The importance of hypertext has been steadily growing over the last decade. Internet and other information systems use hypertext format, with data organized associatively rather than sequentially or relationally. A myriad of textual problems have been considered in the pattern matching field with many non-trivial results. Nevertheless, surprisingly little work has been done on the natural combination of pattern matching and hypertext. In contrast to regular text, hypertext has a non-linear structure and the techniques of pattern matching for text cannot be directly applied to hypertext. Manber and Wu [14] pioneered the study of pattern matching in hypertext and defined a hypertext model for pattern matching. Akutsu [2] developed an algorithm that can be used for exact pattern matching in a tree-structured hypertext. Park and Kim [16] considered regular pattern matching in hypertext. They developed a complex algorithm that works for hypertext with an underlying structure of a...

Nowadays we enter the Web 2.0 era where people’s participation is a key principle. In this context, collective annotations enable to share and discuss readers ’ feedback with regard to digital documents. The results of this activity are going to be used in the Information Retrieval context, which already tends to harness similar collective contributions. In this paper, we propose a collective annotation model supporting feedback exchange through discussion threads. Considering this model, we associate annotations with a measure of the sparked consensus degree (social validation), this allows to provide a synthesized view of associated discussions. Finally, we investigate how Information Retrieval systems may benefit from the proposed model, thus taking advantage of human-contributed highly value-added information, namely collective annotations.