Schema matching is the problem of finding relationships among concepts across heterogeneous data sources that are heterogeneous in format and in structure. Starting from the “hidden meaning” associated with schema labels (i.e. class/attribute names) it is possible to discover relationships among the elements of different schemata. Lexical annotation (i.e. annotation w.r.t. a thesaurus/lexical r...

This paper describes two applications of conditional restricted Boltzmann machines (CRBMs) to the task of autotagging music. The first consists of training a CRBM to predict tags that a user would apply to a clip of a song based on tags already applied by other users. By learning the relationships between tags, this model is able to pre-process training data to significantly improve the perform...

Prior empirical studies suggest repeated exchange develops increasing value in buyer-supplier relationships. A first order implication of this finding is that buyers will concentrate exchange among a relatively small number of suppliers to generate maximum value in relationships. However, buyers are equally concerned with value capture. By distributing rather than concentrating exchange, buyers...

Collaborative manufacturer–retailer relationships based on efficient consumer response (ECR) have become ubiquitous over the past decade. Yet academic studies of ECR adoption and its impact on marketing relationships are relatively scarce. Inspired by the relational view of competitive advantage, the authors empirically investigate whether the extent to which suppliers of a major retailer adopt...

In multilabel classification, each instance in the training set is associated with a set of labels, and the task is to output a label set whose size is unknown a priori for each unseen instance. The most commonly used approach for multilabel classification is where a binary classifier is learned independently for each possible class. However, multilabeled data generally exhibit relationships be...

Mass spectrometry (MS)-based large scale phosphoproteomics has facilitated the investigation of plant phosphorylation dynamics on a system-wide scale. However, generating large scale data sets for membrane phosphoproteins usually requires fractionation of samples and extended hands-on laboratory time. To overcome these limitations, we developed "ShortPhos," an efficient and simple phosphoproteo...

Combinatory Categorial Grammar (CCG) is a lexicalized grammar formalism in which words are associated with categories that specify the syntactic configurations in which they may occur. We present a novel parsing model with the capacity to capture the associative adjacent-category relationships intrinsic to CCG by parameterizing the relationships between each constituent label and the pretermina...

Schema matching is the problem of finding relationships among concepts across heterogeneous data sources (heterogeneous in format and in structure). Starting from the “hidden meaning” associated to schema labels (i.e. class/attribute names) it is possible to discover relationships among the elements of different schemata. Lexical annotation (i.e. annotation w.r.t. a thesaurus/lexical resource) ...

Numerous embedding models have been recently explored to incorporate semantic knowledge into visual recognition. Existing methods typically focus on minimizing the distance between the corresponding images and texts in the embedding space but do not explicitly optimize the underlying structure. Our key observation is that modeling the pairwise image-image relationship improves the discriminatio...