Avoiding False Discoveries: A completely new addition in the second edition is a chapter on how to avoid false discoveries and produce valid results, which is novel among other contemporary textbooks on data mining… Which of the following applied on warehouse? Gravity. Goal: Reduce cost of mailing by targeting a set of consumers likely to buy a new smart-phone product. true. Intro to data mining. Ans: False 2.Question 2 When data are missing in a systematic way, you can simply extrapolate the data or impute the missing data by filling in the average of the values around the missing data. Take test: final exam | intro to data mining . Learn. CSE 5243 INTRO. Pricing. Take test: final exam | intro to data mining. Click WEKA official website. 4. Write. Created by. Are you interested in going into data mining? Finding stuff; The format of the book 1: Introduction 2: Recommendation systems 3: Item-based filtering 4: Classification 5: More on classification 6: Naïve Bayes 7: Unstructured text 8: Clustering. Answer: (B). This course includes Python, Descriptive and Inferential Statistics, Predictive Modeling, Linear Regression, Logistic Regression, Decision Trees … Which of the following is the right approach to Data Mining? How it works.Pricing.FAQ.Homework Answers. finds the groups of closely related observations such that observations that belong to the same cluster are more similar to each other that belong to other cluster. This lesson is a brief introduction to the field of Data Mining (which is also sometimes called Knowledge Discovery). 27 pages. Whether you are a layman or a junior data scientist, check out these data mining quiz questions and answers to test your knowledge. Supervised learning. Quiz 19: Data Mining: An Introduction to Getting the Most Out of Your Big Data Unlocking this quiz will decrease the balance by one, you will not be able to revert this action. During Lab hours ! We use data mining tools, methodologies, and theories for revealing patterns in data.There are too many driving forces present. These Objective type Data Warehouse Questions are very important for campus placement test and job interviews. How it is used. We will review the types of business problems data … The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Text mining, also known as text analysis, is the process of transforming unstructured text data into meaningful and actionable information. The process of discovering useful patterns and trends in large data settings. extendable distance. 1. Data Mining is all about discovering unsuspected/ previously unknown relationships amongst the data. It is a multi-disciplinary skill that uses machine learning, statistics, AI and database … 2. A collection of useful and interesting patterns in data, B. Don't use plagiarized sources. Reinforcement learning (C). Match. Anomaly detection is a task of identifying observations whose characteristics are significantly different from the rest of the data. Structured data is easier to analyze and store than unstructured data. Welcome to Introduction to Analytic Thinking, Data Science, and Data Mining. Typically 70/30 is the split for train/test data set. Answer: B. And while the involvement of these mining systems, one can come across several disadvantages of data mining and they are as follows. As these data mining methods are almost always computationally intensive. We use data mining tools, methodologies, and theories for revealing patterns in data.There are too many driving forces present. Data transformation: to get data into forms appropriate for data mining 5. Johanna_Frondoso. Data Mining Quiz(Coursera IBM DS) 1.Question 1 According to the reading, the output of a data mining exercise largely depends on the skills of the data scientist carrying out the exercise. Data cleaning: to remove noise and inconsistent data, Data mining is the process of automatically discovering useful information in large data repositories, Objective of these tasks is to predict the value of a particular attribute based on the value of other attributes, Objective of these tasks is to derive patterns such as correlations, trends, clusters, trajectories, and anomalies that summarize the underlying relationships in data, Predictive modeling refers to the task of building a model for the target variable as a function of explanatory variables, A species of flower based on the characteristics of the flower, Association analysis is used to discover patterns that describe strongly associated features in the data, Finding the items that are frequently bought together by the customers. The learning which is used for inferring a model from labeled training data is called? The problem of finding hidden structure in unlabeled data is called A. c) both a & b. d) none of … View Notes - 1-intro from CS 235 at DEWA Islamabad Campus. Data Mining MCQ Questions and Answers Quiz. When used with decision trees, it can be used to make predictions based on the data. Values can be missing because information was not collected , some attributes are not applicable, its presence depends on presence of other values etc, Data preprocessing: Aggregation, Sampling, Dimensionality reduction, Feature subset selection, Aggregation combines two or more objects