mining cost patterns

Cost models for distributed pattern mining in the cloud ... - Hal

Jan 14, 2015 ... application to graph patterns. Sabeur Aridhi, Laurent D'Orazio, Mondher Maddouri, Engelbert Mephu. Nguifo. To cite this version: Sabeur Aridhi, Laurent D'Orazio, Mondher Maddouri, Engelbert Mephu Nguifo. Cost models for distributed pattern mining in the cloud: application to graph patterns. 2015.

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Mining Graph Patterns Efficiently via Randomized Summaries ∗

Mine is effective in cutting down the size of graphs, thus decreasing the embedding enumeration cost. However, com- pression might lose patterns at the same time. We address this issue by generating randomized summaries and repeat- ing the process for multiple rounds, where the main idea is that true patterns are...

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gPrune: A Constraint Pushing Framework for Graph Pattern Mining

Proofs are omitted due to space limit. 5 Mining Strategy Selection. The checking steps for pruning patterns and data are both associated with a computa- tional cost. Alternatively, one can first mine all frequent patterns by a known mining algorithm, gSpan [17] for example, then check constraints on every frequent pattern.

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Efficient Frequent Pattern Mining in Relational Databases

based data mining is known to fall behind spe- cialized implementation since the prohibitive na- ture of the cost associated with extracting knowl- edge, as well as the lack of suitable declara- tive query language support. We investigate ap- proaches based on SQL for the problem of find- ing frequent patterns from a...

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Direct Discriminative Pattern Mining for Effective ... - Jiawei Han

frequent patterns. The computational cost raised by the two-step framework motivates us to investigate an alternative approach: Instead of generating the complete set of frequent patterns, directly mine highly discriminative patterns for classification. This leads to our proposal of a direct discriminative pattern mining...

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Mining Frequent Patterns without Candidate Generation - Jiawei Han

It is tedious to repeatedly scan the database and check a large set of candidates by pattern matching, which is especially true for mining long patterns. Can one develop a method that may avoid candidate generation-and-test and utilize some novel data structures to reduce the cost in frequent-pattern mining? This is the...

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Multi-level Frequent Pattern Mining - Semantic Scholar

The basic idea here is to fuse the small core patterns of the colossal patterns in one step. With this approach, they reduce the cost of generating mid-sized patterns, which is the general technique adopted by Apriori and FP-growth. Generalized Sequential Patterns (GSP), an early algorithm in mining sequen- tial patterns...

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CP4IM: Constraint Programming for Itemset Mining - DTAI

Constraint programming for itemset mining, KDD 2008, we have shown that this is a viable approach for many pattern mining problems such as frequent, closed, cost-based itemset mining and more. An accessible introduction is available in T. Guns, S. Nijssen, L. De Raedt. Itemset mining: A constraint programming...

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Mining Frequent Co-occurrence Patterns across Multiple Data Streams

Aug 3, 2013 ... existing methods on mining frequent patterns requiring more than one pass over the data cannot be .... other hand, focus on mining patterns from a single stream where the frequent patterns are defined as ... improved in terms of memory consumption and maintenance cost. In the CooMine approach, we...

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TWINCLE : A Constrained Sequential Rule Mining Algorithm for ...

In this paper, motivated by the analysis of patient pathways in the health domain, a rich type of event logs, called activity-cost event logs, is considered where each event is associated with a cost. The paper formalizes the problem of mining interesting low-cost patterns in these logs by combining novel concepts of penalties...

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GO-SPADE: Mining Sequential Patterns over Datasets with ... - CNRS

containing consecutive repetitions at nearly no extra cost. Keywords: frequent sequential pattern mining, generalized oc- currences, SPADE. 1 Introduction. Mining sequential patterns is an active data mining domain dedicated to sequen- tial data. For example, customer purchases, Web log access, DNA sequences,.

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CP4IM: Constraint Programming for Itemset Mining - DTAI

Constraint programming for itemset mining, KDD 2008, we have shown that this is a viable approach for many pattern mining problems such as frequent, closed, cost-based itemset mining and more. An accessible introduction is available in T. Guns, S. Nijssen, L. De Raedt. Itemset mining: A constraint programming...

