Fuzzy relational databases have been extensively studied in recent years, resulting in several models and constructs, some of which are implemented as software layers on top of diverse existing database systems. Fuzzy extensions to query languages and end-user query interfaces have also been developed, but the design of programming interfaces has not been properly addressed. In this paper, we d...

We derive a new generalization of lowest common ancestors (LCAs) in dags, called the lowest single common ancestor (LSCA). We show how to preprocess a static dag in linear time such that subsequent LSCA-queries can be answered in constant time. The size is linear in the number of nodes. We also consider a “fuzzy” variant of LSCA that allows to compute a node that is only an LSCA of a given perc...

In this paper we combine computer vision and data mining techniques to model high-level concepts for image retrieval, on the basis of basic perceptual features of the human visual system. High-level concepts related to these features are learned and represented by means of a set of fuzzy association rules. The concepts so acquired can be used for image retrieval with the advantage that it is no...

A key challenge for companies is to manage customer relationships as an asset. To create an effective toolkit for the analysis of customer relationships, a combination of relational databases and fuzzy logic is proposed. The fuzzy Classification Query Language allows marketers to improve customer equity, launch loyalty programs, automate mass customization, and refine marketing campaigns.

This paper describes the participation of the Human Interface Laboratory of Meiji University in the ImageCLEF2008 photo retrieval task. We submitted eight retrieval runs taking two main approaches. The first approach combined Text-Based Image Retrieval (TBIR) and Context-Based Image Retrieval (CBIR). The second approach applied query expansion using conceptual fuzzy sets (CFS). A CFS is a metho...

Generating relevant and manageable search results is of great interest in database queries and information retrieval nowadays. This paper proposes an approach to measuring relation compactness and to generating a compact set of query outcomes under a fuzzy relational data model. The approach has desirable properties that (1) the resultant compact set is unique and contains mutually distinct tup...

In agricultural domain, the ObjectProperty knowledge is a useful knowledge that serves the ‘Know-what’ to a farmer or to an agriculturalist such as pest’s characteristics (color, size, and etc). This paper proposes the framework for extracting the object and its properties and also the query system. The extraction problems consist of object identification, property relation identification, and ...

This paper discusses the implementation of Support Vector Machine (SVM) based ranking metrics to compute the similarity and rank the documents based on a user query using Fuzzy Logic. TREC dataset has been used for the same purpose. The dataset is parsed to generate keywords index which is used for the similarity comparison with the user query and ranking is done using SVM. Each query is assign...

We present a top-k query answering procedure for Fuzzy Logic Programming, in which arbitrary computable functions may appear in the rule bodies to manipulate truth values. The top-k ranking problem, i.e. determining the top k answers to a query, becomes important as soon as the set of facts becomes quite large. © 2012 Elsevier B.V. All rights reserved.

Modern Information Retrieval Systems match the terms contained in a user’s query with available documents through the use of an index. In this work, we propose a method for expanding the query with its associated terms, in order to increase the system recall. The proposed method is based on a novel fuzzy clustering of the