Contextualized Question Answering

Luka Bradeško, Lorand Dali, Blaž Fortuna, Marko Grobelnik, Dunja Mladenić, Inna Novalija, Boštjan Pajntar


The paper describes a system which enables accurate and easy-to-use contextualized question answering and itprovides document overview functionalities. The possibility of asking natural language questions enables a friendly interaction for the user.The contextualization is achieved by using an ontology. The answers are provided based on a domain specific document collection of choice. The approach consists of several phases as follows: data preparation, data enhancement, data indexing and handling questions. Every module uses state of the art technologies that are shown to work in a complex pipeline to make available question answering on top of a given document repository with the context of ontologies, such as, Cyc, ASFA and WordNet. The functioning of the proposed approach is demonstrated on English document collections on Aquatic Sciences and Fisheries - ASFA, using Cyc ontology, ASFA thesaurus as domain specific ontology and WordNet as general ontology. Experimental evaluation has shown that the usage of ontologies increases the number of answers retrieved by about 60%. However the number of answers that are actually correct increases by only 40% when using ontologies.


contextualized information retrieval, question answering, ontology

Full Text:



Creative Commons License
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

Crossref Similarity Check logo

Crossref logologo_doaj