Dominance measuring methods are a recent approach for dealing with complex decisionmaking problems with imprecise, incomplete or partial information within multi-attribute value/utility theory. These methods compute pairwise dominance values and exploit the information included in the dominance matrix in different ways to derive measures of dominance intensity to rank the alternatives under con...

Schema matching is a crucial step in data integration. Many approaches to schema matching have been proposed so far. Different types of information about schemas, including structures, linguistic features and data types, etc have been used to match attributes between schemas. Relying on a single aspect of information about schemas for schema matching is not sufficient. Approaches have been prop...

Modelling a target attribute by other attributes in the data is perhaps the most traditional data mining task. When there are many attributes in the data, one needs to know which of the attribute(s) are relevant for modelling the target, either as a group or the one feature that is most appropriate to select within the model construction process in progress. There are many approaches for select...

(Multi-)relational regression consists of predicting continuous response of target objects called reference objects by taking into account interactions with other objects called task-relevant objects. In relational databases, reference objects and task-relevant objects are stored in distinct data relations. Interactions between objects are expressed by means of (many-to-one) foreign key constra...

The paper discusses experiments, results, applications and further developments in tagging a highly inflectional language, based on multiple register diversified language models. The texts are accurately disambiguated in terms of a large tagset (611 tags) in two linear-time processing steps (tiered processing). The underlying tagger simultaneously uses multiple register language models and choo...

In the attribute inference problem, we aim to infer users’ private attributes (e.g., locations, sexual orientation, and interests) using their public data in online social networks. State-of-the-art methods leverage a user’s both public friends and public behaviors (e.g., page likes on Facebook, apps that the user reviewed on Google Play) to infer the user’s private attributes. However, these m...

This paper deals with the analysis of performance of source trajectory estimation by using the measurements provided by multiple towed arrays (or platforms). In numerous practical situations, the maneuvering ability of the receiver (e.g. a ship towing linear arrays) is limited leading thus to consider that the observer motion is rectilinear and uniform. Even if this hypothesis appears quite lim...

Attributes can be used to recognize unseen objects from a textual description. Their learning is oftentimes accomplished with a large amount of annotations, e.g. around 160k-180k, but what happens if for a given attribute, we do not have many annotations? The standard approach would be to perform transfer learning, where we use source models trained on other attributes, to learn a separate targ...