A Maximum Entropy Approach for Semantic Language Modeling

Latent Maximum Entropy Approach for Semantic N-gram Language Modeling

Semantic structured language models

In this study, we propose two novel semantic language modeling techniques for spoken dialog systems. These methods are called semantic concept based language modeling and semantic structured language modeling. In the concept based language modeling, we propose to use long span semantic units to model meaning sequences in spoken utterances. In the latter technique, we use statistical semantic pa...

An Executive Approach Based On the Production of Fuzzy Ontology Using the Semantic Web Rule Language Method (SWRL)

Today, the need to deal with ambiguous information in semantic web languages is increasing. Ontology is an important part of the W3C standards for the semantic web, used to define a conceptual standard vocabulary for the exchange of data between systems, the provision of reusable databases, and the facilitation of collaboration across multiple systems. However, classical ontology is not enough ...

Semantic n-gram language modeling with the latent maximum entropy principle

Latent Maximum Entropy Principle for Statistical Language Modeling

In this paper, w dcscrihe a unified probabilistic framework for statistical lmiguage modeling, latent mmmum mtmpy Wnciple. The salient feature of this approach is that the hidden causal hierarchical dependency structure can be enc d e d into thpsiatwtical model in a principled way hy mixturts of expoocntial families with a rirh expressive power. We first show tlie problem lormulatiun, whition, ...