Web Usage Mining is the process of applying data mining techniques to the discovery of usage patterns from data extracted from Web Log files. It mines the secondary data (web logs) derived from the users' interaction with the web pages during certain period of Web sessions. Web usage mining consists of three phases, namely preprocessing, pattern discovery, and pattern analysis. In this paper, w...

The geometric approach to intra-opus pattern discovery (in which notes are represented as points in pitch-time space in order to discover repeated patterns within a piece of music) shows promise particularly for polyphonic music, but has attracted some criticism because: (1) the approach extends to a limited number of inexact repetition types only; (2) typically geometric pattern discovery algo...

Patterns are an essential part of music and there are many different algorithms that aim to discover them. Based on the improvements brought by using data fusion methods to find the consensus of algorithms on other MIR tasks, we hypothesize that fusing the output from musical pattern discovery algorithms will improve the pattern discovery results. In this paper, we explore two methods to combin...

This paper presents a method for pattern discovery based on viewpoints and feature set patterns. The representation for pattern components accommodates in a fully general way the taxonomic relationships that may exist between interval classes. A heuristic probabilistic hill climbing algorithm is developed to rapidly direct the search towards interesting patterns. The method can be used for sing...

The web resource Regulatory Sequence Analysis Tools (RSAT) (http://rsat.ulb.ac.be/rsat) offers a collection of software tools dedicated to the prediction of regulatory sites in non-coding DNA sequences. These tools include sequence retrieval, pattern discovery, pattern matching, genome-scale pattern matching, feature-map drawing, random sequence generation and other utilities. Alternative forma...

ÐIn this paper, a novel method of pattern discovery is proposed. It is based on the theoretical formulation of a contingency table of events. Using residual analysis and recursive partitioning, statistically significant events are identified in a data set. These events constitute the important information contained in the data set and are easily interpretable as simple rules, contour plots, or ...

The web is a large source of information that can be turned into knowledge. Part of this knowledge concerns the usage of the web itself and is invaluable to the organization of web sites that meet their purposes and prevent disorientation. Data mining is already being used to throw light in various aspects of web utilization. For one major aspect, the discovery of navigation patterns, we show t...

The focus of this article is on various approaches to discerning patterns in nonempty sets endowed with a proximity (nearness) relation. Patterns arise in repetitions of some form in the arrangement of the parts of a set. To simplify the steps leading to pattern discovery, an approach inspired by M. Katĕtov is used, where one proximitises certain parts of a nonempty set, rather than proximitise...

Pattern discovery has been the center of attention of data mining research for a long time, with patterns languages varying from simple to complex, according to the needs of the applications and the format of data. In this talk, I will take a view on pattern mining that combines elements from neighboring areas. More specifically, I will describe our previous research work in the intersection of...