Search results for "Mining"

Reentry devices for chronic arterial occlusions.

2019

Over 30% of patients with splenic marginal zone lymphoma express the same immunoglobulin heavy variable gene: ontogenetic implications.

2012

We performed an immunogenetic analysis of 345 IGHV-IGHD-IGHJ rearrangements from 337 cases with primary splenic small B-cell lymphomas of marginal-zone origin. Three immunoglobulin (IG) heavy variable (IGHV) genes accounted for 45.8% of the cases (IGHV1-2, 24.9%; IGHV4-34, 12.8%; IGHV3-23, 8.1%). Particularly for the IGHV1-2 gene, strong biases were evident regarding utilization of different alleles, with 79/86 rearrangements (92%) using allele *04. Among cases more stringently classified as splenic marginal-zone lymphoma (SMZL) thanks to the availability of splenic histopathological specimens, the frequency of IGHV1-2*04 peaked at 31%. The IGHV1-2*04 rearrangements carried significantly lo…

Evolving Tree Algorithm Modifications

2007

There are many variants of the original self-organizing neural map algorithm proposed by Kohonen. One of the most recent is the Evolving Tree, a tree-shaped self-organizing network which has many interesting characteristics. This network builds a tree structure splitting the input dataset during learning. This paper presents a speed-up modification of the original training algorithm useful when the Evolving Tree network is used with complex data as images or video. After a measurement of the effectiveness an application of the modified algorithm in image segmentation is presented.

Mining Landscapes in Sicily: Problems, Strategies and Perspectives

2015

Sicily has been characterised by a striking mining activity throughout the 19th and 20th centuries. It deeply changed the appearance of the internal areas of the Island, transforming natural and agricultural landscapes into industrial ones. When the extraction activities finally came to an end, the industrial landscape started to be regarded from another point of view, as a cultural and touristic value. However, mining landscape is today a wasted opportunity. Large parts of machines, railways and chimneys are disappearing due to carelessness and abandonment. Anyway, the crisis which is affecting Europe will eventually force us to look back at these territories as a possible resource to over…

An overview of incremental feature extraction methods based on linear subspaces

2018

Abstract With the massive explosion of machine learning in our day-to-day life, incremental and adaptive learning has become a major topic, crucial to keep up-to-date and improve classification models and their corresponding feature extraction processes. This paper presents a categorized overview of incremental feature extraction based on linear subspace methods which aim at incorporating new information to the already acquired knowledge without accessing previous data. Specifically, this paper focuses on those linear dimensionality reduction methods with orthogonal matrix constraints based on global loss function, due to the extensive use of their batch approaches versus other linear alter…

Using PageRank for non-personalized default rankings in dynamic markets

2017

Abstract Default ranking algorithms are used to generate non-personalized product rankings for standard consumers, for example, on landing pages of online stores. Default rankings are created without any information about the consumers’ preferences. This paper proposes using the product centrality ranking algorithm (PCRA), which solves some problems of existing default ranking algorithms: Existing approaches either have low accuracy, because they rely on only one product attribute, or they are unable to estimate ranks for new or updated products, because they use past consumer behavior, such as previous sales or ratings. The PCRA uses the PageRank centrality of products in a product dominat…

Analysis and design of sequencing rules for car sequencing

2009

Abstract This paper presents novel approaches for generating sequencing rules for the car sequencing (CS) problem in cases of two and multiple processing times per station. The CS problem decides on the succession of different car models launched down a mixed-model assembly line. It aims to avoid work overloads at the stations of the line by applying so-called sequencing rules, which restrict the maximum occurrence of labor-intensive options in a subsequence of a certain length. Thus to successfully avoid work overloads, suitable sequencing rules are essential. The paper shows that the only existing rule generation approach leads to sequencing rules which misclassify feasible sequences. We …

A Two-layer Partitioning for Non-point Spatial Data

2021

Non-point spatial objects (e.g., polygons, linestrings, etc.) are ubiquitous and their effective management is always timely. We study the problem of indexing non-point objects in memory. We propose a secondary partitioning technique for space-oriented partitioning indices (e.g., grids), which improves their performance significantly, by avoiding the generation and elimination of duplicate results. Our approach is novel and of a high impact, as (i) it is extremely easy to implement and (ii) it can be used by any space-partitioning index. We show how our approach can be used to boost the performance of spatial range queries. We also show how we can avoid performing the expensive refinement s…

ExtMiner : Combining multiple ranking and clustering algorithms for structured document retrieval

2006

This paper introduces ExtMiner, a platform and potential tool for information management in SMEs (small & medium-size enterprise), or for organizational workgroups. ExtMiner supports interactive and iterative clustering of documents. It provides users with a visual cluster and list views at the same time, supporting iterative search process. ExtMiner may also be applied as a platform for research on retrieval fusion, since it combines search, clustering and visualization algorithms. ExtMiner was evaluated with three document collections. Although the findings were encouraging the user interface and performance with large document repositories need further development. peerReviewed

An approach based on the Adaptive Resonance Theory for analysing the viability of recommender systems in a citizen Web portal

2007

This paper proposes a methodology to optimise the future accuracy of a collaborative recommender application in a citizen Web portal. There are four stages namely, user modelling, benchmarking of clustering algorithms, prediction analysis and recommendation. The first stage is to develop analytical models of common characteristics of Web-user data. These artificial data sets are then used to evaluate the performance of clustering algorithms, in particular benchmarking the ART2 neural network with K-means clustering. Afterwards, it is evaluated the predictive accuracy of the clusters applied to a real-world data set derived from access logs to the citizen Web portal Infoville XXI (http://www…