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Bitcoin Mining Decentralization via Cost Analysis - arXiv

Bitcoin Mining Decentralization via Cost Analysis. Jonathan Harvey-Buschel*, Can Kisagun+. *MIT EECS, +MIT Sloan. Abstract. Bitcoin mining presents a significant economic incentive for efficient hashing and broadcast of data, both parameters stemming from the Proofs-of-Work used to advance the network. This incentive...

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Mining frequent stem patterns from unaligned RNA sequences ...

Aug 14, 2006 ... In this paper, we propose a new method based on a graph mining algorithm in order to detect the motifs shared by a subset of the given RNA sequences. ..... Given a set of stem graphs, a label taxonomy, a minimum support minsup and a maximum cost maxcost, completely enumerate every stem pattern P...

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Comparing Approaches to Mining Source Code for Call-Usage ...

mining and the efficiency of itemset mining is investigated. The two approaches are applied to the. Linux kernel v2.6.14 and results show that mining ordered patterns is worth the additional cost. 1. Introduction. A function-call-usage pattern is a list or set of function calls found in the source code. Although many of these.

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Event Detection through Differential Pattern Mining in ... - Temple CIS

in terms of communication cost and detection quality compared to existing data mining schemes. Index Terms—Internet of things, wireless sensor, data mining, pattern mining, event detection, resource-efficiency. I. INTRODUCTION. With the capabilities of pervasive surveillance, Internet of Things (IoT) such as networked...

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Efficient mining of emerging patterns - ACM Digital Library

Roberto J. Bayardo, Jr., Efficiently mining long patterns from databases, Proceedings of the 1998 ACM SIGMOD international conference on Management of data, .... Rob M. Konijn , Wouter Duivesteijn , Marvin Meeng , Arno Knobbe, Cost-Based Quality Measures in Subgroup Discovery, Revised Selected Papers of PAKDD...

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Sequential pattern mining - Wikipedia

Retailers can not only increase their profit but, also decrease cost by proper management of shelf space allocation and products display. To solve this problem, George and Binu (2013) have proposed an approach to mine user buying patterns using PrefixSpan algorithm and place the products on shelves based on the...

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How digital innovation can improve mining productivity | McKinsey ...

In manufacturing, the cost of industrial robots has fallen by 50 percent since 1990, while US labor costs have risen 80 percent over the same period. ... The integration of geological information into one better, universal source of truth helps optimize drill and blast patterns, create an executable mine plan, and avoid quality...

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Mining Top-K Patterns from Binary Datasets in presence of Noise ...

In this paper we formalize the problem of discovering the Top-K patterns from binary datasets in presence of noise, as the minimization of a novel cost function. According to the Minimum Description Length principle, the proposed cost function favors succinct pattern sets that may approximately describe the input data.

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Sequential pattern mining - Wikipedia

Retailers can not only increase their profit but, also decrease cost by proper management of shelf space allocation and products display. To solve this problem, George and Binu (2013) have proposed an approach to mine user buying patterns using PrefixSpan algorithm and place the products on shelves based on the...

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How digital innovation can improve mining productivity | McKinsey ...

In manufacturing, the cost of industrial robots has fallen by 50 percent since 1990, while US labor costs have risen 80 percent over the same period. ... The integration of geological information into one better, universal source of truth helps optimize drill and blast patterns, create an executable mine plan, and avoid quality...

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Mining Top-K Patterns from Binary Datasets in presence of Noise ...

In this paper we formalize the problem of discovering the Top-K patterns from binary datasets in presence of noise, as the minimization of a novel cost function. According to the Minimum Description Length principle, the proposed cost function favors succinct pattern sets that may approximately describe the input data.

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10 Ways Data Mining Can Help You Get a Competitive Edge

Typically, professionals mine credit card data to find patterns that might suggest fraud, but the data is also used to tailor cards around a variation of credit limits, terms and interest rates…and even ... Pricing – Database mining can also help you determine the best price for your products as you uncover customer sensitivity.

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Approaches for Pattern Discovery Using Sequential Data Mining

small projected sequence databases based on the currently mined frequent sets, the subsequent mining is confined to each projected database relevant to a smaller set of candidates. The major cost of FreeSpan is to deal with projected databases. If a pattern appears in each sequence of a database, its projected database...

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Data Mining For Beginners Using Excel - Cogniview- Using Excel As ...

