Data Mining: Introductory and Advanced Topics

By M. Dunham. 2002

1,932 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f6aa3d256c994a5950fe3262f7f18083d9b40ddd

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Citations in the corpus

Classifying the segmentation of customer value via RFM model and RS theory (2009, methodology): “The problem of mining association rule has firstly been stated in 1993 and is one of the most used tools to find the relationships among items (products) in large databases today (Dunham, 2003).”
Survey on Feature Selection (2015, background): “Clustering, on the other hand, is categorised by Dunham (2002) as a descriptive task.”
A survey on Data Mining approaches for Healthcare (2013, methodology): “Neural Network is used for classification and pattern recognition [58].”
A cosine maximization method for the priority vector derivation in AHP (2014, methodology): “There are several common similarity measures used in practice such as Dice similarity measure, Jaccard similarity measure, overlap similarity measure, and cosine similarity measure (Dunham, 2003).”
Comparison of segmentation algorithms for fluorescence microscopy images of cells (2011, methodology): “The commonly used Jaccard similarity index (32,39) which compares a reference data set with another set of estimates E is defined as: where 0 (cid:5) S (cid:5) 1 : For our purposes, T represents the pixels in a reference mask (‘‘truth’’) and E represents the pixels in a mask produced by a…”
Evaluation of Rule Extraction Algorithms (2014, methodology): “Although the RX algorithm is often cited, and even sometimes used as an example of typical rule extraction; see e.g. [11], it is not widely used in practice.”
A model for spectra-based software diagnosis (2011, methodology): “Jaccard, Dice, Overlap and a more general version of the Ochiai metric called Cosine have been used in the .eld of information retrieval [Dunham 2002].”
Document clustering using nonnegative matrix factorization (2006, methodology): “When the categories or topics for classification are predefined, the process of classification is considered supervised; there are several methods in use that satisfactorily automate the task of supervised classification [3].”
A taxonomy of sequential pattern mining algorithms (2010, background): “A trie [Dunham 2003] is a rooted tree, where root-leaf paths represent sequences.”
Performance Analysis of Naive Bayes and J 48 Classification Algorithm for Data Classification (2013, methodology): “NCAICN-2013, PRMITR,Badnera The experiments results shown in this paper are about classification accuracy, sensitivity and specificity.”
Data Mining in Healthcare and Biomedicine: A Survey of the Literature (2012, methodology): “Prediction data mining includes classification, regression, time series analysis, and prediction [ 31 ].”
An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification (2012, unknown): “It is defined as sim(i, j) = cos(i, j) = (vi vj)/(vi vj) (Dunham, 2003; Sarwar, Karypis, Konstan, & Riedl, 2001).”
Towards the Deployment of Machine Learning Solutions in Network Traffic Classification: A Systematic Survey (2019, unknown): “Different categorizations of the ML algorithms can be found [34]–[36].”