- Portugal
Alipio Jorge
Universidade do Porto, Departamento de Ciência de Computadores, Faculty Member
Reasoning about spatial information is fundamental in natural language to fully understand relationships between entities and/or between events. However, the complexity underlying such reasoning makes it hard to represent formally spatial... more
Reasoning about spatial information is fundamental in natural language to fully understand relationships between entities and/or between events. However, the complexity underlying such reasoning makes it hard to represent formally spatial information. Despite the growing interest on this topic, and the development of some frameworks, many problems persist regarding, for instance, the coverage of a wide variety of linguistic constructions and of languages. In this paper, we present a proposal of integrating ISO-Space into a ISO-based multilayer annotation scheme, designed to annotate news in European Portuguese. This scheme already enables annotation at three levels, temporal, referential and thematic, by combining postulates from ISO 24617-1, 4 and 9. Since the corpus comprises news articles, and spatial information is relevant within this kind of texts, a more detailed account of space was required. The main objective of this paper is to discuss the process of integrating ISO-Space with the existing layers of our annotation scheme, assessing the compatibility of the aforementioned parts of ISO 24617, and the problems posed by the harmonization of the four layers and by some specifications of ISO-Space.
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Research Interests:
... Steve Moyle (1), Alípio Jorge (2)(3) (1) Oxford University Computing Laboratory, UK, (2) LIACC University of Porto, Rua Campo Alegre 823, 4150 Porto, Portugal. (3) Faculty of Economics, University of Porto, Portugal... more
... Steve Moyle (1), Alípio Jorge (2)(3) (1) Oxford University Computing Laboratory, UK, (2) LIACC University of Porto, Rua Campo Alegre 823, 4150 Porto, Portugal. (3) Faculty of Economics, University of Porto, Portugal amjorge@liacc.up.pt, http://www.niaad.liacc.up.pt/~amjorge ...
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Research Interests:
Page 1. MODEL-BASED COLLABORATIVE FILTERING FOR TEAM BUILDING SUPPORT Miguel Veloso Enabler Solutions for Retailing, Av. da Boavista, 1223, 4100-130 Porto - Portugal, miguel.veloso@enabler.com, miv@mail.telepac.pt ...
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In some classification tasks, such as those related to the automatic building and maintenance of text corpora, it is expensive to obtain labeled examples to train a classifier. In such circumstances it is common to have massive corpora... more
In some classification tasks, such as those related to the automatic building and maintenance of text corpora, it is expensive to obtain labeled examples to train a classifier. In such circumstances it is common to have massive corpora where a few examples are labeled (typically a minority) while others are not. Semi-supervised learning techniques try to leverage the intrinsic information in unlabeled examples to improve classification models. However, these techniques assume that the labeled examples cover all the classes to learn which might not stand. In the presence of an imbalanced class distribution getting labeled examples from minority classes might be very costly if queries are randomly selected. Active learning allows asking an oracle to label new examples, that are criteriously selected, and does not assume a previous knowledge of all classes. D-Confidence is an active learning approach that is effective when in presence of imbalanced training sets. In this paper we discu...
We present a generic model and software module of spread-ing activation, and its specialisation to support a number of specific models in the literature. We hope the unification thus provided helps understand spreading activation in... more
We present a generic model and software module of spread-ing activation, and its specialisation to support a number of specific models in the literature. We hope the unification thus provided helps understand spreading activation in general and compare specific mod-els. We also provide a new specific model, Watermark, that reduces the number of parameters of a class of specific models.
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In this paper we discuss how trip time prediction can be useful for operational optimization in mass transit companies and which machine learning techniques can be used to improve results. Firstly, we analyze which departments need trip... more
In this paper we discuss how trip time prediction can be useful for operational optimization in mass transit companies and which machine learning techniques can be used to improve results. Firstly, we analyze which departments need trip time prediction and when. Secondly, we review related work and thirdly we present the analysis of trip time over a particular path. We proceed by presenting experimental results conducted on real data with the forecasting techniques we found most adequate, and conclude by discussing guidelines for future work.
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In this paper we discuss how trip time prediction can be useful for operational optimization in mass transit companies and how data mining techniques can be used to improve results. Firstly, we an- alyze which departments need trip time... more
In this paper we discuss how trip time prediction can be useful for operational optimization in mass transit companies and how data mining techniques can be used to improve results. Firstly, we an- alyze which departments need trip time prediction and when. Secondly, we review related work and thirdly we present the analysis of trip time over a particular path. We proceed by presenting experimental results conducted on real data with the forecasting techniques we found most adequate, and conclude by discussing guidelines for future work.
The first multidimensional algorithm for recommender systems is the well known combined reduction-based, which treats additional dimensions as labels for segmenting/filtering sessions, using the segmented sessions to build the... more
The first multidimensional algorithm for recommender systems is the well known combined reduction-based, which treats additional dimensions as labels for segmenting/filtering sessions, using the segmented sessions to build the recommendation model. This algorithm only uses the additional dimensions when it outperforms the traditional two-dimensional algorithm. Otherwise, it reverts to the traditional two-dimensional algorithm to generate the top-N recommendations. In this paper, we propose to improve the combined reduction-based algorithm by using the DaVI approach, which handles additional dimensions as virtual items. Incorporating the DaVI approach into the combined reductionbased, the multidimensional algorithm uses the additional dimensions not only as labels for segmenting sessions but also as virtual items to improve the recommendation model. The empirical results demonstrate that our proposal reduces the needs of reverting to the traditional two-dimensional algorithm to gener...
