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FAW @ Lange Nacht der Forschung 2016

Lange Nacht der Forschung 2016

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Position Indication:

Content

Web Search and Mining (351.028)

Course Instructor

a.Univ.-Prof. Dr. Birgit Pröll (birgit.proell(at)faw.jku.at)

Registration

via KUSSS

Preliminary Meeting: Presence obligatory!

Presence is obligatory at the beginning of the first course and at the times of presentations of exercises (see timetable below). Exercises may be worked on in groups up to 3 students.

Course Schedule

Please, note that except for the 1st lecture, lectures will start at 12 ct
Furthermore, dates might be subject to change. Therfore, please, save in addition
the following dates - same times, same regulation for obligatory presence:
- Thu 7 April, Thu 21 April, Thu 12 May, Thu 9 Jun 2016

- Thu 10 Mar 2016, 12:00-15:15 (S2 059, S2 046 (room change at 14:30))

  • Preliminary Meeting, decision on course participants, group building for exercises
  • Lecture 1: Information Retrieval "in a nutshell"

- Thu 17 Mar 2016, 12:15-15:15 (S2 059, S2 046 (room change at 14:30))

  • Lecture 2: Web Search: Overview and Basic Concepts

- Thu 14 Apr 2016, 12:15-15:15 (S2 059, S2 046 (room change at 14:30))

  • 12:15-13:30 - Exercise (presence obligatory)
  • Lecture 3: Search Engine Optimization (SEO), Site Search

- Thu 28 April 2016, 12:15-15:15 (S2 059, S2 046 (room change at 14:30))

  • 12:15-13:30 - Exercise (presence obligatory)
  • Lecture 4: Web Informatin Extraction

- Thu 19 May 2016, 12:15-15:15 (S2 059, S2 046 (room change at 14:30))

  • 12:15-13:30 - Exercise (presence obligatory)
  • Lecture 5: Natural Language Processing (NLP), Opinion Mining

- Thu 2 June 2016, 12:15-15:15 (S2 059, S2 046 (room change at 14:30))

  • 12:15-13:30 - Exercise (presence obligatory)
  • Lecture 6: Search User Interfaces, Question Answering, Dialogue Systems

- Thu 16 Jun 2016, 12:15-13:30 (HS12)

  • Final Exam

Course Description

Objectives

- Students have competence in fundamentals and technologies of

  • Web Search (Web Information Retrieval) and their application in search engines
  • Web Mining with an emphasis on Web Information Extraction focusing on a knooweldge-based approach

- They are able to implement and evaluate applications in these fields and have knowledge about related fields and current research topics.

Subject

- Web Search (Web Information Retrieval)

  • Information retrieval „in a nutshell“
  • Web Search Fundamentals
  • Web Crawling
  • Search Engines
  • Weighting and Ranking (PageRank etc.)
  • Web Search Evaluation
  • Site Search
  • Search Engine Optimization (SEO)
  • Search User Interfaces (advanced query concepts etc.)
  • Web 2.0 & Social Media Search/Monitoring

- Web Mining (Web Information Extraction)

  • Information Extraction „in a nutshell“
  • Web information extraction (WebIE) funcamentals
  • WebIE approaches (knowledge-based Web IE, screen-scraping/wrapping, etc.)
  • Web link/structure analysis
  • WebIE tools and aplications (focusing on a knowledge-based approach)

- Current concepts and applications

  • Deep Web Search
  • Spam Detection
  • Question Aanswering Systems (focused seach)
  • Web 2.0 & Social Media Search/Monitoring
  • Opinion Mining / Sentiment Analysis
  • Crowd Knowledge Extraction
  • Web-based Ontology Learning
  • Web Data Quality, etc.

Exercises

  • Exercises will be handed out and are to be presented in the following lession.
  • Exercises can be workes on in groups up to three persons.
  • The first part of each lesson is dedicated to the presentation of exercises - see course schedule above
  • Presence during this firs part of each lesson is obligatory to achieve the exercises' full points. Non-presence results in reduction of exercises' points.

Graduation

  • Exercises (45%), Final Exam (45%), In-class Contribution (10%)
  • The contents for the final exam comprises the in-class presentation of the lecturer as well as the presentations of topics by the students
  • Sowohl die Aufgabenausarbeitung als auch die Klausur müssen positiv abgeschlossen werden.

Course Material & Literature

  • Slides will be accessible for each course the day before
  • Search Engines (B. Croft; Pearson 2010)