for searching in Flickr. The semantic richness added to Flickr search engine using our approach is tested and the results are evaluated