We present a schema for documenting and classifying completed Data Mining, Decision Support and Text and Web Mining cases. Project descriptions from these areas are unified in a hierachically structured relational database. The main... more
We present a schema for documenting and classifying completed Data Mining, Decision Support and Text and Web Mining cases. Project descriptions from these areas are unified in a hierachically structured relational database. The main objectives and benefits of the repository are presented and discussed.
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Some real life problems require the classification of items into naturally ordered classes. Conventional methods, intended for the classification of nominal classes, are traditionally used to deal with these problems where the classes are... more
Some real life problems require the classification of items into naturally ordered classes. Conventional methods, intended for the classification of nominal classes, are traditionally used to deal with these problems where the classes are ordered. This paper proposes an adaptation of association rules for classification intended for multi-class problems where the order relation is not ignored. The theoretical background assumes that the random variable class associated with a given query should follow a unimodal distribution. The adaptation, which uses class association rules (CAR's), is essentially in terms of the output handling, i.e the voting system for the predicted class. The experiments in real datasets are presented. Despite this very simple variant of association rules for classification, the results indicate that the method is making valid predictions and is competitive with state-of-the-art algorithms.
The knowledge gathered by an organization throughout its activity is too valuable an asset to be kept volatile, always dependent on those who produced it. Organizational knowledge also tends to be tacit, and distributed, so only a small... more
The knowledge gathered by an organization throughout its activity is too valuable an asset to be kept volatile, always dependent on those who produced it. Organizational knowledge also tends to be tacit, and distributed, so only a small part of it is likely to be acquired and retained. This chapter describes a number of techniques and tools for capturing this kind of knowledge, applied to a particular research project organization. These techniques cover the design of versatile information collection templates and ways of collecting information from members of the organization. Another important aim is to make such information available internally to the organization, as well as externally to the world. The collection and dissemination of organizational knowledge is realized through Web systems. The Web is also used to link the (distributed) set of tools into an integrated system, allowing some of these tools to communicate automatically. Important issues such as security and ease o...
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Association rule engines typically output a very large set of rules. Despite the fact that association rules are regarded as highly comprehensible and useful for data mining and decision support in fields such as marketing, retail,... more
Association rule engines typically output a very large set of rules. Despite the fact that association rules are regarded as highly comprehensible and useful for data mining and decision support in fields such as marketing, retail, demographics, among others, lengthy outputs may discourage users from using the technique. In this paper we propose a post-processing methodology and tool for browsing/visualizing large sets of association rules. The method is based on a set of operators that transform sets of rules into sets of rules, allowing focusing on interesting regions of the rule space. Each set of rules can be then seen with different graphical representations. The tool is web-based and uses SVG. Association rules are given in PMML.
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Research Interests:
... This includes table, record and attribute selection as well as transformation and cleaning of ... to share data, data transformations and metadata, to apply models to training data and to ... Compared to software development, data... more
... This includes table, record and attribute selection as well as transformation and cleaning of ... to share data, data transformations and metadata, to apply models to training data and to ... Compared to software development, data mining and site planning service-oriented rather than ...
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... L. Ferreira Marcelo Finger Miguel Filgueiras Jose M. Fonseca Dalila Fontes Michael Fink Michael Fisher Ana Fred Joao Gama Pablo Gamallo Gabriela Guimaraes Nick Jennings Alipio Jorge Claude Kirchner Jorg Keller Norbert Kuhn King-Ip Lin... more
... L. Ferreira Marcelo Finger Miguel Filgueiras Jose M. Fonseca Dalila Fontes Michael Fink Michael Fisher Ana Fred Joao Gama Pablo Gamallo Gabriela Guimaraes Nick Jennings Alipio Jorge Claude Kirchner Jorg Keller Norbert Kuhn King-Ip Lin Vitor Lobo Alneu A. Lopes Luis ...
Page 1. Alípio Mário Guedes Jorge Indução Iterativa de Programas Lógicos Uma abordagem à síntese de programas lógicos a partir de especificações incompletas Tese submetida para obtenção do grau de Doutor em Ciência de Computadores ...
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The emerging standard for the platform- and system-independent representation of data mining models, PMML (Predictive Model Markup Language), is currently supported by a number of knowledge discovery support engines (KDDSE). The primary... more
The emerging standard for the platform- and system-independent representation of data mining models, PMML (Predictive Model Markup Language), is currently supported by a number of knowledge discovery support engines (KDDSE). The primary purpose of the PMML standard is to separate model generation from model storage in order to enable users to view, post-process, and utilize data mining models independently of
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We report the use of Ada in the European research project Sol-Eu-Net. Ada was used in a web mining subproject, mainly for data preparation, and also for web system development. Open source Ada resources e.g. GNAT.Spitbol were used. Some... more
We report the use of Ada in the European research project Sol-Eu-Net. Ada was used in a web mining subproject, mainly for data preparation, and also for web system development. Open source Ada resources e.g. GNAT.Spitbol were used. Some such resources were modified, some created anew. XML and SQL were also used in association with Ada.
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ABSTRACT Web mining can be defined as the use of data mining techniques to automatically discover and extract information from web documents and services. A decision support system is a computer-based information system that supports... more
ABSTRACT Web mining can be defined as the use of data mining techniques to automatically discover and extract information from web documents and services. A decision support system is a computer-based information system that supports business or organizational decision-making activities. Data mining and business intelligence techniques can be integrated in order to develop more advanced decision support systems. In this chapter, the authors propose to use web mining as a process to develop advanced decision support systems in order to support the management activities of a website. They describe the web mining process as a sequence of steps for the development of advanced decision support systems. By following such a sequence, the authors can develop advanced decision support systems, which integrate data mining with business intelligence, for websites.