Hasso-Plattner-Institut20 Jahre HPI
Hasso-Plattner-Institut20 Jahre HPI
  
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Text Visualization (Sommersemester 2019)

Lecturer: Dr. Ralf Krestel (Information Systems) , Tim Repke (Information Systems) , Nitisha Jain (Information Systems) , Julian Risch (Information Systems)
Course Website: https://hpi.de/en/naumann/teaching/teaching/ss-19/text-visualization.html

General Information

  • Weekly Hours: 2
  • Credits: 6
  • Graded: yes
  • Enrolment Deadline: 26.04.2019
  • Teaching Form: Project seminar
  • Enrolment Type: Compulsory Elective Module
  • Course Language: English
  • Maximum number of participants: 12

Programs & Modules

IT-Systems Engineering MA
Data Engineering MA
  • CODS-Konzepte und Methoden
  • CODS-Techniken und Werkzeuge
  • CODS-Spezialisierung

Description

With the ever increasing volume of data in the modern world, data visualization has become an essential component of every data analysis task. Visualization is an effective way to convey complex information and acts as a bridge between data and decisions.

This seminar will discuss the techniques and tools for creating efficient visualizations for the most important tasks related to large textual datasets.
The seminar is geared to be a series of highly interactive sessions with the students, seeking active classroom participations. The sessions will comprise of topic introductions, brainstorming for ideas, short group activities and active discussions. To maximize the practical learning, students will be expected to submit short practical assignments for the individual topics every week.
The second part of the seminar will consist of a project to be chosen by the student teams.

Requirements

There are no prerequisites except for being open and motivated to learn about text analysis and tools to analyize and visualize large text collections.

Literature

Collection of data visualization tools here.

Learning

Students will learn to...

  • perform common text analytics tasks to explore and understand a given text dataset.
  • represent large text corpora in visual form.
  • use various tools to process and visualize text data.
  • understand research papers and report on their own projects' progress.

Examination

Students are supposed to do homework assignments in the first phase and to write blog posts throughout the project phase to describe and share their progress.

The final grade will be based on selected homework assignments and the weekly blog posts.

Dates

Time: Monday, 11:00
Location: Campus II, F-E.06

Date Topic
08.04. Introduction and Organization
15.04. TFIDF/VSM + visualization
22.04. Holiday (Easter)
29.04. Dimensionality Reduction+PCA+tSNE+ visualization
06.05. Topic Modeling + Visualization
13.05. Word Embeddings + Visualization
20.05. Text Graphs + Visualization
27.05. Knowledge Graph + Visualization
03.06. Advanced topics + Recap
10.06. Holiday (Pentecost)
17.06. Project Pitches
24.06. Projects in groups
01.07. Projects in groups
08.07. Projects in groups
15.07. Projects in groups
TBD Final Submission

(subject to change)

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