PV211 -- Introduction to Information Retrieval (Spring 2020)

Intro | News | Lectures | Exercises (auth) | Previous courses | Projects |

Intro

The course is based on the textbook Manning, Raghavan and Schutze: Introduction to Information Retrieval (hard copies available in the library at FI) taught at Stanford, Munich and other places. In the course you will, among other things, learn how is it possible to fulfill seekers' information needs at the pace of 10,000+ questions per second on the global web scale within milliseconds.
This year, parts about machine (deep) learning are added, while others are discarded due to capacity reasons. Students will be motivated to try active/flipped learning approaches wherever possible. Course trailer (in Czech)

News

• We have switched to distance mode, and reduced the chapters covered by the course this year. For ``coronavirus updates'', please watch this web page, course materials in IS (auth), IS MU discussion group for PV211 (auth) (FAQ), PV211 2019 videos (auth), PV211 2020 videos (auth), and your email mailbox.
• In the case your want to use IR related materials/courses on Coursera for free, ask for it via an email to Petr Sojka.
• Course slides for 2020 lectures as one PDF (13+MB).
• Final exam terms are posted in IS for registering. Exam will take the form of synchronous IS ROPOTS done in electronic form this year during announced time range.

Lecture slides and other materials

1. 19. 2. 2020 12:00 D3: Introduction to IR, Boolean Retrieval.
   Boolean retrieval slides 1, IIR chapter 1
   Exercises (week 1+2, auth IS)
2. 26. 2. 2020 12:00 D3: Dictionary and Postings' storage (Indexing). Tolerant Retrieval.
   Readings: ternary trees, Soundex demo. Explore Google datacenters (YouTube video).
   Term vocabulary and postings lists slides 2, IIR chapter 2
   Dictionaries and tolerant retrieval slides 3, IIR chapter 3
   Exercises (week 1+2, auth IS)
3. 4. 3. 2020 12:00 D3: Tolerant retrieval (cont.), Index construction, MapReduce.
   Readings: Index construction slides 4, IIR chapter 4
   Exercises (week 3+4, auth IS)
4. 11. 3. 2020 12:00 D3: Index Compression, Scoring.
   Readings: Compression slides 5, IIR chapter 5
   Scoring, term weighting, the vector space model slides 6, IIR chapter 6
   Exercises (week 3+4, auth IS)
5. 18. 3. 2020 12:00 D3: Vector Space Model, Anatomy of the web scale IR system.
   Readings: Vector space model (slides Arguello)
   Google: Anatomy paper from 1998 (PDF), (HTML), slides Google infrastructure by Jeff Dean, Jeff Dean (YouTube video), Google File System, How Google works (YouTube in Czech), Challenges in Building Google... (slides by Jeff Dean from Stanford CS276 course in 2015), Google crash course (in Czech), slides Google architecture (Ed Austin).
   Exercises (week 5+6, auth IS), Sketch Engine
6. 25. 3. 2020 Distributed Word Representations for Information Retrieval.
   Readings: slides, main "word2vec" paper, Building scalable systems that understand content.
   Exercises (week 5+6, auth IS)
7. 1. 4. 2020 Computing scores in complete search system. Ranking.
   Scoring slides 7, IIR chapter 7
   Exercises (week 7+8, auth IS)
8. 8. 4. 2020 Evaluation in IR and result summaries
   Readings: slides 8, IIR chapter 8
   Exercises (week 7+8, auth IS)
9. 15. 4. 2020 Relevance feedback and Query expansion.
   Readings: Query expansion slides 9, IIR chapter 9
   Exercises (week 9+10, auth IS)
10. 22. 4. 2020 Text classification, Naive Bayes, Evaluation, Clustering, kNN.
    Readings: Text Classification and Naive Bayes slides 13, IIR chapter 13
    Clustering Introduction slides Cvinčeková, Flat Clustering slides 16, IIR chapter 16
    Exercises (week 9+10, auth IS), Term project information: deadline by April 29th.
11. 29. 4. 2020 Vector Space Classification.
    Readings: slides 14, IIR chapter 14.
    Exercises (week 11+12, auth IS)
12. 6. 5. 2020 Latent Semantics Models.
    Readings: Latent Semantic Indexing slides 18, IIR chapter 18, Gensim, Latent Dirichlet Allocation Topic similarity by LDA: intro, LDA slides by Blei, LDA visual browser demo
    Similarity search with Gensim (Exercise materials from 2019)
    Exercises (week 11+12, auth IS)
13. 13. 5. 2020 Web search.
    Readings: slides 19, IIR chapter 19.
    Exercises (week 13+14, auth IS)
14. 20. 5. 2020 Link Analysis.
    Readings: slides 21, IIR chapter 21, How Google finds a needle....
    Exercises (week 13+14, auth IS)

Topics not covered in 2020, course runs from previous years

• XML retrieval. slides 10, IIR chapter 10, MathML retrieval by MIaS in EuDML: slides
• Crawling. slides 20, IIR chapter 20
• SVM, Learning to Rank. Support Vector Machines slides 15a, Learning to Rank slides 15b, (IIR chapter 15)
• Probabilistic Information Retrieval slides 11, IIR chapter 11
• Language Models for IR slides 12, IIR chapter 12
• Hierarchical Clustering slides 17, IIR chapter 17
• PV211 course page from 2019, 2018, 2017, 2016, 2015, and 2014. Web pages of similar courses at Stanford and Munich.

Projects and miniprojects

I will be glad if you get encouraged into course topics and you decide to get insight into it by solving [mini]projects. Activities in this direction will be rewarded by the nontrivial number of premium points towards successful grading. Number of stars below is an estimate of project difficulty, from miniproject [(*), 10 points] to big project size [(*****), 30+ points]. I am also open to assign/extend a project as a Bachelor/ Masters/ Dissertation thesis.

• (*)+ Pointing to any (factual, typographical) errors in the course materials.
• (**)+ Preparation of hot topic slides, production or preparation of motivating Khan-Academy style video, or other course materials in LaTeX.
• (**)+ Presentation or teaching video on topics relevant to the course. Possible topics: Sketch Engine, search with linguistic attributes, random walks in texts, topic search and corpora, time-constrained search, topic modelling with gensim, LDA, Wolfram Alpha, specifics of search of structured data (chemical and mathematical formulae, linguistic trees - syntactic or dependency), etc.
• (***) Participation in IR competition at Kaggle.com.
• (***)+ Participation in IR research in our group Math Information Retrieval on research agendas and ARQMath task or EuDML project or DML project.
• (***)+ Evaluation of Math Information Retrieval in system MIaS - possible as a Dean project under supervision of Vít Novotný or Dávid Lupták or Michal Štefánik or as a Bachelor/ Masters/ Dissertation thesis.

To a pupil who was in danger, Master said, "Those who do not make mistakes, they are most mistaken for all – they do not try anything new." Anthony de Mello

sojka at fi dot muni dot cz --