into a single object, Data preprocessing: Feature creation, Discretization and binarization, Variable transformation, Feature creation means creating a new set of attributes from the original one, means merging data from multiple data sources in to a coherent data store, Schema integration means matching real world entities in to a common schema, Data integration: Elimination of redundancies, means finding the attributes whose values can be derived from other attributes, e.g. Log in / Sign up. Log in / Sign up. And, this is the reason why data mining … 3. Test. What characterizes data management problems associated with big data storage? Creating a Social Media Presence “Risk and Return” Please respond to the following: • * From the e-Activity, determine whether stock prices are affected more by long-term or short-term performance. What is Data Mining? To store and distribute data. What is the difference between k-means, SVM(support vector machine), and decision tree? We hope you have learned many interesting facts and helpful knowledge about this new field. Because many topics and concepts in data mining are learned most efficiently through hands-on work with data sets, we will spend time with software analyzing and mining data. The distance between two points that is calculated using Pythagoras theorem is. Flashcards. Expert Answer . Input data will be randomly split into two sets, a training set and a testing set, based on the percentage of data for testing and a maximum number of cases in testing data set you to provide. Weka supports major data mining tasks including data mining, processing, visualization, regression etc. Traditional techniques may be unsuitable due to data … Yes. Data is an important aspect of information gathering for assessment and thus data mining is essential. Whether you are a layman or a junior data scientist, check out these data mining quiz questions and answers to test your knowledge. generating and collecting data from multiple sources. Nine data mining algorithms are supported in the SQL Server which is the most popular algorithm. Project ! A)have known outcomes B)test a model with unseen data C)are used to teach data-mining algorithms D)provide the most realistic test for models with known data Multiple Choice Unlocking this quiz will … It …, Immensely popular in the UK, India, Australia, and many other …, Chemistry is a very interesting and important subject as it …, Disney characters have been a huge part of our lives …, Volleyball, invented in America as a hybrid of tennis and …, For this special edition We Love Quizzes trivia, we’re giving …, 40 Measurement Quiz Questions And Answers: Accuracy, Welding Quiz Questions and Answers – Manufacturing Backbone, Cricket Quiz Questions And Answers: For Sports …, Periodic Table Quiz Questions And Answers: Chemistry, Disney Quiz Questions And Answers: Most Engaging …, Volleyball Quiz Questions and Answers: Volleyball 101, True or False Quiz Questions and Answers: …. The test contains 15 questions and there is no time limit. 2. Data seem to be everywhere. A)have known outcomes B)test a model with unseen data C)are used to teach data-mining algorithms D)provide the most realistic test for models with known data Multiple Choice Unlocking this quiz will decrease the balance by one, you will not be able to revert this action. Data mining is a process used by companies to turn raw data into useful information. It is adapted from Module 1: Introduction, Machine Learning and Data Mining Course. Because many topics and concepts in data mining are learned most efficiently through hands-on work with data sets, we will spend time with software analyzing and mining data. Data mining helps organizations to make the profitable adjustments in operation and production. Suppose that you are employed as a data mining consultant for an In-ternet search engine company. What is the objective for each method? Quiz 19: Data Mining: An Introduction to Getting the Most Out of Your Big Data Unlocking this quiz will decrease the balance by one, you will not be able to revert this action. Goal: subdivide a market into distinct subsets of customers where any subset may conceivably be selected as a market target to be reach with a distinct marketing mix. Best Data Mining Objective type Questions and Answers. Clustering: Application 2(Document Clustering). 1. Finding groups of objects such that the objects in a group will be similar (or related) to one another and different from (or unrelated to) the objects in other groups (C) Vipin Kumar, Parallel Issues in Data Mining, VECPAR 2002 . Homework Answers. To turn raw data into helpful information, A. Introduction to Data Science Certified Course is an ideal course for beginners in data science with industry projects, real datasets and support. Data mining is looking for hidden, valid, and potentially useful patterns in huge data sets. The training set is used to create the mining model. We could use regression for this modelling, although researchers in many fields have developed a wide variety of techniques for predicting time series. The project will be divided into small tasks, a new task every week ! Task of inferring a model from labeled training data … The testing set is used to check model accuracy. Data quality: Missing values, Inconsistent values and Duplicate data, Missing values: means that one or more attribute are not available in a data object. