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The mining sequence

  • Approaching Process Mining with Sequence Clustering

    Abstract. Sequence clustering is a technique of bioinformatics that is used to discover the properties of sequences by grouping them into clusters and assigning each sequence to one of those clusters. In business process mining, the goal is also to extract sequence

  • Improving Marketing Interactions by Mining Sequences

    Improving Marketing Interactions by Mining Sequences Ritwik Sinha1,SanketMehta1(B), Tapan Bohra2, and Adit Krishnan3 1 Big Data Intelligence Lab, Adobe Research, Bangalore, India {risinha,samehta}@adobe2 Georgia Institute of Technology, Atlanta, GA, USA [email protected] 3 IIT Madras, Chennai, India [email protected] Abstract. The advent of digital marketing has

  • Efficient Mining of Outlying Sequence Patterns for

    Aug 05, 2020· In this article, we study the problem of mining outlying sequence patterns in sequence data addressing the question: given a query sequence s in a sequence dataset D, the objective is to discover sequence patterns that will indicate the most unusualness (i.e., outlierness) of s compared against other sequences.

  • Sequence Mining My Browsing History with arulesSequences

    Nov 01, 2020· The sequence mining algorithm can be run by using the cspade() function in the arulesSequences package. Before running the algorithm, Ill need to explain the concept of support. Support can be best thought of as the proportion of sessions that contain a certain URL. Why thats important is that the cSPADE algorithm works recursively to

  • 5.1. Sequential Pattern and Sequential Pattern Mining

    So, this one is a subsequence of this longer sequence. Then, sequential pattern mining, the sequential pattern essentially is if you set a support, like a minimum support is 2, that means, at least 2 sequences contain the subsequence. You find those subsequence, this is a sequential pattern. For example, ab getting together then c, in this

  • Simulation Research for the Influence of Mining Sequence

    Mar 30, 2021· According to existing highwall mining methods, the mining sequence has a great influence on highwall stability. Based on a highwall mining project in Australia, this study adopted the FLAC 3D numerical simulation method to investigate the stability of coal pillars with different mining sequences.

  • An Introduction to Sequential Rule Mining The Data

    Aug 18, 2015· The goal of pattern mining is to discover useful, novel and/or unexpected patterns in databases. In this blog post, we will be interested by a specific type of database called sequences databases. A sequence database contains some sequences. For example, consider the

  • Sequence Mining - an overview ScienceDirect Topics

    Sequence mining has already proven to be quite beneficial in many domains such as marketing analysis or Web click-stream analysis. A sequence s is defined as a set of ordered items denoted by s 1, s 2, , s n . In activity recognition problems, the sequence is typically ordered using timestamps.

  • 5.4 mining sequence patterns in biological data

    May 07, 2015· 5.4 mining sequence patterns in biological data 1. Mining Sequence Patterns in Biological data 1 2. Bioinformatics Applies Computer Technology in Molecular biology Develops algorithms and methods to manage and analyze biological data Effective methods are needed to compare and align biological sequences and discover sequential patterns Type of data DNA: helix

  • Sequence Pattern Mining Based on Markov Chain

    Frequent sequence mining is one of the main challenges in data mining and especially in large databases, which consist of millions of records. There is a number of different applications where

  • Analysis of the Impacts of Mining Sequence and Overburden

    Feb 02, 2021· The validated model was used to compare changes in mining sequence, overburden depth, and the in situ stress field. This will allow mine operators and engineers to have a better idea of the conditions that could be encountered as mining progresses.

  • Description of mining methods (step by step)

    Primary Mining Method Sequential grid down dip. Information. To deal with ground pressures, a V-shaped mining sequence is utilized. The main advantages of the sequential down dip method are the very low energy release rates, which make backfilling unnecessary, and the allowance for the physical separation of rock transport from men and materials.

  • Sequence Data Mining - Lagout

    sequence data mining has developed rapidly, producing a diversified array of concepts, techniques and algorithmic tools. The purpose of this book is to provide, in one place, a concise introduction to the field of sequence data mining, and a fairly comprehensive overview of

  • Collaborative Mining Sequence Optimization for Multiple

    Apr 01, 2021· The optimization of a mining sequence not only reduces stress concentration in surrounding rock but also prevents underground debris flows, significantly improving safety.

