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.

Checking satisfiability of database constraints is a fundamental problem in database design. In addition, database constraints have to be not only satisfiable but also finitely satisfiable. This problem is generally addressed by using theorem provers that, being developed for first order logic formulas, are based on semidecidable procedures. Furthermore, even in simple cases, theorem provers are quite inefficient in dealing with comparison operators such as, for instance, the equality. In this paper, a decidable, sound, and complete method for checking finite satisfiability of a specific class of integrity constraints for object-oriented databases, including the equality constraints, is presented. The method, that is based on a graph-theoretic approach, has exponential complexity in the worst case, rarely occurring in practice.

Inheritance is introducted in object-oriented systems to enhance code reuse and create more compact and readable software. Powerful object models adopt multiple inheritance, allowing a type (or class) definition to inherit from more than one supertype. Unfortunately, in applying this powerful modeling mechanism, inheritance conflicts may be generated, which arise when the same property or operation is defined in more than one supertype. Inheritance conflicts identification and resolution is the key issue of this article. In strongly typed object-oriented systems the resolutioin of inheritance conflicts depends on the compatibility of the types of the conflicting definitions. In case of incompatible types, a contradiction arises. This article focuses on object-oriented databases (ODBs), providing a method aimed at supporting the designer in the construction of correct ODB schemas. The first necessary condition for schema correctness is the absence of contradictions. A second cause of schema incorrectness is due to the presence of structurally recursive types that, when defined within certain hierarchical patterns, cause the nontermination of the inheritance process. In the article, after the formal definition of a correct schema, two graph-theoretic methods aimed at verifying ODB schema correctness are analyzed. Although the first method is intuitive but inefficient, the second allows schema correctness to be checked in polynomial time, in the size of the schema. The results of this study are included in the implementation of Mosaico, an environment for ODB application design.