Where are the Concepts in the Folksonomy Model?

2009

2008

There is a growing interest on how we represent and share tagging data for the purpose of collaborative tagging systems. Conventional tags are not naturally suited for collaborative processes. Being free-text keywords, they are exposed to linguistic variations like case (upper vs lower), grammatical number (singular vs. plural) as well as human typing errors. Additionally, tags depend on the personal views of the world by individual users, and are not normalized for synonymy, morphology or any other mapping. The bottom line of the problem is that tags have no semantics whatsoever. Moreover, even if a user gives some semantics to a tag while using or viewing it, this meaning is not automatically shared with computers since it's not defined in a machine-readable way. With tagging systems increasing in popularity each day, the evolution of this technology is hindered by this problem, since tagging metadata is not readily generated and shared. In this paper we discuss approaches to represent collaborative tagging activities at a semantic level, and present conceptual models for collaborative tagging activities and folksonomies. We present criteria for the comparison of existing tag ontologies and discuss their strengths and weaknesses in relation to these criteria.

Journal of Web Semantics, 2004

The Semantic Web realization depends on the availability of a critical mass of metadata for the web content, associated with the respective formal knowledge about the world. We claim that the Semantic Web, at its current stage of development, is in a state of a critically need of metadata generation and usage schemata that are specific, well-defined and easy to understand. This paper introduces our vision for a holistic architecture for semantic annotation, indexing, and retrieval of documents with regard to extensive semantic repositories. A system (called KIM), implementing this concept, is presented in brief and it is used for the purposes of evaluation and demonstration. A particular schema for semantic annotation with respect to real-world entities is proposed. The underlying philosophy is that a practical semantic annotation is impossible without some particular knowledge modelling commitments. Our understanding is that a system for such semantic annotation should be based upon a simple model of real-world entity classes, complemented with extensive instance knowledge. To ensure the efficiency, ease of sharing, and reusability of the metadata, we introduce an upper-level ontology (of about 250 classes and 100 properties), which starts with some basic philosophical distinctions and then goes down to the most common entity types (people, companies, cities, etc.). Thus it encodes many of the domain-independent commonsense concepts and allows straightforward domainspecific extensions. On the basis of the ontology, a large-scale knowledge base of entity descriptions is bootstrapped, and further extended and maintained. Currently, the knowledge bases usually scales between 10 5 and 10 6 descriptions. Finally, this paper presents a semantically enhanced information extraction system, which provides automatic semantic annotation with references to classes in the ontology and to instances. The system has been running over a continuously growing document collection (currently about 0.5 million news articles), so it has been under constant testing and evaluation for some time now. On the basis of these semantic annotations, we perform semantic based indexing and retrieval where users can mix traditional IR (information retrieval) queries and ontology-based ones. We argue that such large-scale, fully automatic methods are essential for the transformation of the current largely textual web into a semantic web.

2008

The Documentalist Support System (DocSS) is developed to suite novel needs of documentalists working within the Dutch archive for Sound and Vision, broadcasters working outside of Sound and Vision and people interested in the Cultural Heritage value of the archive, who want to perform search in context. The documentalists (and to some extent the other users mentioned) need an environment in which they can view and manipulate multiple types of information (documents and metadata), receive annotation suggestions from their controlled vocabularies, create catalogue descriptions and browse for semantically similar documents within their collection. The open architecture, the publicly published annotation format and the SKOS representation requirement for the controlled vocabularies make the generated annotations interoperable with other annotation databases and the DocSS usable for any documentalist annotating material with controlled vocabularies, for which a digital textual representation of the data exists. 4 http://www.nwo.nl/CATCH/CHOICE 5 http://www.nwo.nl/

Proceedings of IADIS International Conference WWW/Internet, 2009

Tagging systems are very popular tools for organizing and structuring information about arbitrary Web resources by assigning simple keywords (tags) to those resources in a collaborative fashion. Folksonomy is a data structure resulting from the tagging process and is characterized as a flat collection of triples of the form user-resource-tag. Research on folksonomies is only taking off and as of now a number of open research questions and problems require to be answered. One of such problems is the problem of ...

The Indexer, 2015

2006

Abstract This paper presents the Open Annotation and Tagging System (OATS) which draws on previous work in social navigation support, web annotations systems, collaborative tagging and educational metadata. The OATS system augments the text highlighting metaphor by providing a “collaborative tagging” and annotation interface which enables social navigation support. These tools aim to help learners in learning managements systems to better organize and navigate content.

Www, 2007

By analysing the current structure and the usage patterns of collaborative tagging systems, we can find out many important aspects which still need to be improved. Problems related to synonymy, polysemy, different lexical forms, mispelling errors or alternate spellings, different levels of precision and different kinds of tag-to-resource association cause inconsistencies and reduce the efficiency of content search and the effectiveness of the tag space structuring and organization. They are mainly caused by the lack of semantic information inclusion in the tagging process. We propose a new way to describe resources: the semantic tagging. It allows user to state semantic assertions: each of them expresses a defined characteristic of a resource associating it with a concept. We present SemKey, a semantic collaborative tagging system, describing its global architecture and functioning along with the most relevant organizational issues faced. We explore the adequacy of the support offered by the entries of Wikipedia and WordNet in order to access to and reference concepts.

2010

Many of the features of Web 2.0 encourage users to actively interact with each other. Social tagging systems represent one of the good examples that reflect this trend on the Web. The primary purpose of social tagging systems is to facilitate shared access to resources. Our focus in this paper is on the attempts to overcome some of the limitations in social tagging systems such as the flat structure of folksonomies and the absence of semantics in terms of information retrieval. We propose and develop an integrated approach, social tagging systems with directory facility, which can overcome the limitations of both traditional taxonomies and folksonomies. Our preliminary experiments indicate that this approach is promising and that the context provided by the directory facility improves the precision of information retrieval. As well, our synonym detection algorithm is capable of finding synonyms in social tagging systems without any external inputs.

2008

Nowadays the Web represents a growing collection of an enormous amount of contents where the need for better ways to find and organize the available data is becoming a fundamental issue, in order to deal with information overload. Keyword based Web searches are actually the preferred mean to seek for contents related to a specific topic. Search engines and collaborative tagging systems make possible the search for information thanks to the association of descriptive keywords to Web resources. All of them show problems of inconsistency and consequent reduction of recall and precision of searches, due to polysemy, synonymy and in general all the dierent lexical forms that can be used to refer to a particular meaning. A possible way to face or at least reduce these problems is represented by the introduction of semantics to characterize the contents of Web resources: each resource is described by one or more concepts instead of simple and often ambiguous keywords. To support these task...