This article proposes an informational perspective on comparison consequences in social judgment. It is argued that to understand the variable consequences of comparison, one has to examine what target knowledge is activated during the comparison process. These informational underpinnings are conceptualized in a selective accessibility model that distinguishes 2 fundamental comparison processes...

We present a new shape descriptor for measuring the similarity between shapes and exploit it in graphical object recognition and retrieval. By statistically integrating the local length-ratio and angle constraints between contour points relative to the shape skeleton, we construct the shape descriptor capturing the global spatial distribution of the shape contour. Then, the dissimilarity betwee...

Previous studies have shown that various biomedical subdomains have lexical, syntactic, semantic and discourse structure variations. It is essential to recognise such differences to understand that biomedical natural language processing tools, such as named entity recognisers, that work well on some subdomains may not work as well on others. In this paper, we investigate the pairwise similarity...

Previous studies have shown that various biomedical subdomains have lexical, syntactic, semantic and discourse structure variations. It is essential to recognise such differences to understand that biomedical natural language processing tools, such as named entity recognisers, that work well on some subdomains may not work as well on others. In this paper, we investigate the pairwise similarity...

Evidential clustering is an approach to based on the use of Dempster-Shafer mass functions represent cluster-membership uncertainty. In this paper, we introduce a neural-network evidential algorithm, called NN-EVCLUS, which learns mapping from attribute vectors functions, in such way that more similar inputs are mapped output with lower degree conflict. The neural network can be paired one-clas...

Topic models such as Latent Dirichlet Allocation (LDA) can discover topics from a large collection of documents in an unsupervised fashion and thus is one of the most popular text analysis tool currently in use. However, when using it in practice, the topics discovered by topic model don’t always make sense to end users. The poor quality topics will substantially undermine a topic model system’...

The amount of collected digital information grows with each day. This development is facilitated by advanced technology, allowing for more detailed and more complex measurements. As a result, huge data sets gathered in this way are no longer easily comprehensible for a human person. Dimensionality reduction constitutes an important tool to visualise highly complex data in two dimensions, allowi...