Apr 2, 2013 ... What is data mining? Do you have to be a mathematical genius to find patterns in hidden data? Most software programs for data mining cost thousands of dollars, but there is one program sitting on your desktop that makes a perfect data mining tool for beginners: Excel. Data Mining Predictions.

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Mining top-K large structural patterns in a massive network ...

With the spider structure, our approach adopts a probabilistic mining framework to find the top-k largest patterns by (i) identifying an affordable set of promising growth paths toward large patterns, (ii) generating large patterns with much lower combinatorial complexity, and finally (iii) greatly reducing the cost of graph...

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DynaMine: Finding Common Error Patterns by Mining Software ...

coding patterns. Potential patterns discovered through mining are passed to a dynamic analysis tool for validation; finally, the results of dynamic analysis are presented to the user. .... an informal description of DynaMine, our pattern mining and er- ..... Because the incremental cost of checking for additional patterns.

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In Situ Leach Mining (ISL) of Uranium - World Nuclear Association

In USA ISL is seen as the most cost effective and environmentally acceptable method of mining, and other experience supports this. ... Whatever the type of pattern used, there is a mixture of injection wells, to introduce the leach solution to the orebody, and extraction wells with submersible pumps used to deliver pregnant...

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Mining patterns for clustering using unsupervised decision trees ...

Pattern-based clustering algorithms return a set of patterns that describe the objects grouped in each cluster. The most recent algorithms proposed in this approach have a high computational cost in the clustering stage, making them non suitable when a huge amount of patterns are extracted from a dataset. In this paper, we...

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Mining | Britannica.com

Obviously, the opposite is also true, and a mine may cease production because (1) the mineral is exhausted or (2) the prices have dropped or costs risen so much that ... Apparently, the first mineral used was flint, which, because of its conchoidal fracturing pattern, could be broken into sharp-edged pieces that were useful as...

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Reviews for Pattern Discovery in Data Mining from Coursera | Class ...

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some...

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Use of Data-Mining to Perform a Real World Cost ... - Value in Health

the direct medical costs of HER2-positive breast cancer (BC) treatment in Iran and the fraction of total costs from trastuzumab use. METHODS: Data from 21/03/2011-. 20/03/2014 were examined using data-mining to determine clinical stages. R-based classification algorithms were designed based on medication patterns...

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50 Data Mining Resources: Tutorials, Techniques and More - NGData

Jan 12, 2018 ... Mining frequent patterns, associations, and correlations; Advanced data, information systems, and advanced applications; Integrating a data mining system with a database or data warehouse system. Cost: FREE. 19. Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling...

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Phoenix Mining Math - Pickaxes and Patterns - Survival Mode ...

NEW* I have calculated a conversion rate for iron->iron, iron->diamond, diamond->iron, and diamond->diamond based off of cost to make a pickaxe vs average ...

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Dominance Programming for Itemset Mining - EU FET-Open ...

Relevant pattern mining is not an isolated case. Many other pattern mining settings can not be formalized adequately using conjunctions of constraints. Bonchi and Lucchese [10] have shown that combinations of closedness and monotonic constraints such as the max-cost constraint can lead to am- biguous problem...

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Text and Data Mining - RightsDirect

Researchers use text mining to extract assertions, facts and relationships from text, for purposes of identifying patterns or relations between items that would ... protein interactions that eventually leads to the development of a new drug, or maybe a subtle shift in weather patterns that predicts a downturn in the price of wheat.

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3 Technologies in Exploration, Mining, and Processing ...

The costs of mine closure and reclamation of the site now constitute a significant portion of mining cost. Hence, ore bodies that can be mined in a way that produces virtually no waste and that leaves a small surface “footprint” may have distinct economic and environmental advantages over ore bodies that produce large...

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Chapter 74 - Mining and Quarrying

... and restructuring are each putting pressure on mining companies to reduce their costs and increase their productivity. The high capital intensity of much of the mining industry encourages mining companies to seek the maximum use of their equipment, calling in turn for more flexible and often more intensive work patterns.

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Non-communicable disease risk factor patterns among mining ...

Non-communicable disease risk factor patterns among mining industry workers in Papua, Indonesia: longitudinal findings from the Cardiovascular Outcomes in a .... (LMICs).3 Without appropriate action to reduce NCD risk, the numbers will only continue to rise, imposing major human, social and economic costs.4–6.

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