When the available information is imperfect, it is often desirable to represent it in the database, so that it can be used to answer queries of interest as much as possible. The data as well as query in data sources are often vague or imprecise (fuzzy). In this paper, a comprehensive classification of fuzzy data is done. This classification will be used as framework for understanding how fuzzy ...

As main result of all our previous work we have now available a FSQL Server for Oracle Databases pro grammed in PL SQL This server allows us to query either a Fuzzy or Classic Relational Database with the FSQL language Fuzzy SQL The FSQL language is an extension of the SQL language which permits us to write exible or fuzzy conditions in our queries to a fuzzy or traditional database In this wor...

Structural Query Language (SQL) is very restrictive and very dominant tool that handles data that is crisp and precise in nature; but it is unable to fulfill the needs for data which is uncertain, imprecise, and vague in nature. The human queries are rarely crisp, which need unusual requirements to deal with it based on world knowledge. These requirements are called Fuzzy Queries (FQ) that real...

The problem addressed in this article is image indexing and retrieval according to the color. Indeed we propose a classification based on the dominant color(s) of the images. The process consists in two steps: first, assigning a colorimetric profile to the image in HLS space (Hue, Lightness, Saturation) and then, handling the query for the retrieval. To achieve the first step, the definition of...

Fuzzy rough set theory is a candidate framework for query refinement. Indeed, a thesaurus defines an approximation space in which the query, which is a set of terms, can be approximated from the upper and the lower side. The upper approximation turns out to be too flexible however, resulting in query explosion, while the lower approximation is too strict, resulting in the empty query. Therefore...

The fuzzy information retrieval model was proposed some years ago to solve several limitations of the Boolean model without a need of a complete redesign of the information retrieval system. However, the complexity of the fuzzy query language makes it difficult to formulate user queries. Among other proposed approaches to solve this problem, we find the Inductive Query by Example (IQBE) framewo...

With the rapid development of Internet of Things (IoT), enormous events are produced by various kinds of devices at high speed. Complex Event Processing (CEP) is the key part of IoT middleware which can help the user to get semantic meanings of primitive events. Context-awareness is an important feature of CEP engine. In this paper a high performance distributed context-aware CEP architecture a...

With the Semantic Web progress many independently developed distinct domain ontologies have to be shared and reused by a variety of applications. The use of ontologies in information retrieval applications allows the retrieval of semantically related documents to an initial users’ query. This work presents a fuzzy information retrieval model for improving the document retrieval process consider...

This position paper proposes a collaboration method between Semantic Web and Fuzzy Logic aiming to handle uncertainty in the information retrieval process in order to cover more relevant items in result of search process. The collaboration method employs OWL ontology in query enhancement, RDF in annotation process and fuzzy rules in ranking enhancement.

Spatial decision making is a fundamental function of contemporary Geographic Information Systems (GIS). One of the most fertile GIS development areas is integrating multiple criteria decision models (MCDM) into GIS querying mechanisms. The classic approach for this integration has been to use Boolean techniques of MCDM with crisp representations of spatial objects (features) to produce static m...