Abstract To protect and promote the originality authenticity of mountain foodstuffs, European Union set Regulation No 1151/2012 to create optional quality term “mountain product”. Our research aimed at exploring attractiveness product label for consumers, considering both attitude towards itself purchase intentions. We propose a model investigate relationships between four latent constructs — a...

Music semantic annotation aims to automatically annotate a music signal with a set of semantic labels (words or tags). Existing methods on music semantic annotation usually take it as a multi-label binary classification problem, and model each semantic label individually while ignoring their relationships. However, there are usually strong correlations between some labels. Intuitively, investig...

In multi-label learning, each instance can be related with one or more binary target variables. Multi-label learning problems are commonly found in many applications, e.g. in text classification where a news article is possible to be both on politics and finance. The main motivation of multi-label learning algorithms is the exploitation of label dependencies in order to improve prediction accur...

Currently, structural pattern recognizer evaluations compare graphs of detected structure to target structures (i.e. ground truth) using recognition rates, recall and precision for object segmentation, classification and relationships. In document recognition, these target objects (e.g. symbols) are frequently comprised of multiple primitives (e.g. connected components, or strokes for online ha...

With the recent advances in graph neural networks, there is a rising number of studies on graph-based multi-label classification with consideration object dependencies within visual data. Nevertheless, representations can become indistinguishable due to complex nature label relationships. We propose image framework based transformer networks fully exploit inter-label interactions. The paper pre...

We propose a probabilistic model that captures contextual 4 4 information in the form of typical spatial relationships between regions 5 5 of an image. We represent a region’s local context as a combination of the 6 6 identity of neighbouring regions as well as the geometry of the neighbour7 7 hood. We subsequently cluster all the neighbourhood configurations with 8 8 the same label at the foca...

Need for robust and high performance XML database systems increased due to growing XML data produced by today’s applications. Like indexes in relational databases, XML labeling is the key to XML querying. Assigning unique labels to nodes of a dynamic XML tree in which the labels encode all structural relationships between the nodes is a challenging problem. Early labeling schemes designed for s...

In social advertising, ads are targeted based on underlying social networks and their content is tailored with information that pertains to the social relationship. This paper explores the effectiveness of social advertising using data from field tests of different ads on Facebook. We find evidence that social advertising is effective, and that this efficacy seems to stem mainly from the abilit...

We consider a setting where agents select among competing products of unknown quality by costly sequential search. The agents are active on an online social network, and late movers benefit from possibly being able to see early movers’ purchase decisions. In this setting we consider the impact of advertising by firms, and the incentives of the underlying social network platform. We consider dis...

In recent years, much effort has been put in ontology learning. However, the knowledge acquisition process is typically focused in the taxonomic aspect. The discovery of non-taxonomic relationships is often neglected, even though it is a fundamental point in structuring domain knowledge. This paper presents an automatic and unsupervised methodology that addresses the non-taxonomic learning proc...