The major challenging issue to determine the relevance and the novelty of sentences is the amount of information used in similarity computation among sentences. An information retrieval (IR) with reference corpus approach is proposed. A sentence is considered as a query to a reference corpus, and similarity is measured in terms of the weighting vectors of document lists ranked by IR systems. Tw...

Interest in One-Class Classification methods has soared in recent years due to its wide applicability in many practical problems where classification in the absence of counterexamples is needed. In this paper, a new one class classification rule based on order statistics is presented. It only relies on the embedding of the classification problem into a metric space, so it is suitable for Euclid...

Although dopamine is one of the most studied neurotransmitter in the brain, its exact function is still unclear. This short review focuses on its role in different levels of cognitive vision: visual processing, visual attention and working memory. Dopamine can influence cognitive vision either through direct modulation of visual cells or through gating of basal ganglia functioning. Even if its ...

Novelty identification is accustomed to distinguishing novel data from an approaching stream of documents. In this study, we proposed a novel methodology for document-level novelty identification by utilizing document-to-sentence-level strategy. This work first splits a document into sentences, decides the novelty of every sentence, then registers the record-level novelty score in view of an al...

A challenge for search systems is to detect not only when an item is relevant to the user’s information need, but also when it contains something new which the user has not seen before. In the TREC novelty track, the task was to highlight sentences containing relevant and new information in a short, topical document stream. This is analogous to highlighting key parts of a document for another p...

Novelty detection, recognising features that differ from those that are normally seen, is a potentially useful ability for a mobile robot. Once a robot can detect those features that are novel the amount of learning that has to be done can be reduced (as only new things need to be learnt), the attention of the robot can be focused onto the new features, and the robot can be used as an inspectio...

Novelty search is a recent and promising approach to evolve neurocontrollers, especially to drive robots. The main idea is to maximize the novelty of behaviors instead of the efficiency. However, abandoning the efficiency objective(s) may be too radical in many contexts. In this paper, a Paretobased multi-objective evolutionary algorithm is employed to reconcile novelty search with objective-ba...

Content-based filtering methods fall short in situations where there are many similar items to recommend from, for instance when recommending articles from multiple news portals. To deal with this problem, we can consider the novelty of recommendations. Detecting novelty is usually implemented as finding the most dissimilar articles. We propose a method that uses topic modelling to find the nov...