Web-Based Knowledge Extraction and the Cognitive Characterization of Cultural Groups

The advent of Web 2.0 has provided new opportunities for cultural analysts to understand more about the cognitive characteristics of cultural groups. In particular, user-contributed content provides important indications as to the beliefs, attitudes and values of cultural groups, and this is an important focus of attention for those concerned with the development of cognitively-relevant models. In order to support the exploitation of the Web in the context of cultural modeling activities, it is important to deal with both the large-scale nature of the Web and the current dominance of natural language formats. In this paper, we outline an approach to support the exploitation of the Web in the context of cultural modeling activities. The approach begins with the development of qualitative cultural models (which describe the beliefs, concepts and values of cultural groups), and these models are subsequently used to develop an ontology-based information extraction capability (which harvests model-relevant information from online textual resources). We are currently developing a system to support the approach, and the continued development of this system should enable cultural analysts to more fully exploit the Web for the purpose of developing more accurate, detailed and predictively-relevant cognitive models

Real‐time interactive social environments: A review of BT's generic learning platform

Online learning in particular and lifelong learning in general require a learning platform that makes sense both pedagogically and commercially. This paper sets out to describe what we mean by generic, learning and platform. The technical requirements are described, and various trials that test the technical, educational and commercial nature of the platform are described Finally, the future developments planned for the Real‐time Interactive Social Environments (RISE) are discusse

Exploring The Value Of Folksonomies For Creating Semantic Metadata

Finding good keywords to describe resources is an on-going problem: typically we select such words manually from a thesaurus of terms, or they are created using automatic keyword extraction techniques. Folksonomies are an increasingly well populated source of unstructured tags describing web resources. This paper explores the value of the folksonomy tags as potential source of keyword metadata by examining the relationship between folksonomies, community produced annotations, and keywords extracted by machines. The experiment has been carried-out in two ways: subjectively, by asking two human indexers to evaluate the quality of the generated keywords from both systems; and automatically, by measuring the percentage of overlap between the folksonomy set and machine generated keywords set. The results of this experiment show that the folksonomy tags agree more closely with the human generated keywords than those automatically generated. The results also showed that the trained indexers preferred the semantics of folksonomy tags compared to keywords extracted automatically. These results can be considered as evidence for the strong relationship of folksonomies to the human indexer’s mindset, demonstrating that folksonomies used in the del.icio.us bookmarking service are a potential source for generating semantic metadata to annotate web resources

Improving Distributed Representations of Tweets - Present and Future

Unsupervised representation learning for tweets is an important research field which helps in solving several business applications such as sentiment analysis, hashtag prediction, paraphrase detection and microblog ranking. A good tweet representation learning model must handle the idiosyncratic nature of tweets which poses several challenges such as short length, informal words, unusual grammar and misspellings. However, there is a lack of prior work which surveys the representation learning models with a focus on tweets. In this work, we organize the models based on its objective function which aids the understanding of the literature. We also provide interesting future directions, which we believe are fruitful in advancing this field by building high-quality tweet representation learning models.Comment: To be presented in Student Research Workshop (SRW) at ACL 201

Improving Distributed Representations of Tweets - Present and Future

Unsupervised representation learning for tweets is an important research field which helps in solving several business applications such as sentiment analysis, hashtag prediction, paraphrase detection and microblog ranking. A good tweet representation learning model must handle the idiosyncratic nature of tweets which poses several challenges such as short length, informal words, unusual grammar and misspellings. However, there is a lack of prior work which surveys the representation learning models with a focus on tweets. In this work, we organize the models based on its objective function which aids the understanding of the literature. We also provide interesting future directions, which we believe are fruitful in advancing this field by building high-quality tweet representation learning models.Comment: To be presented in Student Research Workshop (SRW) at ACL 201

Ensuring the discoverability of digital images for social work education : an online tagging survey to test controlled vocabularies

The digital age has transformed access to all kinds of educational content not only in text-based format but also digital images and other media. As learning technologists and librarians begin to organise these new media into digital collections for educational purposes, older problems associated with cataloguing and classifying non-text media have re-emerged. At the heart of this issue is the problem of describing complex and highly subjective images in a reliable and consistent manner. This paper reports on the findings of research designed to test the suitability of two controlled vocabularies to index and thereby improve the discoverability of images stored in the Learning Exchange, a repository for social work education and research. An online survey asked respondents to "tag", a series of images and responses were mapped against the two controlled vocabularies. Findings showed that a large proportion of user generated tags could be mapped to the controlled vocabulary terms (or their equivalents). The implications of these findings for indexing and discovering content are discussed in the context of a wider review of the literature on "folksonomies" (or user tagging) versus taxonomies and controlled vocabularies

From the invalidity of a General Classification Theory to a new organization of knowledge for the millennium to come

Proceedings der 10. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation. Wien, 3-5 Juli 2006The idea of organizing knowledge and the determinism in classifícation structures implicitly involve certain limits which are translated into a General Theory on the Classifícation of Knowledge, given that classifícation responds to specific parameters and structures more than to a theoretical concept. The classifícation of things is a refiection of their classifícation by man, and this is what determines classifícation structures. The classifícation and organization of knowledge are presented to us as an artificial construct or as a useful fiction elaborated by man. Positivist knowledge reached its peak in the 20* century when science classifications and implemented classifícation systems based on the latter were to be gestated and Consolidated. Pragmatism was to serve as the epistemological and theoretical basis for science and its classifícation. If the classifícation of the sciences has given rise to clastification systems, the organisation and representation of knowledge has to currendy give rise to the context of the globalisation of electronic information in the hypertextual organisational form of electronic information where, if in information the médium ivas the message, in organisation the médium is the structure. The virtual reality of electronic information delves even deeper into it; the process is completed as the subject attempts to look for information. This information market needs standards of an international nature for documents and data. This body of information organization will be characterized by its dynamic nature. If formal and material structures change our concept of knowledge and the way it is structured, then this organization will undergo dynamic change along with the material and formal structures of the real world. The semantic web is a qualitative leap which can be glimpsed on tiie new knowledge horizon; the latter would be shaped with the full integration of contents and data, the language itself would include data and its rules of reason or representation system. The new organisation of knowledge points to a totally nCw conception; post-modern epistemology has yet to be articulated. In the 21 st century, the organization of electronic information is presenting a novel hypertextual, non-linear architecture that will lead to a new change in the paradigm for organization of knowledge for the mülennium to come.Publicad