Thematic Annotation: extracting concepts out of documents
Pierre Andrews, Martin Rajman

TL;DR
This paper introduces a novel thematic annotation method that leverages a large semantic database to extract relevant concepts from documents without relying on keyword extraction, focusing on hierarchical concept relations.
Contribution
The work presents a new concept-based annotation algorithm that uses a semantic hierarchy to represent document content, differing from traditional keyword or statistical methods.
Findings
Effective extraction of relevant concepts not explicitly present in the text
Utilizes a semantic hierarchy to capture document themes
Provides a synthetic, concept-based document representation
Abstract
Contrarily to standard approaches to topic annotation, the technique used in this work does not centrally rely on some sort of -- possibly statistical -- keyword extraction. In fact, the proposed annotation algorithm uses a large scale semantic database -- the EDR Electronic Dictionary -- that provides a concept hierarchy based on hyponym and hypernym relations. This concept hierarchy is used to generate a synthetic representation of the document by aggregating the words present in topically homogeneous document segments into a set of concepts best preserving the document's content. This new extraction technique uses an unexplored approach to topic selection. Instead of using semantic similarity measures based on a semantic resource, the later is processed to extract the part of the conceptual hierarchy relevant to the document content. Then this conceptual hierarchy is searched to…
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling · Semantic Web and Ontologies
