A model of an information retrieval system with unbalanced fuzzy linguistic information

Most information retrieval systems based on linguistic approaches use symmetrically and uniformly distributed linguistic term sets to express the weights of queries and the relevance degrees of documents. However, to improve the system–user interaction, it seems more adequate to express these linguistic weights and degrees by means of unbalanced linguistic scales, that is, linguistic term sets with different discrimination levels on both sides of the middle linguistic term. In this contribution we present an information retrieval system that accepts weighted queries whose weights are expressed using unbalanced linguistic term sets. Then, the system provides the retrieved documents classified in linguistic relevance classes assessed on unbalanced linguistic term sets. To do so, we propose a methodology to manage unbalanced linguistic information and we use the linguistic 2‐tuple model as the representation base of the unbalanced linguistic information. Additionally, the linguistic 2‐tuple model allows us to increase the number of relevance classes in the output and also to improve the performance of the information retrieval system. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 1197–1214, 2007.     

A multigranular hierarchical linguistic model for design evaluation based on safety and cost analysis

Before implementing a design of a large engineering system different design proposals are evaluated. The information used by experts to evaluate different options may be vague and/or incomplete. Although different probabilistic tools and techniques have been used to deal with these kinds of problems, it seems better to use the fuzzy linguistic approach to model vagueness and the Dempster‐Shafter theory of evidence for modeling incompleteness and ignorance. In the evaluation of alternative designs, different criteria can be considered. In this article an evaluation process is developed in terms of Safety and Cost analysis. Both criteria involve uncertainty, vagueness, and ignorance due to their nature. Therefore, we propose an evaluation process defined in a linguistic framework where both criteria will be conducted in different utility spaces, i.e., in a multigranular linguistic domain. Once the evaluation framework has been defined, we present an evaluation process based on a Multi‐Expert Multi‐Criteria decision model that will be able to deal with multigranular linguistic information without loss of information in order to evaluate different design options for an engineering system in a precise manner. Accordingly, we propose the use of a multigranular linguistic model based on the Linguistic Hierarchies presented by Herrera and Martínez (“A model based on linguistic 2‐tuples for dealing with multigranularity hierarchical linguistic contexts in multi‐expert decision‐making.” IEEE Trans Syst Man Cybern B 2001;31(2):227–234). © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 1161–1194, 2005.     

Flexible querying via if-sets

The traditional query languages used in database management systems require precise and unambiguous queries only. Fuzzy querying was introduced to relax this rigidity and allow the user more natural information retrieval. In this article we suggest how to enrich fuzzy querying by the use of IF-sets. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 587–597, 2007.     

Handling linguistic web information based on a multi‐agent system

Much information over the Internet is expressed by natural languages. The management of linguistic information involves an operation of comparison and aggregation. Based on the Ordered Weighted Averaging (OWA) operator and modifying indexes of linguistic terms (their indexes are fuzzy numbers on [0,T] ? R⁺), new linguistic aggregating methods are presented and their properties are discussed. Also, based on a multi‐agent system and new linguistic aggregating methods, gathering linguistic information over the Internet is discussed. Moreover, by fixing the threshold α, “soft filtering information” is proposed and better Web pages (or documents) that the user needs are obtained. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 435–453, 2007.     

α‐Cut fuzzy control charts for linguistic data

The major contribution of fuzzy set theory is its capability of representing vague data. Fuzzy logic offers a systematic base in dealing with situations that are ambiguous or not well defined. In the literature, there exist some fuzzy control charts developed for linguistic data that are mainly based on membership and probabilistic approaches. In this article, α‐cut control charts for attributes are developed. This approach provides the ability of determining the tightness of the inspection by selecting a suitable α‐level: The higher α the tighter inspection. The article also presents a numerical example and interprets and compares other results with the approaches developed previously. © 2004 Wiley Periodicals, Inc. Int J Int Syst 19: 1173–1195, 2004.     

Abductive case‐based reasoning

This article introduces abductive case‐based reasoning (CBR) and attempts to show that abductive CBR and deductive CBR can be integrated in clinical process and problem solving. Then it provides a unified formalization for integration of abduction, abductive CBR, deduction, and deductive CBR. This article also investigates abductive case retrieval and deductive case retrieval using similarity relations, fuzzy similarity relations, and similarity metrics. The proposed approach demonstrates that the integration of deductive CBR and abductive CBR is of practical significance in problem solving such as system diagnosis and analysis, and will facilitate research of abductive CBR and deductive CBR. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 957–983, 2005.     

