Matches in SemOpenAlex for { <https://semopenalex.org/work/W390176713> ?p ?o ?g. }
Showing items 1 to 84 of
84
with 100 items per page.
- W390176713 abstract "Uncertain information is common in many database applications due to intensive data dissemination arising from different pervasive computing sources, such as the high volume data obtained from sensor networks and mobile communications. In this thesis, we propose how to process and manage uncertain information in vague databases. Our work mainly focuses on four aspects: modelling uncertain information by vague sets, maintaining consistency in vague databases, extending SQL to query vague relations and mining vague association rules. Modelling uncertain information by vague sets is the gravity of our work. We discuss how to measure vagueness in practice and the relationships between vague memberships and nulls. A new similarity measure of vague sets and the concepts of median membership (m) and imprecision membership (i) are proposed. Based on these two memberships, we define the notions of mi-overlap, mi-union and mi-intersection between vague sets and the concepts of vague relations and vague databases. Functional dependencies (FDs) and inclusion dependencies (INDs) are the most fundamental integrity constraints that arise in practice in relational databases. We utilize FDs and INDs to maintain the consistency of a vague database. First, we tackle the problem, given a vague relation r and a set of FDs F, of how to obtain the best approximation of r with respect to F when taking into account the median membership and the imprecision membership thresholds. Using these two thresholds of a vague set, we define a merge operation on r. Second, we consider, given a vague database d and a set of INDs N, how to obtain the minimal possible change in value-precision for d. Finally, we develop a vague chase procedure as a means to maintain consistency of d with respect to F and N.Incorporating the notion of vague sets in relations, we propose vague SQL (VSQL), which is an extension of SQL for the vague relational model, and show that VSQL combines the capabilities of a standard SQL with the power of manipulating vague relations. VSQL allows users to formulate a wide range of queries on vague data. Using vague sets, we address the limitations of traditional association rule (AR) mining, which only discovers the hidden relationship among the items that have been sold but ignores the items that are almost sold. For example, in many online shopping applications, such as Amazon and eBay, those items that have been browsed in detail or put into the basket but are not checked out (almost sold items) carry hesitation information, since customers are hesitating to buy them. We propose a new notion of vague association rules (VARs) and devise an efficient algorithm to mine the VARs." @default.
- W390176713 created "2016-06-24" @default.
- W390176713 creator A5067034635 @default.
- W390176713 creator A5081754547 @default.
- W390176713 date "2014-12-23" @default.
- W390176713 modified "2023-09-23" @default.
- W390176713 title "Processing and management of uncertain information in vague databases" @default.
- W390176713 doi "https://doi.org/10.14711/thesis-b1070799" @default.
- W390176713 hasPublicationYear "2014" @default.
- W390176713 type Work @default.
- W390176713 sameAs 390176713 @default.
- W390176713 citedByCount "0" @default.
- W390176713 crossrefType "dissertation" @default.
- W390176713 hasAuthorship W390176713A5067034635 @default.
- W390176713 hasAuthorship W390176713A5081754547 @default.
- W390176713 hasConcept C124101348 @default.
- W390176713 hasConcept C127413603 @default.
- W390176713 hasConcept C146978453 @default.
- W390176713 hasConcept C154945302 @default.
- W390176713 hasConcept C177264268 @default.
- W390176713 hasConcept C199360897 @default.
- W390176713 hasConcept C23123220 @default.
- W390176713 hasConcept C2776083694 @default.
- W390176713 hasConcept C2776436953 @default.
- W390176713 hasConcept C2776825360 @default.
- W390176713 hasConcept C2778865114 @default.
- W390176713 hasConcept C33762810 @default.
- W390176713 hasConcept C33923547 @default.
- W390176713 hasConcept C41008148 @default.
- W390176713 hasConcept C42011625 @default.
- W390176713 hasConcept C510870499 @default.
- W390176713 hasConcept C5655090 @default.
- W390176713 hasConcept C58166 @default.
- W390176713 hasConcept C64543145 @default.
- W390176713 hasConcept C77088390 @default.
- W390176713 hasConcept C80444323 @default.
- W390176713 hasConceptScore W390176713C124101348 @default.
- W390176713 hasConceptScore W390176713C127413603 @default.
- W390176713 hasConceptScore W390176713C146978453 @default.
- W390176713 hasConceptScore W390176713C154945302 @default.
- W390176713 hasConceptScore W390176713C177264268 @default.
- W390176713 hasConceptScore W390176713C199360897 @default.
- W390176713 hasConceptScore W390176713C23123220 @default.
- W390176713 hasConceptScore W390176713C2776083694 @default.
- W390176713 hasConceptScore W390176713C2776436953 @default.
- W390176713 hasConceptScore W390176713C2776825360 @default.
- W390176713 hasConceptScore W390176713C2778865114 @default.
- W390176713 hasConceptScore W390176713C33762810 @default.
- W390176713 hasConceptScore W390176713C33923547 @default.
- W390176713 hasConceptScore W390176713C41008148 @default.
- W390176713 hasConceptScore W390176713C42011625 @default.
- W390176713 hasConceptScore W390176713C510870499 @default.
- W390176713 hasConceptScore W390176713C5655090 @default.
- W390176713 hasConceptScore W390176713C58166 @default.
- W390176713 hasConceptScore W390176713C64543145 @default.
- W390176713 hasConceptScore W390176713C77088390 @default.
- W390176713 hasConceptScore W390176713C80444323 @default.
- W390176713 hasLocation W3901767131 @default.
- W390176713 hasOpenAccess W390176713 @default.
- W390176713 hasPrimaryLocation W3901767131 @default.
- W390176713 hasRelatedWork W1975859956 @default.
- W390176713 hasRelatedWork W2001016939 @default.
- W390176713 hasRelatedWork W2098086597 @default.
- W390176713 hasRelatedWork W2101860636 @default.
- W390176713 hasRelatedWork W2106421800 @default.
- W390176713 hasRelatedWork W2117391519 @default.
- W390176713 hasRelatedWork W2184255026 @default.
- W390176713 hasRelatedWork W2270153803 @default.
- W390176713 hasRelatedWork W2354372682 @default.
- W390176713 hasRelatedWork W2385685283 @default.
- W390176713 hasRelatedWork W2388423878 @default.
- W390176713 hasRelatedWork W2516115785 @default.
- W390176713 hasRelatedWork W2584178177 @default.
- W390176713 hasRelatedWork W2584703162 @default.
- W390176713 hasRelatedWork W2735992016 @default.
- W390176713 hasRelatedWork W2807232009 @default.
- W390176713 hasRelatedWork W2903877409 @default.
- W390176713 hasRelatedWork W3011104238 @default.
- W390176713 hasRelatedWork W3011431054 @default.
- W390176713 hasRelatedWork W96130865 @default.
- W390176713 isParatext "false" @default.
- W390176713 isRetracted "false" @default.
- W390176713 magId "390176713" @default.
- W390176713 workType "dissertation" @default.