Discrete Characterization of Domain Using Semantic Clustering

Domain Adaptable Semantic Clustering in Statistical NLG

We present a hybrid natural language generation system that utilizes Discourse Representation Structures (DRSs) for statistically learning syntactic templates from a given domain of discourse in sentence “micro” planning. In particular, given a training corpus of target texts, we extract semantic predicates and domain general tags from each sentence and then organize the sentences using supervi...

Word clustering effect on vocabulary learning of EFL learners: A case of semantic versus phonological clustering

The aim of this study is to determine the effect of word clustering method on vocabulary learning of Iranian EFL learners through a case of semantic versus phonological clustering. To this effect, 80 homogeneous students from four intermediate classes at an English institute in Torbat e Heydariyeh participated in this research. They were assigned to four groups according to semantic versus phon...

Semantic-Based Image Retrial in the VQ Compressed Domain using Image Annotation Statistical Models

Text Clustering using Semantic Terms

In traditional text clustering, documents appear terms frequency without considering the semantic information of each document (i.e., vector model). The property of vector model may be incorrectly classified documents into different clusters when documents of same cluster lack the shared terms. Recently, to overcome this problem uses knowledge based approaches. However, these approaches have an...

Clustering of Web Search Results Using Semantic

Clustering is related to data mining for information retrieval. Relevant information is retrieved quickly while doing the clustering of documents. It organizes the documents into groups; each group contains the documents of similar type content. Different clustering algorithms are used for clustering the documents such as partitioned clustering (K-means Clustering) and Hierarchical Clustering (...