13215
Comment:
|
15882
|
Deletions are marked like this. | Additions are marked like this. |
Line 8: | Line 8: |
<a style="color:darkred; font-weight: bold" href="http://ad-wiki.informatik.uni-freiburg.de/teaching/InformationRetrievalWS1617/Exam">NEW: information about the exam</a> | <a style="color:darkred; font-weight: bold" href="http://ad-wiki.informatik.uni-freiburg.de/teaching/InformationRetrievalWS1617/Exam">Information about the exam</a> |
Line 10: | Line 10: |
{{{ #!html <a style="color:darkred; font-weight: bold" href="http://ad-wiki.informatik.uni-freiburg.de/teaching/InformationRetrievalWS1617/Evaluation">Here are the results for the official evaluation of this course</a> }}} |
|
Line 21: | Line 27: |
* Short introductions to SVN and Vim and the installation of gtest (for C++ only) can be found [[ProgrammierenCplusplusSS2016|here]] (in German). | * Short introductions to SVN and Vim and the installation of gtest (for C++ only) can be found [[ProgrammierenCplusplusSS2016|here (in German)]] and for the SVN now also [[SVNEnglish|here (in English)]]. |
Line 37: | Line 43: |
* Lecture 11, Tuesday, January 17, 2017 (Classification, Naive Bayes): [[https://youtube.com/embed//M4stb0NzDLY]] ([[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/lecture-11.mp4|Download]]), [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn-public/public/slides/lecture-11.pdf|Slides]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn-public/public/exercises/sheet-11.pdf|Exercise Sheet 11]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn/public/code/lecture-11/|Code for ES 11]], Datasets for ES11: [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/movie_genres_train.txt|movie genres (train)]], [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/movie_genres_test.txt|movie genres (test)]], [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/movie_ratings_train.txt|movie ratings (train)]], [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/movie_ratings_test.txt|movie ratings (test)]]. | * Lecture 11, Tuesday, January 17, 2017 (Classification, Naive Bayes): [[https://youtube.com/embed/M4stb0NzDLY|Video Recording]] ([[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/lecture-11.mp4|Download]]), [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn-public/public/slides/lecture-11.pdf|Slides]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn-public/public/exercises/sheet-11.pdf|Exercise Sheet 11]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn/public/code/lecture-11/|Code for ES 11]], Datasets for ES11: [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/movie_genres_train.txt|movie genres (train)]], [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/movie_genres_test.txt|movie genres (test)]], [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/movie_ratings_train.txt|movie ratings (train)]], [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/movie_ratings_test.txt|movie ratings (test)]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn/solutions/sheet-11/|Solution]]. * Lecture 12, Tuesday, January 24, 2017 (Linear Classifiers, Perceptrons), '''[[https://daphne.informatik.uni-freiburg.de/forum/viewtopic.php?f=611&t=3490|online only because Prof. Bast was sick]]''': [[https://youtube.com/embed/IR0WkiPTm7k|Video Recording]] ([[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/lecture-12.mp4|Download]]), [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn-public/public/slides/lecture-12.pdf|Slides]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn-public/public/exercises/sheet-12.pdf|Exercise Sheet 12]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn/solutions/sheet-12/sheet-12-solution.pdf|Solution]]. * Lecture 13, Tuesday, January 31, 2017 (Knowledge Bases, SPARQL, Translation to SQL): [[https://youtube.com/embed/_iXQEBP3Yrg|Video Recording]] ([[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/lecture-13.mp4|Download]]), [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn-public/public/slides/lecture-13.pdf|Slides]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn-public/public/exercises/sheet-13.pdf|Exercise Sheet 13]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn/public/code/lecture-13/|Code from the lecture and TIP file]], [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/freebase.tsv|Datasets for ES13]] (10M facts from Freebase), [[InformationRetrievalWS1617/ResultsES13|Table for your results]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn/solutions/sheet-13/|Solution]]. * Lecture 14, Tuesday, February 7, 2017 (Course Evaluation, Exam, Work at our Chair): [[https://youtube.com/embed/Jjn1bbTarXo|Video Recording]] ([[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1617/lecture-14.mp4|Download]]), [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn-public/public/slides/lecture-14.pdf|Slides]], [[https://daphne.informatik.uni-freiburg.de/ws1617/InformationRetrieval/svn-public/public/exercises/sheet-14.pdf|Exercise Sheet 14 (very short + does not count for exam admission)]]. |
Welcome to the Wiki of the course "Information Retrieval" in the winter term 2016/2017
Here are the results for the official evaluation of this course
The course is given by Prof. Dr. Hannah Bast and assisted by Patrick Brosi. It takes place every Tuesday from 4:15pm until 5:45pm in the Hörsaal HS 026 in building 101. The first lecture is on Tuesday, 18 October 2016 and the last lecture is on Tuesday, 7 February 2017. There will be no lecture on Tuesday, 1 November 2016 (Halloween), and on Tuesday, 27 December 2016 and Tuesday, 3 January 2017 (christmas break). This is 14 lectures altogether.