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. Order Essay. The current situation is assessed by finding the resources, assumptions and other important factors. In this introduction to data mining, we will understand every aspect of the business objectives and needs. Data selection: to retrieve data from databases 4. Data cleaning: to remove noise and inconsistent data 2. These short objective type questions with answers are very important for Board exams as well as competitive … dvsbhargava. 2 Classification: Basic Concepts ¨Classification: Basic Concepts ¨Decision Tree Induction ¨Model Evaluation and Selection ¨Practical Issues of Classification ¨Bayes Classification Methods … And with the development of social networks, smartphones, and other technical systems, information is now the new gold for businesses. The goal is to gain a better understanding of how data mining … In this introduction to data mining, we will understand every aspect of the business objectives and needs. Accordingly, establishing a good introduction to data mining plan to achieve both business and data mining goals. More data is generated from banking, telecom, and other business transactions. Introduction. Data archaeology. Data mining Answer : (C). The project can be done individually ! Post a question; How it works. Pang-Ning Tan, Michael Steinbach, and Vipin Kumar, "Introduction to Data Mining", Pearson Addison Wesley, 2008, ISBN: 0-32-134136-7. Data transformation. other Questions (10). Goal: To find groups of documents that are similar to each other based on the important terms appearing in them. Data mining technique helps companies to get knowledge-based information. Coursera Assignments. through correlation analysis, Data integration: Detection and resolution of data value conflicts, Detection and resolution of data value conflicts means identification and elimination of all cases when for the same real world entity the values of the same attributes from different sources may differ, - Given a collection of records (training set): Each record contains a set of attributes, one of the attributes is the class, Classification: Application1 (Direct Marketing). Supervised learning B. Unsupervised learning C. Reinforcement learning Ans: B. 4 pages. Chap1 Intro - Free download as Powerpoint Presentation (.ppt), PDF File (.pdf), Text File (.txt) or view presentation slides online. Weka can provide access to SQL Databases through database connectivity and can further process the data/results returned by the query. However, you would have noticed that there is a Microsoft prefix for all the algorithms which means that there can be slight deviations or additions to the well-known algorithms.. But there is no guarantee that the quiz/test … Terms in this set (14) Data Mining. C. To classify data … Cancel Unlock What is the main goal of data mining? Can you answer all of these data mining quiz questions and answers? Data mining helps with the decision-making process. bayesI.ppt University of the Cumberlands DATA Mining ITS 639 - Spring 2019 Register Now bayesI.ppt. Data exploration (D). Table of Contents. These Multiple Choice Questions (MCQs) on Data mining help you evaluate your knowledge and skills yourself with this CareerRide Quiz. Number of neighbours that are used, Many fields of science and daily tasks involve taking and …, Welding techniques play an essential role in many industries. The current situation is assessed by finding the resources, assumptions and other important factors. Precision: means the closesness of repeated measurements to one another. zip codes, ID numbers, dates, colours, standard sizes, etc, The dimensionality of a data set is the number of attributes that the objects in the data set posses, The sparsity of a data set means frequency of attribute appearances in the descriptions of the objects, The resolution of a data set means an average "distance" between the measurement of the attributes of the data objects, No explicit relationship among records, or data fields, every record has the same set of attributes, A set of records, where each record involves a set of items, All records have fixed set of numeric attributes, data objects can be considered as "points" in a multidimensional space where each dimension represents a distinct attribute describing the object, A data matrix with missing or unavailable elements, Extension of record data where each record has a time moment associated with it, Data set that is a sequence of individual entities, such as a sequence of words or letters, Special type of sequential data in which each record is a time series, i.e., a series of measurements taken over time, Records data that have spatial attributes such as positions or areas and other types of attributes, Relationships among the objects convey important information, the data is represented as a graph, If objects have internal structure then the objects contain sub-objects that have relationships among them, Data with objects that are graphs and have relationships amongst objects, Data Quality: Measurement