26572934
Intelligent techniques for global e-business Web portal development
This paper presents a series of intelligent techniques that facilitates the automatic development of multilingual Web portal for e-business operating as global enterprise. It aims to provide an efficient and effective framework for selecting and organizing knowledge from voluminous linguistically diverse Web contents. To achieve this, a concept-based approach that incorporates text mining and Web intelligence using neural network and fuzzy techniques is proposed. First, a concept-based taxonomy of themes, which will act as the hierarchical backbone of the Web portal, is automatically generated. Second, a concept-based multilingual Web crawler is developed to intelligently harvest relevant multilingual documents from the Web. Finally, a concept-based multilingual text categorization technique is proposed to organize multilingual documents by concepts. As such, correlated multilingual Web documents can be gathered/filtered/organised based on their semantic content to facilitate high-performance multilingual information access.
26508095
Computer-aided system to solve uncertainty in project management
In project management, uncertainty often exists in relation to the estimation of activity durations. Fuzzy set theory is an effective way of solving the uncertainty caused by a lack of sufficient precise information. To schedule a project under conditions of limited resources, a genetic algorithm combined with a tabu mechanism is developed in order to search effectively and efficiently for a global-optimal or near-optimal solution. The fuzzy algorithm developed has been integrated into a computer-aided system. An experiment has demonstrated that the system is beneficial for solving such NP-hard problems when the project size increases.
30777974
Identifying Parallel Web Documents by Filenames
Parallel Web documents are the crucial lexical basis for constructing robust multilingual Web-based linguistic knowledge resources. To identify parallel Web documents efficiently and effectively, this paper develops a new automatic approach based on filenames using the commonly used parallel document naming practice on the Web. The approach involves three procedures for identifying common file descriptor, language flag, and language flag-pair respectively among all file names examined. To examine how these three procedures can be used to get the best result, five methods are developed by incorporating these procedures in different ways. An experimental study on a Hong Kong government Web site is conducted to evaluate the performance of these five methods in terms of recall and precision. The experimental result shows that the method combining the procedures of the file descriptor alignment and the language flag-pair alignment outperforms other methods, with a 95.3% of precision rate and a 91.0% of recall rate.
34978103
Inter-company comparison using modified TOPSIS with objective weights
Abstract Simultaneous consideration of multiple financial ratios is required to adequately evaluate and rank the relative performance of competing companies. This paper formulates the inter-company comparison process as a multi-criteria analysis model, and presents an effective approach by modifying TOPSIS for solving the problem. The modified TOPSIS approach can identify the relevance of the financial ratios to the evaluation result, and indicate the performance difference between companies on each financial ratio. To ensure that the evaluation result is not affected by the inter-dependence of the financial ratios, objective weights are used. As a result, the comparison process is conducted on a commonly accepted basis and is independent of subjective preferences of various stakeholders. An empirical study of a real case in China is conducted to illustrate how the approach is used for the inter-company comparison problem. The result shows that the approach can reflect the decision information emitted by the financial ratios used. The comparison of objective weighting methods suggests that, with the modified TOPSIS approach, the entropy measure compares favourably with other methods for the case study conducted. Scope and purpose The performance evaluation and ranking of modern enterprises is a complex process, in which multiple financial ratios are required to be considered simultaneously. The purpose of this paper is to apply the framework of multi-criteria analysis to the inter-company comparison problem. An effective approach based on the concept used by the technique for order preference by similarity to ideal solution (TOPSIS) is developed to rank competing companies in terms of their overall performance on multiple financial ratios. The approach modifies the TOPSIS method by using weighted Euclidean distances to ensure a meaningful interpretation of the evaluation result. The use of objective weights for financial ratios based on Shannon's entropy concept reflects the context-dependent concept of informational importance. This ensures that the evaluation result is not affected by the inter-dependency of criteria and inconsistency of subjective weights. This approach is particularly applicable for situations where reliable subjective weights cannot be obtained. With its simplicity in both concept and computation, the approach can readily be incorporated into a computer-based system.
7026890
Improving Business Failure Predication Using Rough Sets with Non-financial Variables
Rough set models with financial variables have proven to be effective in predicting business failure. To enhance the predictive performance of rough set models, this paper includes a non-financial variable, auditor switching, into the modeling process, in addition to 14 financial ratios commonly used in business failure research. An empirical study on 62 failed firms and 62 one-to-one matching non-failed firms in Taiwan between 1998 and 2005 is conducted, using available data for the three years before failure. Six rough set models are constructed individually with and without the auditor switching variable, using the three-year data respectively. The empirical study shows that the non-financial variable is the most significant attribute and plays an essential role in enhancing the performance of rough set models. These findings highlight the effectiveness of rough set models for business failure prediction and particularly the importance of incorporating non-financial variables in business failure research.
19978728
Fuzzy Utilities Comparison in Multicriteria Analysis
This paper presents a new approach for comparing fuzzy utilities in fuzzy multicriteria analysis. The approach developed combines the merit of two prominent concepts individually used in the existing methods: the fuzzy reference set and the degree of dominance. The decisive information of the fuzzy utilities being compared is sensibly used. The computation involved is simple, and the underlying concepts are logically sound and comprehensible. The comparative study conducted on benchmark cases in the literature shows that the approach compares favorably with other methods examined.
10821054
A Kernel-Based Two-Stage One-Class Support Vector Machines Algorithm
One-class SVM is a kernel-based method that utilizes the kernel trick for data clustering. However it is only able to detect one cluster of non-convex shape in the input space. In this study, we propose an iterative two-stage one-class SVM to cluster data into several groups. In the first stage, one-class SVM is used to find an optimal weight vector for each cluster in the feature space, while in the second stage the weight vector is used to refine the clustering result. A mechanism is provided to control the optimal hyperplane to work against outliers. Experimental results have shown that our method compares favorably with other kernel based clustering algorithms, such as KKM and KFCM on several synthetic data sets and UCI real data sets.
7363085
An Empirical Study On The Generation Of Zero Anaphors In Chinese
In this paper, we describe the creation of rules for generating Chinese zero anaphors through a sequence of experiments in a stepwise enhanced manner. In the experiments, we basically examined the occurence of zero anaphors in a real text and the ones generated by the algorithms employing the rules, assuming the same semantic and discourse structures as the text. The factors of locality, syntactic constraints, discourse structure and salience of objects were considered in the rules. The results of the experiment show that 93% of the zero anaphors in the text can be correctly generated by an algorithm using a rule involving all the above factors.