Abstract In this paper, we address the problem of answering complex questions formulated by users in natural language. Since traditional information retrieval systems are not suitable for complex questions, these questions are usually run over knowledge bases, such as Wikidata or DBpedia. We propose a semi-automatic approach for transforming a natural language question into a SPARQL query that can be easily processed over a knowledge base. The approach applies classification techniques to associate a natural language question with a proper query template from a set of predefined templates. The nature of our approach is semi-automatic as the query templates are manually written by human assessors, who are the experts of the knowledge bases, whereas the classification and query processing steps are completely automatic. Our experiments on the large-scale CSQA dataset for question-answering corroborate the effectiveness of our approach.

Semantic similarity search is one of the most promising methods for improving the performance of retrieval systems. This paper presents a new probabilistic method for ontology weighting based on a Bayesian approach. In particular, this work addresses the semantic search method SemSim for evaluating the similarity among a user request and semantically annotated sources. Each resource is annotated with a vector of features (annotation vector), i.e., a set of concepts defined in a reference ontology. Analogously, a user request is represented by a collection of desired features. The paper shows, on the bases of a comparative study, that the adoption of the Bayesian weighting method improves the performance of the SemSim method.

Ontologies are emerging as a key solution to allow different applications to exchange information in a cooperative business environment. From the technology point of view, the growth of the Internet and the Web has favoured the exchange of information and documents among people, but unfortunately the same is not true when information is exchanged among software applications. To tackle the latter problem, ontology-based approaches are among the most promising ones. This is one of the reasons of the momentum that ontologies, and consequently ontology management systems (OMSs), are witnessing. An OMS represents a powerful tool to create common and shareable knowledge repositories concerning a given application domain. The goal of this work is to present SymOntoX, a Web-based OMS conceived for the ebusiness domain. It is an open source software system supporting collaborative and distributed ontology authoring activities.