CSE 572 Data Mining Huan Liu CSE CEAS

CSE 572 Data Mining Huan Liu, CSE, CEAS, ASU http: //www. public. asu. edu/~huanliu/DM 05 S/cse 572. html 12/13/2021 CSE 572: Data Mining by H. Liu 1

CSE 591 Contents of basic and advanced topics Classification, Clustering, Association, and Applications Format - A semi-seminar course with a lot of assignments and Work Paper reading, discussion, project, presentation Assessment Class participation, assignments, project proposal, presentations, exam(s) 12/13/2021 CSE 572: Data Mining by H. Liu 2

You TA: Yin Ding, yin. ding@asu. edu Me: Huan Liu, huanliu@asu. edu n n Where: Brickyard 566 When: see on the class website, or by appointment “No pain, no gain” – if you cannot commit your time to this class, think again if you should take it My. ASU will be used, so make sure your email address is correct & won’t miss important announcement 12/13/2021 CSE 572: Data Mining by H. Liu 3

Course Format An experiment since Fall 2000 about effective teaching of graduate data mining Research papers - the main categories to be found on the course web site You can choose one of the textbooks listed. A reference list is an entering point for you to access related subjects Everyone is expected to read research papers and participate in class discussion Selected research paper presentation Project presentations will be evaluated during presentation 12/13/2021 CSE 572: Data Mining by H. Liu 4

Point distribution (tentative) Projects (30%) Reading/presentation assignment (10%) Exam(s) (40%) Assignments (20%), and class participation, quizzes (up to 10% extra credit) Late penalty, YES, increased expoentially. Academic integrity (http: //www. public. asu. edu/~huanliu/conduct. html) 12/13/2021 CSE 572: Data Mining by H. Liu 5

Research paper reading Each group will be responsible to select one paper and find additional different papers based on the group size (3 – 4 students each group) All are expected to search for and read the selected papers. n n n What is it about (e. g. , key idea, basic algorithm)? What are points to discuss and improve? What can we do with it? What to submit? (see more on the class website) n n n A brief report that describes the above and 2 questions suitable for quizzes/tests with solutions A set of presentation slides for 20 minutes Due date: 2/11 Friday, midnight, use digital drop box The grade will be given based on (1) quality of additional papers, (2) slides for presentation, (3) the report, and (4) oral presentation will be selected among the best submissions and presenters will be given extra credit based on presentation Earliest presentation will likely start from 2/17/04 12/13/2021 CSE 572: Data Mining by H. Liu 6

Project Proposal n n Proposal presentation, discussion, revision A project that can be completed in a semester Project n Class presentation and/or demo Report One key goal of this course is to take advantage of your intelligence and experience to create something useful and with impact 12/13/2021 CSE 572: Data Mining by H. Liu 7

Topic Distribution (tentative) 12/13/2021 CSE 572: Data Mining by H. Liu 8

Categories of interests (including design and implementation) 1. Data and application security Data mining and privacy 2. Data reduction and selection Streaming data reduction Dealing with large data (column- & row-wise) Selection bias 3. Learning algorithms Ensemble methods Incremental learning Active learning and co-training 4. Bioinformatics for CBS 598 or others w 12/13/2021 A discussion board was created CSE 572: Data Mining by H. Liu 9

Your first assignment Think about what you want to accomplish. List 2 your areas of interests (don’t be restricted by the previous list). Pick an area of interest and choose a general topic for paper presentation. Complete the above and submit it in the 3 rd class (next Tuesday 1/25). 12/13/2021 CSE 572: Data Mining by H. Liu 10

2 nd Assignment due in two weeks First, choose your category of interest Second, form presentation groups (3 -4 a group) Third, each group picks a paper from the given list of papers and find additional 2 high-quality relevant papers n n Submit it through my. ASU TA will help you and compile a list of all papers at the end Write a summary for each paper including n n n What is it about Why is it significant and relevant Where is it published and when 12/13/2021 CSE 572: Data Mining by H. Liu 11

Introduction The need for data mining Data mining Web mining (log, link, content) Applications 12/13/2021 CSE 572: Data Mining by H. Liu 12

What is data mining Data mining is n n extraction of useful patterns from data sources, e. g. , databases, texts, web, image. the analysis of (often large) observational data sets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner. 12/13/2021 CSE 572: Data Mining by H. Liu 13

Patterns (1) Patterns are the relationships and summaries derived through a data mining exercise. Patterns must be: n n valid novel potentially useful understandable 12/13/2021 CSE 572: Data Mining by H. Liu 14

Patterns (2) Patterns are used for n n n prediction or classification describing the existing data segmenting the data (e. g. , the market) profiling the data (e. g. , your customers) Detection (e. g. , intrusion, fault, anomaly) 12/13/2021 CSE 572: Data Mining by H. Liu 15

Data (1) Data mining typically deals with data that have already been collected for some purpose other than data mining. Data miners usually have no influence on data collection strategies. Large bodies of data cause new problems: representation, storage, retrieval, analysis, . . . 12/13/2021 CSE 572: Data Mining by H. Liu 16

Data (2) Even with a very large data set, we are usually faced with just a sample from the population. Data exist in many types (continuous, nominal) and forms (credit card usage records, supermarket transactions, government statistics, text, images, medical records, human genome databases, molecular databases). 12/13/2021 CSE 572: Data Mining by H. Liu 17

Typical DM tasks Classification: n mining patterns that can classify future data into known classes. Association rule mining: n mining any rule of the form X Y, where X and Y are sets of data items. Clustering: n identifying a set of similar groups in the data 12/13/2021 CSE 572: Data Mining by H. Liu 18

Sequential pattern mining: A sequential rule: A B, says that event A will be immediately followed by event B with a certain confidence Deviation/anomaly/exception detection: discovering the most significant changes in data Data visualization: using graphical methods to show patterns in data. High performance computing Bioinformatics 12/13/2021 CSE 572: Data Mining by H. Liu 19

Why data mining Rapid computerization of businesses produces huge amounts of data How to make best use of data? A growing realization: knowledge discovered from data can be used for competitive advantage and to increase business intelligence. 12/13/2021 CSE 572: Data Mining by H. Liu 20

Make use/sense of your data assets Many interesting things you want to find cannot be found using database queries “find me people likely to buy my products” “Who are likely to respond to my promotion” Fast identify underlying relationships and respond to emerging opportunities 12/13/2021 CSE 572: Data Mining by H. Liu 21

Why now The data is abundant. The data is being collected or warehoused. The computing power is affordable. The competitive pressure is increasingly. Data mining tools have become available. New challenges n n New data types evolve New applications emerge 12/13/2021 CSE 572: Data Mining by H. Liu 22

DM fields Data mining is an emerging multidisciplinary field: Statistics Machine learning Databases Visualization OLAP and data warehousing High-performance computing. . . 12/13/2021 CSE 572: Data Mining by H. Liu 23

Summary What is data mining? KDD - knowledge discovery in databases: non-trivial extraction of implicit, previously unknown and potentially useful information Why do we need data mining? Wide use of computer systems - data explosion knowledge is power – but we’re data rich, knowledge poor – useful, understandable and actionable knowledge. . . Data mining is not a plug-and-play, so we are not done yet and need to continue this class … 12/13/2021 CSE 572: Data Mining by H. Liu 24

An Overview of KDD Process (Guess which is which) 12/13/2021 CSE 572: Data Mining by H. Liu 25

Web mining – an application The Web is a massive database Semi-structured data XML and RDF Web mining n n n Content Structure Usage 12/13/2021 CSE 572: Data Mining by H. Liu 26