Data Mining, Integration and Analysis - PowerPoint Presentation

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Data Mining, Integration and Analysis

Karin Becker

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Data Mining, Integration and Analysis

Knowledge Discovery

Web and Text Mining

Data ScienceRecommendation SystemsScalability and PerformanceReproducibility

Ana Lucia Cetertich BazzanJoao Luiz Dihl CombaKarin BeckerLeandro Krug WivesLucas Mello SchnorrMara AbelRenata De Matos GalanteViviane Pereira Moreira

Reserach Areas

Faculty

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Knowledge Discovery

What do we do?

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Knowledge Discovery

Data Collection

Data Integration

Data Preprocessing

Data Mining

Data Analysis

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Karin Becker

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Extract Knowledge from Social Media

Semantic enrichment framework for event-related tweet identification (Simone Romero)

No assumptions about event properties

Contextual knowledge from semantic web and external documentsImproved mainly recall

Simone Romero, Karin Becker. A framework for event classification in tweets based on hybrid semantic enrichment . Expert Systems with Applications 118: 522-538 (2019)

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Extract Knowledge from Social Media

Identifica

tion of stance in tweets (Marcelo Dias)

No threads of argumentationsUnsupervised and weakly supervised* frameworks (runner-up)Target and stance expression depends on the domain

Marcelo Dias, Karin Becker. An Heuristics-based, Weakly-Supervised Approachfor Classification of Stance in Tweets . Proc. of Web Inteligence, 2016.

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Extract Knowledge from Social Media

Identifica

tion of stance in tweets

Unsupervised frameworkExcelent perfomance on straightfoward targets (Hillary, Clinton)

Marcelo Dias, Karin Becker. An Heuristics-based, Weakly-Supervised Approachfor Classification of Stance in Tweets . Proc. of Web Inteligence, 2016.

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Extracting Knowledge from Social Midia

analyze the

emotions people express about terrorism events

in Twitter using demographics (Jonathas Harb)Automatic emotion classification (4 terrorism events)Tested deep learning with different seeding strategiesDemographic analysis (Face++, Profile Location)

Jonathas Harb, Karin Becker. Emotion Analysis of Reaction to Terrorism on Twitter. Proc. of Workshop on Big Social Data and Urban Computing, 2018.

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Analysis

Q2: Do different terrorism events raise the same emotional reaction?

NO

Gender? Age?

Location?Our hypothesis: it depends on how people relate to the event

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Extracting Knowledge from Social Midia

C

ompare engagement of twitter users in Pink October and Blue November campaigns (Roberto Walter)

5 different countriesDemographic analysis (Face++, Profile Location)Tweet topic categorization

Roberto Walter, Karin Becker. Caracterização e Comparação das Campanhas do Outubro Rosa e Novembro Azul no Twitter. SBBD 2018: 133-144

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Extracting Knowledge from Social Midia

T

opic discovery and drift analysis

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Extracting Knowledge from Social Interaction

Relating conversational topics and toxic behavior effects in a MOBA game

(Joaquim Mesquita)

MOBA Games (LoL)Effects of toxic behavior on other playersBehavioral patterns based on on-line chats

Joaquim A. M. Neto, Karin Becker: Relating conversational topics and toxic behavior effects in a MOBA game. Entertainment Computing 26: 10-29 (2018)

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Extracting Knowledge from Social Interaction

Relating conversational topics and toxic behavior effects in a MOBA game

(Joaquim Mesquita)

MOBA Games (LoL)Effects of toxic behaviorBehavioral Patterns based on on-line chats

Joaquim A. M. Neto, Karin Becker: Relating conversational topics and toxic behavior effects in a MOBA game. Entertainment Computing 26: 10-29 (2018)

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Extracing Knowledge from Medical Data

Machine translation for biomedical texts, paralel corpus (Felipe Soares)

H

ierarchical classifier for non-invasive colorectal cancer screeningPlasma fluorescence data

Cancer, No findings, Further investigationFelipe Soares, Karin Becker, Michel J. Anzanello:A hierarchical classifier based on human blood plasma fluorescence for non-invasive colorectal cancer screening. Artificial Intelligence in Medicine 82: 1-10 (2017)

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Extracting Knowledge from Medical Data

Relating mental states using social media (Vanessa Borba)

Characterization of mental states (verbal cues, emotions and sentiments, behavioral and social patterns)

Analysis of temporal evolution of mental states (e.g. Ansiety – depression – suicide)Detecting Anomalies in Health Provision Records (Cristiano Sulzbach)

Lack of parameters of “normality”Discovery of groups of dataAnalysis of closeness

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A final word on Software Engineering

Strong background on software engineering

Industry experience

Agile MethodsSentiment analysis on software artifactsSatisfaction of IT users (Sentiment analysis on IT Tickets, Blaz, 2016)Analisis of assertiveness of user stories and development productivity and quality metrics (Guilherme Dias, 2018)

Using gamefication in SCRUM for self-imrpovement (Camilla Schmidt, on-going)

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Renata Galante

galante@

inf.ufrgs.br

Data

Integration

Data

Analysis

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Raul Barth (master)

Passenger

density

and flow analysis and city zones and bus stops

classification

for

public

bus

service

management

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Framework

DMBSM

– Data Mining Framework for Bus Service

ManagementInput: GPS, bus stop and smart card data Extracting as

passengers’ density and flow informationBus stops segmentation based on travel purposesFinding the real bus service demandEnabling decision-making. Based on Lambda Architecture, using Big Data for parallel processing

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Framework – Architecture and Results

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Case of Study - Results

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Ricardo

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Marcos

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Drunk Text Identification

Marcos

Grzeça

, Karin Becker, Renata Galante (UFRGS)

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Drunk Text Identification

Detecção de textos escritos por pessoas alcoolizadas

Marcos

Grzeça, Karin Becker, Renata Galante (UFRGS)

Romero & Becker (2019)

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Drunk Text Identification

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Drunk Text Identification