  • Mind the Gap: Large-Scale Frequent Sequence Mining

    data mining, frequent sequence mining, MapReduce 1. INTRODUCTION Frequent sequence mining (FSM) is a fundamental com-ponent in a number of important data mining tasks. In text mining, for example, frequent sequences can be used to construct statistical language models for machine trans-lation [17], information retrieval [32], information extrac-

  • 5.3 mining sequential patterns - SlideShare

    May 07, 2015· 5.3 mining sequential patterns 1. Mining Sequential Patterns 1 2. Sequential Pattern Mining Sequence database consists of sequences of ordered elements or events (with or without time) Sequential Pattern Mining is the mining of frequently occurring ordered events or subsequences as patterns Example: Customer shopping sequences: First buy computer, then CD-ROM, and then

  • Sequence data mining - IIT Bombay

    sequences of discrete multi-attribute records. Existing literature on sequence mining is partitioned on application-specific boundaries. In this article we distill the basic operations and techniques that are common to these applications. These include conventional mining operations like classification and clustering and sequence spe-

  • Sequential Pattern Mining

    Mining GSP (Generalized Sequential Pattern) mining algorithm Outline of the method Initially, every item in DB is a candidate of length-1 for each level (i.e., sequences of length-k) do scan database to collect support count for each candidate sequence generate candidate length-(k+1) sequences from length-k

  • Part 2 Mining Patterns in Sequential Data

    Sequential Pattern Mining: Definition P. Singer, F. Lemmerich: Analyzing Sequential User Behavior on the Web ^Given a set of sequences, where each sequence consists of a list of elements and each element consists of a set of items, and given a user-specified min_support threshold, sequential pattern mining is to find all of

  • What Is Sequence Mining? (with pictures) - EasyTechJunkie

    Feb 11, 2021· Sequence mining is a type of structured data mining in which the database and administrator look for sequences or trends in the data. Sequence mining can be broken into two categories. Itemset mining is used in marketing and

  • Mining sequences with similarity to XTH genes in the

    The xyloglucan endotransglucosylase/hydrolase (XTH) genes in Arabidopsis thaliana (L.) Heynh. form part of a group of mechano-stimulated genes and play an important role in abiotic stress tolerance. Mining the RNAseq transcriptomic database of 40,430 potato (Solanum tuberosum L.) genes based on functional annotation and homology search, our objective was to discover potentially homologous XTH

  • Deterministic Pattern Mining On Genetic Sequences

    Deterministic Pattern Mining On Genetic Sequences: 10.4018/978-1-60566-766-9013: The recent increase in the number of complete genetic sequences freely available through specialized Internet databases presents big challenges for the

  • Mining sequence data in R with the TraMineR package: A

    TraMineR is a R-package for mining and visualizing sequences of categorical data. Its primary aim is the knowledge discovery from event or state sequences describing life courses, although most of its features apply also to non temporal data such as text or DNA sequences for instance. The

  • Mining Stream, Time-Series, and Sequence Data

    by discussing the mining of stream, time-series, and sequence data. Chapter 9 focuses on the mining of graphs, social networks, and multirelational data. Chapter 10 examines mining object, spatial, multimedia, text, and Web data. Research into such mining is fast evolving. Our discussion provides a broad introduction. We expect that many new books

  • CS6220: Data Mining Techniques

    November 16, 2014 Data Mining: Concepts and Techniques 15 GSPGeneralized Sequential Pattern Mining GSP (Generalized Sequential Pattern) mining algorithm proposed by Agrawal and Srikant, EDBT96 Outline of the method Initially, every item in DB is a candidate of length-1 for each level (i.e., sequences of length-k) do scan database to collect support count for each candidate

  • Mining - Wikipedia

    Mining is the extraction of valuable minerals or other geological materials from the Earth, usually from an ore body, lode, vein, seam, reef, or placer deposit.These deposits form a mineralized commodity that is of economic interest to the miner. Ores recovered by mining include metals, coal, oil shale, gemstones, limestone, chalk, dimension stone, rock salt, potash, gravel, and clay.

  • Mineral Exploration and Mining Sequence

    Throughout the mining sequence, projects require numerous permits, authorizations and licences. Federal, provincial and territorial governments must also ensure the Crowns legal obligations regarding Indigenous peoples are met.

  • Identifying Optimal Mining Sequences for Continuous

    Predicted Optimal Mining Sequence for Day 12Actual Mining Sequence for Day 12 . Application Case Study . Application Case Study . Application Case Study Day AMS OMS Difference Cuts Feet Mined CCT (min) Cuts Feet Mined CCT (min) Cuts Feet Mined CCT (min) 1 17 276 590 18 252 596 +1 -24 +6

  • Analysis of the Impacts of Mining Sequence and Overburden

    Feb 02, 2021· The validated model was used to compare changes in mining sequence, overburden depth, and the in situ stress field. This will allow mine operators and engineers to have a better idea of the conditions that could be encountered as mining progresses.

