Sentence examples for semantic representations from inspiring English sources

In this study, we present a framework that infers human activities from observations using semantic representations.

Google's "word2vec" tool is another technique for automated extraction of semantic representations from Big Data.

After interests enrichment step comes the semantic representations of these interests and user's profile and context.

We present a model in which there is competition to activate distributed semantic representations.

Our method combines a bottom-up data driven approach with top-down feedback provided by high level semantic representations.

For example, matching data at different levels of abstraction often requires reasoning that explains the difference between two semantic representations.

As an example of this, Google's Word2vec provides an automated means of extracting semantic representations from big data.

Many articles on image labeling have focused on the use of high-level semantic representations and contextual information.

The success of this approach therefore depends critically on the integrity of the semantic representations of the items being trained.

These results are discussed as consistent with the idea that antipsychotics reduce abnormal activations of particular semantic representations.

We propose a method that allows robots to obtain and determine a higher-level understanding of a demonstrator's behavior via semantic representations.