Collaborative tagging represents for the Web a potential way for organizing and sharing information and for heightening the capabilities of existing search engines. However, because of the lack of automatic methodologies for generating the tags and supporting the tagging activity, many resources on the Web are deficient in tag information, and recommending opportune tags is both a current open issue and an exciting challenge. This paper approaches the problem by applying a combined set of techniques and tools (that uses tags, domain ontologies, keyphrase extraction methods) thereby generating tags automatically. The proposed approach is implemented in the PIRATES (Personalized Intelligent tag Recommender and Annotator TEStbed) framework, a prototype system for personalized content retrieval, annotation, and classification. A case study application is developed using a domain ontology for software engineering

Accessibility, usability and inclusion represent desirable challenges of current research in the field of universal design: in some cases, these features require adaptive behaviours and specialised customisations, while, in general, it is possible to identify common and shareable guidelines. We focus our attention on children with autism spectrum disorders. Many studies show the positive impact of using computer technologies for supporting the lives of these users. Despite that, just a restricted part of the current websites and apps is accessible and usable for people with ASD. In this paper, we present general and shared guidelines and best practices for accessibility and usability for all; and we propose specialised guidelines for designers and developers of websites and mobile applications for users with ASD. We then present a review of many of the existing websites and applications, in order to check which comply with all, or parts of these guidelines.

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Tag-based systems have become very common for online classification thanks to their intrinsic advantages such as self-organization and rapid evolution. However, they are still affected by some issues that limit their utility, mainly due to the inherent ambiguity in the semantics of tags. Synonyms, homonyms, and polysemous words, while not harmful for the casual user, strongly affect the quality of search results and the performances of tag-based recommendation systems. In this paper we rely on the concept of tag relatedness in order to study small groups of similar tags and detect relationships between them. This approach is grounded on a model that builds upon an edge-colored multigraph of users, tags, and resources. To put our thoughts in practice, we present a modular and extensible framework of analysis for discovering synonyms, homonyms and hierarchical relationships amongst sets of tags. Some initial results of its application to the delicious database are presented, showing that such an approach could be useful to solve some of the well known problems of folksonomies