AI-based novelty detection in crowdsourced idea spaces

Novelty Detection in Projected Spaces for Structural Health Monitoring

The aim of Structural Health Monitoring (SHM) is to detect and identify damages in man-made structures such as bridges by monitoring features derived from vibration data. A usual approach is to deal with vibration measurements, obtained by acceleration sensors during the service life of the structure. In this case, only normal data from healthy operation are available, so damage detection becom...

AI Based Prevention and Detection

Modelling efficient novelty-based search result diversification in metric spaces

a r t i c l e i n f o a b s t r a c t Novelty-based diversification provides a way to tackle ambiguous queries by re-ranking a set of retrieved documents. Current approaches are typically greedy, requiring O (n 2) document–document comparisons in order to diversify a ranking of n documents. In this article, we introduce a new approach for novelty-based search result diversification to reduce th...

Graph-Based Text Representation For Novelty Detection

We discuss several feature sets for novelty detection at the sentence level, using the data and procedure established in task 2 of the TREC 2004 novelty track. In particular, we investigate feature sets derived from graph representations of sentences and sets of sentences. We show that a highly connected graph produced by using sentence-level term distances and pointwise mutual information can ...

Crowdsourced Idea Generation: The Effect of Exposure to an Original Idea

The effect of exposure to an original or common idea on crowdsourced idea generation was studied by asking crowd workers to design a public service advertisement. As compared to having no idea exposure, exposure to an original idea decreased fluency and increased the average originality of ideas generated by each person. By contrast, exposure to a common idea had no effect on either idea origin...