Learning to Generate Semantic Annotation for Domain Specific Sentences

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

Domain Specific Automatic Question Generation from Text

The goal of my doctoral thesis is to automatically generate interrogative sentences from descriptive sentences of Turkish biology text. We employ syntactic and semantic approaches to parse descriptive sentences. Syntactic and semantic approaches utilize syntactic (constituent or dependency) parsing and semantic role labeling systems respectively. After parsing step, question statements whose an...

Ontology Learning and Semantic Annotation: a Necessary Symbiosis

Semantic annotation of text requires the dynamic merging of linguistically structured information and a “world model”, usually represented as a domain-specific ontology. On the other hand, the process of engineering a domain ontology through semi-automatic ontology learning system requires the availability of a considerable amount of semantically annotated documents. Facing this bootstrapping p...

Learning to Generate CGs from Domain Specific Sentences

Automatically generating Conceptual Graphs (CGs) [1] from natural language sentences is a difficult task in using CG as a semantic (knowledge) representation language for natural language information source. However, up to now only few approaches have been proposed for this task and most of them either are highly dependent on one domain or use many manually constructed generation rules. In this...

Semantic Annotation of Resources of Distance Learning Based Intelligent Agents

This paper presents a system based on intelligent agents for the semantic annotation of learning resources taking into account the context of training. Semantic annotations systems rarely treat existing semantic annotations in the field of distance education (e-learning). Most researchers in the field of education limit annotations to specific cases (teacher annotation, learner annotation, anno...