Today, a large amount of uncertain data is produced by several applications where the management systems of traditional databases incuding indexing methods are not suitable to handle such type of data. In this paper, we propose an inverted based index method for effciently searching uncertain categorical data over distributed environments. We adress two kinds of query over the distributed uncertain databases, one a distributed probabilis-tic thresholds query, where all results sastisfying the query with probablities that meet a probablistic threshold requirement are returned, and another a distributed top k-queries, where all results optimizing the transfer of the tuples and the time treatment are returned.
Atlantis Press The 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology https://hal.archives-ouvertes.fr/hal-01224226 The 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology , Jun 2015, Gijon Spain. Atlantis Press, 2015, <http://www.atlantis-press.com/php/pub.php?publication=ifsa-eusflat-15>. <10.2991/ifsa-eusflat-15.2015.197 > http://www.atlantis-press.com/php/pub.php?publication=ifsa-eusflat-15ARRAY(0x7f5470024bb0) 2015-06-30