The paper "Towards Concept Identification using a Knowledge-Intensive Approach" presents an approach to identify concepts and their types in micro posts relying on the DBpedia knowledge base and ontology. Our approach consist first in carrying out a preprocessing task where messages are normalised. Then we attempt to identify candidate concepts leveraging part-of-speech tags and Wikipedia article titles. Next we associate the candidate concepts with DBpedia resources and tap into the ontology hierarchy of classes and resource properties to classify the resource in one of the following types: Person, Organization, Location, and Miscellaneous, which covers films, sport events, software, awards and television shows.
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