The fuzzy min-max neural network classifier is a supervised learning method. This classifier takes the hybrid neural networks and fuzzy systems approach. All input variables in the network are required to correspond to continuously valued variables, and this can be a significant constraint in many real-world situations where there are not only quantitative but also categorical data. The usual way of dealing with this type of variables is to replace the categorical by numerical values and treat them as if they were continuously valued. But this method, implicitly defines a possibly unsuitable metric for the categories. A number of different procedures have been proposed to tackle the problem. In this article, we present a new method. The procedure extends the fuzzy min-max neural network input to categorical variables by introducing new fuzzy sets, a new operation, and a new architecture. This provides for greater flexibility and wider application. The proposed method is then applied to missing data imputation in voting intention polls. The micro data-the set of the respondents' individual answers to the questions-of this type of poll are especially suited for evaluating the method since they include a large number of numerical and categorical attributes.
Multilingual lexicons are needed in various applications, such as cross-lingual information retrieval, machine translation and some others. Often, these applications suffer from the ambiguity of dictionary items, especially when an intermediate natural language is involved in the process of the dictionary construction, since this language adds its ambiguity to the ambiguity of working languages. This paper aims at proposing a new method for producing multilingual dictionaries without the risk of introducing additional ambiguity. As a disambiguated intermediate language we use the so-called Universal Words. A set of more than 200,000 unambiguous Universal Words have been constructed automatically on the basis of the well-known English lexical database WordNet. This approach is being used for the construction of a five language-dictionary in the field of cultural heritage within the framework of the PATRILEX project sponsored by the Spanish Research Council.
Abstract. We are presenting a description of the UNL initiative based on the Universal Networking Language (UNL). This language was conceived to be the support of the multilingual communication on the Internet beyond the linguistic barriers. This initiative was launched by the Institute of Advanced Studies of the United Nations University in 1996. The initial consortium was formed to support 15 languages. Eight years later, this initial consortium changed, many components and resources were developed, and the UNL language itself evolved to be the support of different type of applications from the multilingual generation to the "knowledge repositories" or cross lingual information retrieval applications. We describe the main features of the UNL Language making a comparison with some similar approaches like interlinguas. We also describe some organizational and managerial aspects of the UNL according the criteria of quality and maturity, putting emphasis on the open character of the initiative for any interested group or researcher.
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