  • Sequence Mining My Browsing History with arulesSequences

    The sequence mining algorithm can be run by using the cspade() function in the arulesSequences package. Before running the algorithm, Ill need to explain the concept of support. Support can be best thought of as the proportion of sessions that contain a certain URL. Why thats important is that the cSPADE algorithm works recursively to

  • 6 Stages of the Mining Process BOSS Magazine

    Jun 22, 2018· Mining has been a vital part of American economy and the stages of the mining process have had little fluctuation. However, the process of mining for ore is intricate and requires meticulous work procedures to be efficient and effective. This is why we have broken down the mining process into six comprehensive steps.

  • 1.1 PHASES OF A MINING PROJECT

    The first way in which proposed mining projects differ is the proposed method of moving or excavating the overburden. What follows are brief descriptions of the most common methods. 1.1.3.1 Open-pit mining Open-pit mining is a type of strip mining in which

  • Machine Learning 9: 'Sequential Rule Mining'

    Jun 24, 2018· Sequential Rule Mining is a data mining technique which consists of discovering rules in sequences. Sequential Rule Mining has many applications for example for analysing the behaviour of

  • Sequence Mining.pdf - Sequence Mining 01 Introduction

    Sequential Pattern Mining Ƭ Sequence database consists of sequences of ordered elements or events (with or without time) Ƭ Sequential Pattern Mining is the mining of frequently occurring ordered events or subsequences as patterns Ƭ Example: Ɣ Customer shopping sequences: Ŷ First buy computer, then CD-ROM, and then digital camera, within 3 months. Ŷ Web access patterns, Weather

  • Mining frequent pyramid patterns from time series

    Jan 01, 2021· The core idea of the existing sequential pattern mining algorithms is identifying the item sets with high frequency by using uniform criteria (He, Zhang, Wu, 2019, Huang, Chen, Wang, Chen, 2000, Pei, Han, Mortazavi-Asl, Pinto, Hsu, 2001, Shyur, Jou, Chang, 2013, Wu, Tong, Zhu, Wu, 2017).

  • PrefixSpan: Mining Sequential Patterns Efficiently by Prefix

    The sequential pattern mining problem was first intro-duced by Agrawal and Srikant in [2]: Given a set of se-quences, where each sequence consists of a list of elements and each element consists of a set of items, and given a user-specified min support threshold, sequential pattern mining is to find all of the frequent subsequences, i.e., the

  • Sequential Pattern Mining - Computer Science

    Sequence Databases and Sequential Pattern Analysis (Temporal) order is important in many situations Time-series databases and sequence databases Frequent patterns (frequent) sequential patterns Applications of sequential pattern mining Ct h iCustomer shopping sequences: First buy computer, then CD-ROM, and then digital camera, within 3 months.

  • Glossary of Mining Terms - SEC

    Continuous miner - A piece of mining equipment which produces a continuous flow of ore from the working face. Controlled blasting - Blasting patterns and sequences designed to achieve a particular objective. Cast blasting, where the muck pile is cast in a particular direction, and deck blasting, where holes are loaded once but blasted in

  • Mines and Minerals Ministry of Energy, Northern

    Nov 04, 2020· Here you will find information and resources on all stages of the mining sequence, as well as requirements for mineral exploration and development in Ontario, from prospecting to early and advanced development, to production and closure. Read more. Geology.

  • Identifying Optimal Mining Sequences for Continuous Miners

    Predicted Optimal Mining Sequence for Day 12Actual Mining Sequence for Day 12 . Application Case Study . Application Case Study . Application Case Study Day AMS OMS Difference Cuts Feet Mined CCT (min) Cuts Feet Mined CCT (min) Cuts Feet Mined CCT (min) 1 17 276 590 18 252 596 +1 -24 +6

  • Sequence Mining - Rensselaer Polytechnic Institute

    260 Sequence Mining Given a database D ={s 1,s 2,,s N} of N sequences, and given some sequence r, thesupport ofr in thedatabaseD is definedas thetotalnumber of sequencesin D that contain r sup(r)= s i Drs i #!!! The relative support of r is the fraction of sequences that contain r rsup(r)=sup(r)/N Given a user-specified minsup threshold, we say that a sequence r is frequent in


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