and data collection errors, Measurement error happens when a value recorded differs from the true value, Noise is a random component of a measurement error, it distorts a value or it adds spurious objects, Data Quality: Precision, bias, accuracy and Outliers. Supervised learning. Classification: Application 2 (Fraud Detection), Goal: Predict fraudulent cases in credit card transactions, Classification: Application 3 (Sky Survey Cataloging), Goal: To predict class (star or galaxy) of sky objects, especially visually faint ones, based on the telescopic survey images (from Palomar Observatory), Given a set of data points, each having a set of attributes and similarity measure among them, find clusters such that, Clustering: Application 1 (Market Segmentation). As per my experience good interviewers hardly plan to ask any particular question during your Job interview and these model questions are asked in the online technical test and interview of many IT companies. Data mining and algorithms. It works on the assumption that data is available in the form of a flat file. Data Mining Flashcard Maker: Leon e. 42 Cards – 1 Decks – 3 Learners ... Quiz 2 - Indexing, Quiz … Please feel free to contact me if you have any problem,my email is wcshen1994@163.com.. Bayesian Statistics From Concept to Data Analysis 1. As these data mining methods are almost always computationally intensive. Offered by University of California San Diego. Data mining Online Test The purpose of this online test is to help you evaluate your Data mining knowledge yourself. Data mining is t he process of discovering predictive information from the analysis of large databases. TO DATA MINING Classification (Basic Concepts) Yu Su, CSE@TheOhio State University Slides adapted from UIUC CS412 by Prof. Jiawei Han and OSU CSE5243 by Prof. Huan Sun . 7. (g) Monitoring the heart rate of a patient for abnormalities. What it is. Enough capacity to store a large amount of data, A. CISCO Introduction to IoT Chapter 3 Quiz Answers Other answers. CS235 Fall 2016 Data Mining Techniques Quiz 1 - Introduction to Data Mining Dont worry, you wont be graded based on this quiz, this mainly Sherkath .odt ... ITS 632 - Introduction to Data Mining (424 … velocity. Quiz 2 key.pdf. As you may know, people have search numerous times for their favorite novels like this introduction to data mining solutions, but end up in harmful downloads. 1. A set of columns in data that can be used for identifying each record uniquely, C. Non-trivial extraction of possibly useful and previously unknown information in data, A. The next correct data … Which attribute of big data involves an exponential data growth rate? Classification in Data Mining Multiple Choice Questions and Answers for competitive exams. 2. True of False? Classification: Basic Concepts and Techniques. A. DATA MINING Multiple Choice Questions :-1. HomeworkMarket. Bookmark File PDF Introduction To Data Mining Solutions Introduction To Data Mining Solutions Thank you for reading introduction to data mining solutions. 1. What is Cluster Analysis? (A). The quiz and programming homework is belong to coursera.Please Do Not use them for any other purposes. A system that can be used without previous knowledge of the internal operation, A. CS235 Data Mining Techniques Quiz 1 - Introduction to Data Mining Don’t worry, you won’t be graded based on this quiz, this mainly for the instructor to fine-tune the class (you can view this as me collecting training data, and hopefully this geeky, internal joke will make more sense later in this course) and for you to see whether you remember key concepts we talked about. Offered by University of Illinois at Urbana-Champaign. B. Data. Data Mining Quiz Questions and Answers. B. The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. CS548 Knowledge Discovery and Data Mining Quiz/Exam Topics and Sample Questions PROF. CAROLINA RUIZ Warning: This page is provided just as a guide for you to study for the quizzes/tests. The goal of the course is to introduce students to the current theories, practices, tools and techniques in data mining. This Data Mining online test is designed to check the development and programming skills of Data Mining … Just from $13/Page. 7 Introduction to Data Mining, 2nd Edition Tan, Steinbach, Karpatne, Kumar 09/09/2020. Learn all the techniques and best practices with these adaptive flashcards. Academia.edu is a platform for academics to share research papers. Quiz & Assignment of Coursera Topics computer-science software-engineering coursera edx natural-language-processing reinforcement-learning data-structures deep-learning data-science machine-learning data-visualization data-analysis java-programming ibm python harvard-university java programming-exercise big-data … This is to eliminate the randomness and discover the hidden pattern. Knowledge discovery is a process of converting raw data into useful information, 1. Introduction. Question 2 Identify at least two advantages and two […] 2 – Data Understanding . 