The tutors for this course are Raghu Rajan, Natalie Prange, Johanna Götz, Axel Lehmann, Claudius Korzen, Björn Buchhold. The administrator of the supporting systems (Daphne, SVN, Forum, Jenkins) is Axel Lehmann.
Important Links
Here is the link to Daphne (our course management system, login with your RZ user name and password).
Here is the link to the Forum (for announcements and questions, you are automatically a member when you have logged into Daphne).
Code style profiles for Eclipse: Java, C++ (add .xml to file name).
Short introductions to SVN and Vim and the installation of gtest (for C++ only) can be found here (in German) and for the SVN now also here (in English).
The topics of this course will be similar (but not identical) to those of the courses Information Retrieval WS 2012/2013 and Information Retrieval WS 2013/2014 and Information Retrieval WS 2015/2016./
Here is information about the exams from previous years: WS 12/13, WS 13/14, WS 15/16.
Lecture Slides, Video Recordings, Exercise Sheets, and Code
Lecture 1, Tuesday, October 18, 2016 (Introduction, Inverted Index, Zipf's Law): Video Recording (Download), Slides, Exercise Sheet 1, Code from the lecture, Dataset for ES1 (189,898 movies, title + description), Solution.
Lecture 2, Tuesday, October 25, 2016 (Ranking and Evaluation): Video Recording (Download), Slides, Exercise Sheet 2, TIP file and example file for test cases, Movies dataset (same one as for ES1), Movies Benchmark, Table for your ranking results, Solution.
Lecture 3, Tuesday, November 8, 2016 (Efficient List Intersection): Video Recording (Download), Slides, Exercise Sheet 3, postings lists for ES3, basic code to get you started in Java and C++, Table for your intersection results, Solution.
Lecture 4, Tuesday, November 15, 2016 (Compression, Codes, Entropy): Video Recording (Download), Slides, Exercise Sheet 4, Solution.
Lecture 5, Tuesday, November 22, 2016 (Fuzzy Search, Edit Distance, q-Gram Index): Video Recording (Download), Slides, Exercise Sheet 5, Cities dataset (181,296 cities, rank + geolocation), basic code and TIP file to get you started in Java and C++, Table for your results, Solution.
Lecture 6, Tuesday, November 29, 2016 (Web applications, part 1): Video Recording (Download), Slides, Exercise Sheet 6, Cities dataset (same as for ES 5), basic code and TIP file to get you started in Java and C++, HTML, CSS and JavaScript from the lecture, Solution.
Lecture 7, Tuesday, December 6, 2016 (Web applications, part 2: Vulnerabilities, Cookies, Unicode): Video Recording (Download), Slides, Exercise Sheet 7, TIP file, Code from the lecture, NEW cities dataset, Solution.
Lecture 8, Tuesday, December 13, 2016 (Vector space model): Video Recording (Download), Slides, Exercise Sheet 8, TIP file, Code from the lecture, Solution.
Lecture 9, Tuesday, December 20, 2016 (Clustering, k-means): Video Recording (Download), Slides, Exercise Sheet 9, TIP file, Table for your results, Solution.
Lecture 10, Tuesday, January 10, 2017 (Latent Semantic Indexing): Video Recording (Download), Slides, Exercise Sheet 10, TIP file, Code from the lecture, Table for your results, Solution.
Lecture 11, Tuesday, January 17, 2017 (Classification, Naive Bayes): Video Recording (Download), Slides, Exercise Sheet 11, Code for ES 11, Datasets for ES11: movie genres (train), movie genres (test), movie ratings (train), movie ratings (test), Solution.
Lecture 12, Tuesday, January 24, 2017 (Linear Classifiers, Perceptrons), online only because Prof. Bast was sick: Video Recording (Download), Slides, Exercise Sheet 12, Solution.
Lecture 13, Tuesday, January 31, 2017 (Knowledge Bases, SPARQL, Translation to SQL): Video Recording (Download), Slides, Exercise Sheet 13, Code from the lecture and TIP file, Datasets for ES13 (10M facts from Freebase), Table for your results, Solution.
Lecture 14, Tuesday, February 7, 2017 (Course Evaluation, Exam, Work at our Chair): Video Recording (Download), Slides, Exercise Sheet 14 (very short + does not count for exam admission).