Data Mining for Browsing Patterns in Weblog Data by Art Neural Networks

Categorising visitors based on their interaction with a website is a key problem in Web content usage. The clickstreams generated by various users often follow distinct patterns, the knowledge of which may help in providing customised content. This paper proposes an approach to clustering weblog data, based on ART2 neural networks. Due to the characteristics of the ART2 neural network model, the proposed approach can be used for unsupervised and self-learning data mining, which makes it adaptable to dynamically changing websites.

Cultural Knowledge for Named Entity Disambiguation: A Graph-Based Semantic Relatedness Approach

One of the ultimate aims of Natural Language Processing is to automate the analysis of the meaning of text. A fundamental step in that direction consists in enabling effective ways to automatically link textual references to their referents, that is, real world objects. The work presented in this paper addresses the problem of attributing a sense to proper names in a given text, i.e., automatically associating words representing Named Entities with their referents. The method for Named Entity Disambiguation proposed here is based on the concept of semantic relatedness, which in this work is obtained via a graph-based model over Wikipedia. We show that, without building the traditional bag of words representation of the text, but instead only considering named entities within the text, the proposed method achieves results competitive with the state-of-the-art on two different datasets.

Towards Wider Sharing of Iconographical Art Content

Information and multimedia technologies that have been developed during the past couple of years provided new e-tools to memory institutions (viz. museum, libraries, galleries, etc.), reviving the valuable treasure made by generation of people. Digital libraries (DLs) are such powerful contemporary tools for cultural heritage presentation, preservation and archiving. However, DLs power will in-crease significantly if they use mechanisms for ubiquitous sharing of their e-artefacts and they distribute attractive content in the social networks, reflecting community demands and needs. This paper presents a service for automatic sharing of iconographical artefacts and full collections from the Bulgarian Iconographical Digital Library to selected Facebook communities. In this case the service will be used for widely promotion of knowledge about East-Christian Iconographical Art and Culture, but I could be used not only for this and not only in this domain.