Database queries with fuzzy linguistic quantifiers
IEEE Transactions on Systems, Man and Cybernetics
Beyond min aggregation in multicriteria decision: (ordered) weighted min, discri-min, leximin
The ordered weighted averaging operators
Using fuzzy sets in flexible querying: why and how?
Flexible query answering systems
A relational model of data for large shared data banks
Communications of the ACM
Bipolarity in Flexible Querying
FQAS '02 Proceedings of the 5th International Conference on Flexible Query Answering Systems
Preferences; Putting More Knowledge into Queries
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Bipolar Queries and Queries with Preferences (Invited Paper)
DEXA '06 Proceedings of the 17th International Conference on Database and Expert Systems Applications
Proceedings of the 2009 ACM symposium on Applied Computing
Fuzzy Sets and Systems
Fuzzy sets in database and information systems: Status and opportunities
Fuzzy Sets and Systems
Bipolar representations in reasoning, knowledge extraction and decision processes
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
SQLf: a relational database language for fuzzy querying
IEEE Transactions on Fuzzy Systems
A flexible bipolar querying approach with imprecise data and guaranteed results
Fuzzy Sets and Systems
Bipolar queries: An aggregation operator focused perspective
Fuzzy Sets and Systems
Bipolar fuzzy querying of temporal databases
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
Bipolar SQLf: a flexible querying language for relational databases
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
Bipolar queries in textual information retrieval: A new perspective
Information Processing and Management: an International Journal
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When expressing their information needs in a (database) query, users sometimes prefer to state what has to be rejected rather than what has to be accepted. In general, what has to be rejected is not necessarily the complement of what has to be accepted. This phenomenon is commonly known as the heterogeneous bipolar nature of expressing information needs. Satisfaction degrees in regular fuzzy querying approaches are based on the `symmetric' assumption that the extent to which a database record respectively satisfies and does not satisfy a given query are complements of each other and are therefore less suited to adequately handle heterogeneous bipolarity in query specifications and query processing. In this paper we present a bipolar query satisfaction modelling framework which is based on couples that consist of an independent degree of satisfaction and degree of dissatisfaction. The use and advantages of the framework are illustrated in the context of fuzzy query evaluation in regular relational databases. More specifically, the evaluation of heterogeneous bipolar queries that contain both positive and negative criteria is studied.