121,772 research outputs found
Dataset_folder
No full textThe folder has the seventeen network datasets we used for a network regression task. The folder contains the files used for a 5-cross validation experiment replicated by 5 trials. The datasets are organized in 4 categories of files: namefile_arffTest_N (the testing file for the trial N-th), namefile_arffTrain_M (the training file for the trial M-th), namefile_arffTrain_P_arffSampleQ (the sample for Q-th trial at P-th fold). Also, a file of the distances of the edges is associated to each dataset
Dataset_folder
No full textThe folder has the seventeen network datasets we used for a network regression task. The folder contains the files used for a 5-cross validation experiment replicated by 5 trials. The datasets are organized in 4 categories of files: namefile_arffTest_N (the testing file for the trial N-th), namefile_arffTrain_M (the training file for the trial M-th), namefile_arffTrain_P_arffSampleQ (the sample for Q-th trial at P-th fold). Also, a file of the distances of the edges is associated to each dataset
Mining Trajectory Data for Discovering Communities of Moving Objects
No full textRecent advances on tracking technologies enable the collection of spatio-temporal data in the form of trajectories. The analysis of such data can convey knowledge in prominent applications, and mining groups of moving objects turns out to be a valuable mean to model their movement. Existing approaches pay particular attention in groups where objects are close and move together or follow similar trajectories by assuming that movement cannot change over time. Instead, we observe that groups can be of interest also when objects are spatially distant and have di↵erent but inter-related movements: objects can start from di↵erent places and join together to move towards a common location. To take into account inter-related movements, we have to analyze the objects jointly, follow their respective movements and consider changes of movements over time. Motivated by this, we introduce the notion of communities and propose a computational solution to discover them. The method is structured in three steps. The first step performs a feature extraction technique to elicit the inter-related movements between the objects. The second one leverages a tree-structure in order to group objects with similar inter-related movements. In the third step, these groupings are used to mine communities as groups of objects which exhibit inter-related movements over time. We evaluate our approach on real data-sets and compare it with existing algorithms
Project D.A.M.A.: Document Acquisition, Management and Archiving
No full textA paper document processing system is an information sys-
tem component which transforms information on printed or handwritten
documents into a computer-revisable form. In intelligent systems for pa-
per document processing this information capture process is based on
knowledge of the specific layout and logical structures of the documents.
In this project we design a framework which combines technologies for
the acquisition and storage of printed documents with knowledge-based
techniques to represent and understand the information they contain.
The innovative aspects of this work strengthen its applicability to tools
that have been developed for building digital libraries
A Multi-Language Comparison of Influences on Author Verification using Character N-Grams
No full textWe create a new multi-language corpus for author verification based on Wikipedia talkpages, and evaluate the influence that differences in topic and time have on character n-gram author profiles. Topic alignment between two texts is found to increase author verification precision, and an authors writing style is found to change over time, but not more significantly after 3 years than after 1 year.Information ArchitectureWISElectrical Engineering, Mathematics and Computer Scienc
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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