Miguel Rodríguez

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Current approaches to Information Extraction (IE) are capable of extracting large amounts of facts with associated probabilities. Because no current IE system is perfect, complementary and conflicting facts are obtained when different systems are run over the same data. Knowledge Fusion (KF) is the problem of ag-gregating facts from different extractors.(More)
The interest in integrating web-scale knowledge bases (KBs) has intensified in the last several years. Research has focused on knowledge base completion between two KBs with complementary information, lacking any notion of uncertainty or method of handling conflicting information. We present SigmaKB, a knowledge base system that utilizes Consensus(More)
The join query optimization problem has been widely addressed in relational database management systems (RDBMS). The problem consists of finding a join order that minimizes the time required to execute a query. Many strategies have been implemented to solve this problem including deterministic algorithms, randomized algorithms, meta-heuristic algorithms and(More)
The aim of this paper is to show an introduction to the calculation of belief revision that expresses knowledge by a 2CNF. This procedure basically consists of adding a new belief expressed by a clause 2CNF, into the set of beliefs of a knowledge database, preserving its consistency. This generally implies having to remove some clauses from previous(More)