Introduction to Data Mining

Principles of Database Systems

November 13, 2019

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Outline

1 What is data?

2 What is data science/mining?

3 Graph Mining

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What is data?

Outline

1 What is data?

2 What is data science/mining?

3 Graph Mining

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What is data?

Data is Big!

I Big Data

I Data is everywhere.

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What is data?

Data Growth

I An article by Forbesstates that

• Data is growing fasterthan ever before

• By the year 2020,about 1.7 megabytesof new informationwill be created everysecond for everyhuman being on theplanet.

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What is data?

Types of Data

How many?

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What is data?

Types of Data

How many?I Time-series data

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What is data?

Types of Data

How many?I Time-series dataI Sequence data

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What is data?

Types of Data

How many?I Time-series dataI Sequence dataI Graphs, social

networks

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What is data?

Types of Data

How many?I Time-series dataI Sequence dataI Graphs, social

networksI Multimedia, WWW

data

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What is data?

Types of Data

How many?I Time-series dataI Sequence dataI Graphs, social

networksI Multimedia, WWW

dataI Text data

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What is data science/mining?

Outline

1 What is data?

2 What is data science/mining?

3 Graph Mining

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What is data science/mining?

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What is data science/mining?

What do data scientists do?

I Make discoveries while swimming indata

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What is data science/mining?

What do data scientists do?

I Make discoveries while swimming indata

I The statistics represent this significantand growing demand for data scientists.

• Data mining tops LinkedIn’s list of the“hottest skills of 2016”

• Best job in USA for 2016• 3,433: Number of Job Openings in

2016• #16 Highest Paying Job in Demand

in 2016Average Base Salary : $105,395:

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What is data science/mining?

What is Data science/mining?

I Non-trivial extraction of implicit,previously unknown, and potentiallyuseful information from data

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What is data science/mining?

What is Data science/mining?

I Non-trivial extraction of implicit,previously unknown, and potentiallyuseful information from data

I Storing, organizing and integrating hugeamount of unstructured data

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What is data science/mining?

What is Data science/mining?

I Non-trivial extraction of implicit,previously unknown, and potentiallyuseful information from data

I Storing, organizing and integrating hugeamount of unstructured data

I a.k.a. KDD (knowledge discovery indatabases)

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What is data science/mining?

Application of Data Science

I ?

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What is data science/mining?

Application of Data Science

I Internet search

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What is data science/mining?

Application of Data Science

I Internet searchI Recommender

systems

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What is data science/mining?

Application of Data Science

I Internet searchI Recommender

systemsI Biological

Classification

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What is data science/mining?

Application of Data Science

I Internet searchI Recommender

systemsI Biological

ClassificationI ...

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What is data science/mining?

Data Mining Tasks

1 Prediction Methods (Supervised Learning): Predict unknown orfuture values of the data using other known data

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What is data science/mining?

Data Mining Tasks

1 Prediction Methods (Supervised Learning): Predict unknown orfuture values of the data using other known data

• Classification: Is this A or B?

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What is data science/mining?

Data Mining Tasks

1 Prediction Methods (Supervised Learning): Predict unknown orfuture values of the data using other known data

• Classification: Is this A or B?

• Anomaly detection: Is this weird?Fraud Detection

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What is data science/mining?

Data Mining Tasks

1 Prediction Methods (Supervised Learning): Predict unknown orfuture values of the data using other known data

• Classification: Is this A or B?

• Anomaly detection: Is this weird?Fraud Detection

• Regression: How much? Howmany?

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What is data science/mining?

Data Mining Tasks - Continued

2 Description Methods (Unsupervised learning): Findhuman-interpretable (previously unknown) patterns that describe thedata (unlabeled)

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What is data science/mining?

Data Mining Tasks - Continued

2 Description Methods (Unsupervised learning): Findhuman-interpretable (previously unknown) patterns that describe thedata (unlabeled)

I Clustering: How is dataorganized?

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What is data science/mining?

Data Mining Tasks - Continued

2 Description Methods (Unsupervised learning): Findhuman-interpretable (previously unknown) patterns that describe thedata (unlabeled)

I Clustering: How is dataorganized?

I Association rule mining:Are these related?

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What is data science/mining?

What is dataset?

I Collection of data objects andtheir attributes

I Simple Case : n × d matrix• n objects with d dimension

each,• d columns are called variables,

features or attributes ofobjects

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What is data science/mining?

What is dataset?