An argument‐based decision support system for assessing natural language usage on the basis of the web corpus

The last decade bears witness to an exponential growth in the use of the World Wide Web. As a result, a huge number of documents are accessible online through search engines, whose pattern‐matching capabilities have turned out to be useful for mining the Web space as a particular kind of linguistic corpus, commonly known as the Web Corpus. This article presents a novel, argumentative approach to providing proactive assistance for language usage assessment on the basis of usage indices, which are good indicators of the suitability of an expression on the basis of the Web Corpus. The user preferences consist of a number of (possibly defeasible) rules and facts that encode different aspects of adequate language usage, defining the acceptability of different terms on the basis of the computed usage indices. A defeasible argumentation system determines if a given expression is ultimately acceptable by analyzing a defeasible logic program that encodes the user's preferences. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 1151–1180, 2006.     

On a similarity measure between LR‐type fuzzy numbers and its application to database acquisition

This article presents a new similarity measure for LR‐type fuzzy numbers. The proposed similarity measure is based on a defined metric between LR‐type fuzzy numbers. It is known that an exponential operation is highly useful in dealing with the classical Shannon entropy and cluster analysis. We adopted, therefore, the exponential operation on this metric. Furthermore, we analyze its properties and make numerical comparisons to several similarity measures. The results show that the proposed similarity measure can overcome the drawbacks of the existing similarity measures. We then apply it to compound attributes for handling null queries to database systems. These applications can also be widely used in fuzzy queries to databases. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 1001–1016, 2005.     

EGO: A personalized multimedia management and retrieval tool

The problems of content‐based image retrieval (CBIR) systems can be attributed to the semantic gap between the low‐level data representation and the high‐level concepts the user associates with images, on the one hand, and the time‐varying and often vague nature of the underlying information need, on the other. These problems can be addressed by improving the interaction between the user and the system. In this article, we sketch the development of CBIR interfaces and introduce our view on how to solve some of the problems these interfaces present. To address the semantic gap and long‐term multifaceted information needs, we propose a “retrieval in context” system, EGO. EGO is a tool for the management of image collections, supporting the user through personalization and adaptation. We will describe how it learns from the user's personal organization, allowing it to recommend relevant images to the user. The recommendation algorithm is described, which is based on relevance feedback techniques. Additionally, we provide results of a performance analysis of the recommendation system and of a preliminary user study. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 725–745, 2006.     

Learning cooperative linguistic fuzzy rules using the best–worst ant system algorithm

Within the field of linguistic fuzzy modeling with fuzzy rule‐based systems, the automatic derivation of the linguistic fuzzy rules from numerical data is an important task. In the last few years, a large number of contributions based on techniques such as neural networks and genetic algorithms have been proposed to face this problem. In this article, we introduce a novel approach to the fuzzy rule learning problem with ant colony optimization (ACO) algorithms. To do so, this learning task is formulated as a combinatorial optimization problem. Our learning process is based on the COR methodology proposed in previous works, which provides a search space that allows us to obtain fuzzy models with a good interpretability–accuracy trade‐off. A specific ACO‐based algorithm, the Best–Worst Ant System, is used for this purpose due to the good performance shown when solving other optimization problems. We analyze the behavior of the proposed method and compare it to other learning methods and search techniques when solving two real‐world applications. The obtained results lead us to remark the good performance of our proposal in terms of interpretability, accuracy, and efficiency. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 433–452, 2005.     

Hierarchical spatial relation based on a contiguity graph

Autonomous agents traversing a natural space need to be knowledgeable of its space configuration. The existing space models in geographic information systems and robotics, however, deal with only the topological relations among numerous types of spatial relations. We aim to develop an enhanced space model that elaborates the spatial relations with respect to their relevant physical relations. Specifically, the spatial relations in a space configuration are further characterized with the gravitation as a potential factor to affect the space configuration. The resulting space model is capable of capturing an extended set of spatial relations over existing models such as a four‐intersection model. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 867–892, 2005.     

Scene similarity measure for video content segmentation in the framework of a rough indexing paradigm

This article presents a scene similarity measure for video content segmentation. In the context of the rough indexing paradigm, we extract only partial information from MPEG compressed streams to measure the similarity of video frames through time. The similarity measure of I‐Frames is defined based on motion compensation of DC images and local contrast computation. The method allows a real‐time segmentation of the video content. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 765–783, 2006.     

