Mining Rank Data
نویسندگان
چکیده
This paper addresses the problem of mining rank data, that is, data in the form of rankings (total orders) of an underlying set of items. More specifically, two types of patterns are considered, namely frequent subrankings and dependencies between such rankings in the form of association rules. Algorithms for mining patterns of this kind are proposed and illustrated on three case studies.
منابع مشابه
A new approach based on data envelopment analysis with double frontiers for ranking the discovered rules from data mining
Data envelopment analysis (DEA) is a relatively new data oriented approach to evaluate performance of a set of peer entities called decision-making units (DMUs) that convert multiple inputs into multiple outputs. Within a relative limited period, DEA has been converted into a strong quantitative and analytical tool to measure and evaluate performance. In an article written by Toloo et al. (2009...
متن کاملBalancing Interpretability and Predictive Accuracy for Unsupervised Tensor Mining
The PARAFAC tensor decomposition has enjoyed an increasing success in exploratory multi-aspect data mining scenarios. A major challenge remains the estimation of the number of latent factors (i.e., the rank) of the decomposition, which yields high-quality, interpretable results. Previously, we have proposed an automated tensor mining method which leverages a well-known quality heuristic from th...
متن کاملGeneralized Matrix Factorizations as a Unifying Framework for Pattern Set Mining: Complexity Beyond Blocks
Matrix factorizations are a popular tool to mine regularities from data. There are many ways to interpret the factorizations, but one particularly suited for data mining utilizes the fact that a matrix product can be interpreted as a sum of rank-1 matrices. Then the factorization of a matrix becomes the task of finding a small number of rank-1 matrices, sum of which is a good representation of ...
متن کاملA New Approach for Mining Top-Rank-k Erasable Itemsets
Erasable itemset mining first introduced in 2009 is an interesting variation of pattern mining. The managers can use the erasable itemsets for planning production plan of the factory. Besides the problem of mining erasable itemsets, the problem of mining top-rank-k erasable itemsets is an interesting and practical problem. In this paper, we first propose a new structure, call dPID_List and two ...
متن کاملParameter-Tuned Data Mining: A General Framework
Real-world data mining applications often confront us with complex and noisy data, which makes it necessary to optimize the data mining models thoroughly to achieve high-quality results. We describe in this contribution an approach to tune the parameters of the model and the feature selection conjointly. The aim is to use one framework to solve a variety of tasks. We show that tuning is of larg...
متن کامل