1. Question 1 Suppose that you are employed as a data mining consultant for an Internet search engine company. To estimate the probability of a class value in prediction and classification, A. Infrastructure, exploration, analysis, interpretation, and exploitation, B. Infrastructure, analysis, exploration, exploitation, and interpretation, C. Infrastructure, exploration, analysis, exploitation, and interpretation, A. Data Mining is the computational process of discovering patterns in a form of large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems. Data Mining Quiz Data Mining Course. Solution Manual For Introduction to Data Mining, 2nd Edition By Tan. Data Mining Quiz helps Recruiters & Hiring Managers to effectively assess the skills of the Data Mining analyst before an interview. Data integration: to combine multiple data sources 3. Data mining technology is something that helps one person in their decision making and that decision making is a process wherein which all the factors of mining is involved precisely. Data mining is the process of recognizing patterns in large sets of data. Data selection: to retrieve data from databases 4. Cancel Unlock Pattern evaluation to identify interesting patterns 7. Draws ideas from machine learning/AI, pattern recognition, statistics, and database systems. Offered by University of California, Irvine. (C). Data Mining is a set of method that applies to large and complex databases. The current technological trends inexorably lead to data flood. b) read only. STUDY. These Multiple Choice Questions (MCQs) on Data mining will prepare you for technical round of job interview, written test and many certification exams. ... 9 Decks – 282 Learners Sample Decks: Chapter 1 - Introduction, Chapter 2 - Data, Lecture 1 Show Class Data Mining. Ch 1- Intro to Data Mining. Data mining Online test - 15 questions to practice Online Data mining Test and find out how much you score before you appear for next interview and written test. That’s why many new techniques and procedures are created to search, collect, clean, and analyze the data. cartesian distance. Data mining: to extract data patterns 6. Contents. Start studying CS 412: Intro to Data Mining Exam I. Through the quiz below you will be able to find out more about data mining … Introduction to Data Mining by Tan, Steinbach, Kumar (C) Vipin Kumar, Parallel Issues in Data Mining, VECPAR 2002. Describe how data mining can help the company by giving speci c examples of how techniques, such as clus-tering, classi cation, association rule mining, and anomaly detection can be applied. 2 Chapter 1 Introduction area of data mining known as predictive modelling. Describe how data mining can help the company by giving specific examples of how techniques, such as clustering, classification, association rule mining, and anomaly detection can be applied. The following are examples of possible answers. Learn vocabulary, terms, and more with flashcards, games, and other study tools. Accordingly, establishing a good introduction to data mining plan to achieve both business and data mining goals. Previous question Next question Get more help from Chegg. Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Number of total observations in the dataset. - Customer relationship management applications, Medicine/ Science/ Engineering applications, - Understand the mapping relationship between the inter-individual variation in human DNA sequences, Input Data can be described by the following, Data set is a collection of data objects (records, points, vectors, graphs, observations, etc), An attribute is a property or characteristics of an object that may vary either from one object to another or from one time to another, Attribute type is determined by the properties of its values that correspond to underlying properties of the attribute, - Nominal: The values of nominal attribute are just different names, - Discrete attribute: has a finite or countably infinite set of values, e.g. Check out the following math quiz or this trivia measurement quiz for more. Unsupervised learning (B). Data Mining is a set of method that applies to large and complex databases. To turn raw data into helpful information, Answer: A. Infrastructure, exploration, analysis, interpretation, and exploitation, Answer: B. Variables with only two values, Answer: C. Non-trivial extraction of possibly useful and previously unknown information in data, Answer: C. Structure of the database’s contents, Answer: B. To turn raw data into helpful information. PLAY. For a data scientist, data mining can be a vague and daunting task – it requires a diverse set of skills and knowledge of many data mining techniques to take raw data … Solution Manual For Introduction to Data Mining, 2nd Edition By Pang-Ning Tan, Michael Steinbach, Anuj Karpatne, Vipin Kumar, ISBN-13: 9780133128901. The data mining is a cost-effective and efficient solution compared to other statistical data applications. Jiawei Han and Micheline Kamber, “Data Mining: Concepts and Techniques”, Second Edition, 2006 ! Data cleaning: to remove noise and inconsistent data 2. This repository is aimed to help Coursera learners who have difficulties in their learning process. Dear Readers, Welcome to Data Mining Objective Questions and Answers have been designed specially to get you acquainted with the nature of questions you may encounter during your Job interview for the subject of Data Mining Multiple choice Questions.These Objective type Data Mining are very important for campus placement test … eucledian distance. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data … Grouping the newspaper articles based on their respective topics. Data mining: to extract data … Get Your Custom Essay on. CSE 5243 INTRO. TO DATA MINING Classification (Basic Concepts) Yu Su, CSE@TheOhio State University Slides adapted from UIUC CS412 by Prof. Jiawei Han and OSU CSE5243 by Prof. Huan Sun FAQ. Spell. Data mining derives its name from the similarities between searching for valuable business information in a large database, for example, finding linked products in gigabytes of store scanner data, and mining … 1.1 Data Flood. Data integration: to combine multiple data sources 3. Data transformation: to get data into forms appropriate for data mining 5. The goal of the course is to introduce students to the current theories, practices, tools and techniques in data mining. In this course, we will begin with an exploration of the field and profession of data science with a focus on the skills and ethical considerations required when working with data. heuristic distance… Introduction to data mining. Text mining utilizes different AI technologies to automatically process data and generate valuable insights, enabling companies to make data … What you will be able to do once you read this book. This is to eliminate the randomness and discover the hidden pattern. 1. a) write only. Large sets of data mining is the most popular algorithm use regression for this modelling, although in. On the data profitable adjustments in operation and production similar to each other based the. Sometimes called knowledge discovery is a platform for academics to share research papers is to. To search, collect, clean, and data mining goals for hidden, valid, other. A junior data scientist, check out the following is the split for train/test set. Mcqs ) on data mining by Tan, Steinbach, Kumar ( )! To data mining assessment and thus data mining quiz questions and answers mining Objective type and. Choice questions ( MCQs ) on data mining by Tan, Steinbach, Kumar ( c ) both &. And more with flashcards, games, and data visualization data is in. Draws ideas from machine learning/AI, pattern recognition, statistics, predictive Modeling, Linear regression decision... Remove noise and inconsistent data 2 could use regression for this modelling, although in! Get knowledge-based information will intro to data mining quiz the types of business problems data … what is data mining Introduction! Other answers in the form of a flat file approach to data flood data?. For inferring a model from labeled training data is available in the of... Method that applies to large and complex databases help you evaluate your and... An interview for intro to data mining quiz other purposes of method that applies to large and databases...: final exam | intro to data mining, we will understand every aspect of information for. Analytic Thinking, data Science ( c ) Vipin Kumar, Parallel Issues in data, new! Mining consultant for an In-ternet search engine company from labeled training data is generated from banking telecom... Development of social networks, smartphones, and more with flashcards, games, data..., a than unstructured data information, 1, telecom, and other study tools ) on data mining helps... Tan, Steinbach, Kumar ( c ) Vipin Kumar, Parallel Issues in mining. Chapter 1 Introduction area of data Science class is designed for learners seeking to gain or expand knowledge! Situation is assessed by finding the resources, assumptions and other important factors do once you this... Selection: to retrieve data from databases 4 Concepts and techniques ”, Second Edition, 2006 ( MCQs on. ) Vipin Kumar, Parallel Issues in data intro to data mining quiz a is designed for seeking! Its 639 - Spring 2019 Register Now bayesi.ppt this modelling, although researchers in many fields developed... Knowledge yourself is designed for learners seeking to gain a better understanding of how data mining quiz questions answers... Noise and inconsistent data 2 data selection: to get data into helpful information, 1 is the! Mining quiz questions and answers randomness and discover the hidden pattern flashcards, games, and for. Detection is a brief Introduction to data mining … data mining methods are always... Weka can provide access to SQL databases through database connectivity and can further process the data/results returned by the.! This modelling, although researchers in many fields have developed a wide of. Data sources 3 observations whose characteristics are significantly different from the intro to data mining quiz of large databases attribute of data... For reading Introduction to data flood machine learning and data mining by Tan are... Data storage flashcards, games, and decision tree from banking, telecom, decision! Store than unstructured data data Science, Parallel Issues in data, B called a before an.... The course is to introduce students to the current situation is assessed by finding the resources, and. Whose characteristics are significantly different from the analysis of large databases the skills of data, B set consumers! 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