Methods of case adaptation: A survey

In this article, we provide an overview of the case adaptation process. We classify various existing case adaptation methods available in the literature. We consider three different aspects, namely, domain knowledge requirement, adaptive capabilities of the case adaptation methods, and the kind of adaptation knowledge required. We then derive certain findings about the nature of the case adaptation methods and their applicability in real‐life tasks. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 627–645, 2005.     

Local identification of prototypes for genetic learning of accurate TSK fuzzy rule‐based systems

This work presents the use of local fuzzy prototypes as a new idea to obtain accurate local semantics‐based Takagi–Sugeno–Kang (TSK) rules. This allow us to start from prototypes considering the interaction between input and output variables and taking into account the fuzzy nature of the TSK rules. To do so, a two‐stage evolutionary algorithm based on MOGUL (a methodology to obtain Genetic Fuzzy Rule‐Based Systems under the Iterative Rule Learning approach) has been developed to consider the interaction between input and output variables. The first stage performs a local identification of prototypes to obtain a set of initial local semantics‐based TSK rules, following the Iterative Rule Learning approach and based on an evolutionary generation process within MOGUL (taking as a base some initial linguistic fuzzy partitions). Because this generation method induces competition among the fuzzy rules, a postprocessing stage to improve the global system performance is needed. Two different processes are considered at this stage, a genetic niching‐based selection process to remove redundant rules and a genetic tuning process to refine the fuzzy model parameters. The proposal has been tested with two real‐world problems, achieving good results. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 909–941, 2007.     

A unified logical model for CBR‐based e‐commerce systems

This article examines new issues resulting from applying case‐based reasoning (CBR) in e‐commerce and proposes a unified logical model for CBR‐based e‐commerce systems (CECS) that consists of three cycles and covers almost all activities of applying CBR in e‐commerce. This article also decomposes case adaptation into problem adaptation and solution adaptation, which not only improves the understanding of case adaptation in the traditional CBR, but also facilitates the refinement of activity of CBR in e‐commerce and intelligent support for e‐commerce. It then investigates CBR‐based product negotiation. This article thus gives insight into how to use CBR in e‐commerce and how to improve the understanding of CBR with its applications in e‐commerce from a logical viewpoint. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 29–46, 2005.     

Answers to queries concerning uncertain and imprecise information in fuzzy relational databases

A model of an extended fuzzy relational database was proposed to accommodate uncertain and imprecise information. We use two supplementary measurements, satisfactory degree and extra degree, for determining the quality of answers to Select‐Project‐Join (SPJ) queries. The method of measurement determines how much satisfactory information is provided and how much truth information is required for a query. The answers to the query thus contain sure answers and maybe answers. The core of this study is the detailed discussion on the quality of answers in an extended fuzzy relation to query processing. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 647–668, 2005.     

A multigranular linguistic content‐based recommendation model

Recommendation systems are a clear example of an e‐service that helps the users to find the most suitable products they are looking for, according to their preferences, among a vast quantity of information. These preferences are usually related to human perceptions because the customers express their needs, taste, and so forth to find a suitable product. The perceptions are better modeled by means of linguistic information due to the uncertainty involved in this type of information. In this article, we propose a content‐based recommendation model that will offer a more flexible context to improve the final recommendations where the preferences provided by the sources will be modeled by means of linguistic variables assessed in different linguistic term sets. The proposal consists of offering a multigranular linguistic context for expressing the preferences instead of forcing users to use a unique scale. Then the content‐based recommendation model will look for the most suitable product(s), comparing them with the customer(s) information according to its resemblance. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 419–434, 2007.     

Ant colony optimization of clustering models

The original ant system algorithm is simplified leading to a generalized ant colony optimization algorithm that can be used to solve a wide variety of discrete optimization problems. It is shown how objective function based clustering models such as hard and fuzzy c‐means can be optimized using particular extensions of this simplified ant optimization algorithm. Experiments with artificial and real datasets show that ant clustering produces better results than alternating optimization because it is less sensitive to local extrema. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 1233–1251, 2005.     

基于英汉机译实现跨语言信息检索

随着日益增长的大量信息成为可利用的、用户面对查询一个多语种文本集合的情形，变得越来越普遍。这就产生一个非常重要的问题一以一种语言描述的用户查询与以不同语言书写的文本之间的匹配问题，也就是一种如何跨越语言界限的问题，即跨语言信息检索(Cross-Language Information Retrievat，CLIR)。针对该项任务建立了一个面向英汉的跨语言信息检索系统，并以此为基础提交了相关的几组运行结果。同时，结合所构建的汉语IR系统，实现完整的英一汉CLIR过程。