Collaborative tagging as a knowledge organisation and resource discovery tool

The purpose of the paper is to provide an overview of the collaborative tagging phenomenon and explore some of the reasons for its emergence. Design/methodology/approach - The paper reviews the related literature and discusses some of the problems associated with, and the potential of, collaborative tagging approaches for knowledge organisation and general resource discovery. A definition of controlled vocabularies is proposed and used to assess the efficacy of collaborative tagging. An exposition of the collaborative tagging model is provided and a review of the major contributions to the tagging literature is presented. Findings - There are numerous difficulties with collaborative tagging systems (e.g. low precision, lack of collocation, etc.) that originate from the absence of properties that characterise controlled vocabularies. However, such systems can not be dismissed. Librarians and information professionals have lessons to learn from the interactive and social aspects exemplified by collaborative tagging systems, as well as their success in engaging users with information management. The future co-existence of controlled vocabularies and collaborative tagging is predicted, with each appropriate for use within distinct information contexts: formal and informal. Research limitations/implications - Librarians and information professional researchers should be playing a leading role in research aimed at assessing the efficacy of collaborative tagging in relation to information storage, organisation, and retrieval, and to influence the future development of collaborative tagging systems. Practical implications - The paper indicates clear areas where digital libraries and repositories could innovate in order to better engage users with information. Originality/value - At time of writing there were no literature reviews summarising the main contributions to the collaborative tagging research or debate

Sense Tagging: Semantic Tagging with a Lexicon

Sense tagging, the automatic assignment of the appropriate sense from some lexicon to each of the words in a text, is a specialised instance of the general problem of semantic tagging by category or type. We discuss which recent word sense disambiguation algorithms are appropriate for sense tagging. It is our belief that sense tagging can be carried out effectively by combining several simple, independent, methods and we include the design of such a tagger. A prototype of this system has been implemented, correctly tagging 86% of polysemous word tokens in a small test set, providing evidence that our hypothesis is correct.Comment: 6 pages, uses aclap LaTeX style file. Also in Proceedings of the SIGLEX Workshop "Tagging Text with Lexical Semantics

Short Term Memory May Be the Depletion of the Readily Releasable Pool of Presynaptic Neurotransmitter Vesicles

The Tagging/Retagging model of short term memory was introduced earlier (1) to explain the linear relationship that exists between response time and correct response probability for word recall and recognition: At the initial stimulus presentation words tag the corresponding long term memory locations. The tagging process is linear in time and takes about one second to reach a tagging level of 100%. After stimulus presentation the tagging level decays logarithmically with time to 50% after 14 seconds and to 20% after 220 seconds. If a probe word is reintroduced the tagging level has to go back to 100% for the word to be properly identified, which leads to a delay in response time. This delay is proportional to the tagging loss which is in turn directly related to the decrease in probability of correct word recall and recognition.\ud Evidence suggests that the tagging level is the level of depletion of the Readily Releasable Pool (RRP) of neurotransmitter vesicles at presynaptic terminals. The evidence includes the initial linear relationship between tagging level and time as well as the subsequent logarithmic decay of the tagging level. The activation of a short term memory may thus be the depletion of RRP (exocytosis) and short term memory decay may be the ensuing recycling of the neurotransmitter vesicles (endocytosis).\u

Research Perspectives on Social Tagging

Social tagging has emerged as one of the most popular social software tools available online. Originating from Del.icio.us, social tagging capabilities can now be found on a number of major music, news, video, and commercial websites, as well as on social network sites and enterprise systems. Although social tagging allows individuals to organize content utilizing user-generated vocabulary, the power of social tagging stems from the ability to view and share resources with other users of the system. Through the sharing of tags and resources, social tagging systems facilitate network connections and perhaps even the creation of communities. In this panel, an exciting group of young researchers will present their ongoing work on social tagging. This panel will present a variety of perspectives on social tagging ranging from qualitative ethnographic work to quantitative visualizations. Additionally, the panel will cover topics such as: the definition of a tag, the role that tags play in social network sites, as well as tags in corporate and organizational settings. The research and the varying methods presented in this panel will present viewers with an exciting array of perspectives on social tagging. Additionally, in order to further engage the audience, the panelists will also participate in a point-counterpoint discussion with the participants which will help illuminate both the advantages and disadvantages of social tagging, as well as further highlight the multiple perspectives and approaches available for continuing social tagging research

Semantic Tagging on Historical Maps

Tags assigned by users to shared content can be ambiguous. As a possible solution, we propose semantic tagging as a collaborative process in which a user selects and associates Web resources drawn from a knowledge context. We applied this general technique in the specific context of online historical maps and allowed users to annotate and tag them. To study the effects of semantic tagging on tag production, the types and categories of obtained tags, and user task load, we conducted an in-lab within-subject experiment with 24 participants who annotated and tagged two distinct maps. We found that the semantic tagging implementation does not affect these parameters, while providing tagging relationships to well-defined concept definitions. Compared to label-based tagging, our technique also gathers positive and negative tagging relationships. We believe that our findings carry implications for designers who want to adopt semantic tagging in other contexts and systems on the Web.Comment: 10 page

Semantic Tagging with Deep Residual Networks

We propose a novel semantic tagging task, sem-tagging, tailored for the purpose of multilingual semantic parsing, and present the first tagger using deep residual networks (ResNets). Our tagger uses both word and character representations and includes a novel residual bypass architecture. We evaluate the tagset both intrinsically on the new task of semantic tagging, as well as on Part-of-Speech (POS) tagging. Our system, consisting of a ResNet and an auxiliary loss function predicting our semantic tags, significantly outperforms prior results on English Universal Dependencies POS tagging (95.71% accuracy on UD v1.2 and 95.67% accuracy on UD v1.3).Comment: COLING 2016, camera ready versio

Tagging, Folksonomy & Co - Renaissance of Manual Indexing?

This paper gives an overview of current trends in manual indexing on the Web. Along with a general rise of user generated content there are more and more tagging systems that allow users to annotate digital resources with tags (keywords) and share their annotations with other users. Tagging is frequently seen in contrast to traditional knowledge organization systems or as something completely new. This paper shows that tagging should better be seen as a popular form of manual indexing on the Web. Difference between controlled and free indexing blurs with sufficient feedback mechanisms. A revised typology of tagging systems is presented that includes different user roles and knowledge organization systems with hierarchical relationships and vocabulary control. A detailed bibliography of current research in collaborative tagging is included.Comment: Preprint. 12 pages, 1 figure, 54 reference

A study of topological vertexing for heavy quark tagging

We compare heavy quark tagging and anti-tagging efficiencies for vertex detectors with different inner raddi using the topological vertex technique developed at the SLC/SLD experiment. Charm tagging benefits by going to very small inner radii.Comment: 5 pages 3 figures Latex, Presented at the 5th International Linear Collider Workshop (LCWS2000