I Collection of data objects andtheir attributes

I Simple Case : n × d matrix• n objects with d dimension

each,• d columns are called variables,

features or attributes ofobjects

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Graph Mining

Outline

1 What is data?

2 What is data science/mining?

3 Graph Mining

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Graph Mining

Graph Mining

I Graph

I Community Detection

I Community Search

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Graph Mining

Graphs

I Structured data representing relationship btw objects

I Important in modeling sophisticated structures and their interaction

I Formed by

• A set of vertices

• A set of edges

I Examples

• Computer networks

• Social networks

• Protein interactionnetworks

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Graph Mining

Graphs

I Structured data representing relationship btw objects

I Important in modeling sophisticated structures and their interaction

I Formed by

• A set of vertices

• A set of edges

I Examples

• Computer networks

• Social networks

• Protein interactionnetworks

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Graph Mining

Graphs

I Structured data representing relationship btw objects

I Important in modeling sophisticated structures and their interaction

I Formed by

• A set of vertices

• A set of edges

I Examples

• Computer networks

• Social networks

• Protein interactionnetworks

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Graph Mining

Graphs

I Structured data representing relationship btw objects

I Important in modeling sophisticated structures and their interaction

I Formed by

• A set of vertices

• A set of edges

I Examples

• Computer networks

• Social networks

• Protein interactionnetworks

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Graph Mining

Graphs

I Structured data representing relationship btw objects

I Important in modeling sophisticated structures and their interaction

I Formed by

• A set of vertices

• A set of edges

I Examples

• Computer networks

• Social networks

• Protein interactionnetworks

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Graph Mining

Graphs

I Structured data representing relationship btw objects

I Important in modeling sophisticated structures and their interaction

I Formed by

• A set of vertices

• A set of edges

I Examples

• Computer networks

• Social networks

• Protein interactionnetworks

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Graph Mining

Community Detection

I Graph Clustering: afundamental data miningproblem

I Discover densely connectedgroups in a large graph

• Many links within acommunity

• Few links betweencommunities

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Graph Mining

Community Detection

I Graph Clustering: afundamental data miningproblem

I Discover densely connectedgroups in a large graph

• Many links within acommunity

• Few links betweencommunities

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Graph Mining

Community Detection

I Graph Clustering: afundamental data miningproblem

I Discover densely connectedgroups in a large graph

• Many links within acommunity

• Few links betweencommunities

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Graph Mining

Community Detection

I Graph Clustering: afundamental data miningproblem

I Discover densely connectedgroups in a large graph

• Many links within acommunity

• Few links betweencommunities

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Graph Mining

Community Detection

I Widely used in many fields

• Social networks

• Biological networks

• Citation networks

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Graph Mining

Community Detection

I Widely used in many fields

• Social networks

• Biological networks

• Citation networks

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Graph Mining

Community Detection

I Widely used in many fields

• Social networks

• Biological networks

• Citation networks

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Graph Mining

Community Detection

I Widely used in many fields

• Social networks

• Biological networks

• Citation networks

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Graph Mining

Community Search

I Big Data; increasing size of the networks

• Expensive time/space cost to identify all communities

I Interested in the communities pertaining to a given vertex

I Local community detection (Community Search)

• Given a (set of) query node(s), finding all densely connected subgraphsof the input graph, containing the given query node(s)

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Graph Mining

Community Search

I Big Data; increasing size of the networks

• Expensive time/space cost to identify all communities

I Interested in the communities pertaining to a given vertex

I Local community detection (Community Search)

• Given a (set of) query node(s), finding all densely connected subgraphsof the input graph, containing the given query node(s)

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Graph Mining

Community Search

I Big Data; increasing size of the networks

• Expensive time/space cost to identify all communities

I Interested in the communities pertaining to a given vertex

I Local community detection (Community Search)

• Given a (set of) query node(s), finding all densely connected subgraphsof the input graph, containing the given query node(s)

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Graph Mining

Community Search

I Big Data; increasing size of the networks

• Expensive time/space cost to identify all communities

I Interested in the communities pertaining to a given vertex

I Local community detection (Community Search)

• Given a (set of) query node(s), finding all densely connected subgraphsof the input graph, containing the given query node(s)

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Graph Mining

Community Search

I Big Data; increasing size of the networks

• Expensive time/space cost to identify all communities

I Interested in the communities pertaining to a given vertex

I Local community detection (Community Search)

• Given a (set of) query node(s), finding all densely connected subgraphsof the input graph, containing the given query node(s)

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Graph Mining

Any Questions?

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