Date |
Slides |
Topics |
Literature |
Lecturer |
Comments |
|---|---|---|---|---|---|
Chapter I: Introduction | |||||
| October 15 | IR overview: [PDF] Part on data mining: [PDF] | IRDM applications & demos | Pauli & Klaus | Not relevant for the exam | |
Chapter II: Basics from probability theory, statistics, and linear algebra | |||||
| October 17 | No class | ... | ... | Pauli | |
| October 22 | [PDF] | Linear algebra | ZM: Ch. 7; TSK: App. B; MRS: Ch. 18; Extra reading: GL | Pauli | |
| October 24 | [PDF] | Events, probabilities, limit theorems | LW: Ch. 1-5 | Pauli | |
| October 29 | [PDF] | Parameter estimation, confidence intervals, hypothesis testing | LW: Ch. 6-7, 9, 10 | Klaus | |
Chapter III: Ranking principles | |||||
| October 31 | [PDF] | Boolean IR, TF-IDF, IR evaluation | MRS: Ch. 1,2,6,8 | Klaus | |
| November 5 | [PDF] | Probabilistic IR, BM25 | MRS: Ch. 11 | Klaus | |
| November 7 | [PDF] | Statistical language models, latent topic models | MRS: Ch. 12 | Klaus | |
| November 12 | [PDF] | Relevance feedback, novelty & diversity | MRS: Ch. 9,10; BY: Ch. 5,13 | Klaus | 1st short test |
Chapter IV: Link analysis | |||||
| November 14 | [PDF] | The World Wide Web as a graph, PageRank | MRS: Ch. 21; RU: Ch. 5 | Klaus | |
| November 19 | [PDF] | HITS | MRS: Ch. 21; RU: Ch. 5 | Klaus | |
| November 21 | [PDF] | Topic-specific & personalized PageRank, online link analysis, spam detection, social networks | see lecture slides | Klaus | |
Chapter V: Indexing & searching | |||||
| November 26 | [PDF] | Inverted lists, merging vs. hashing | MRS: Ch. 4,5; BY: Ch. 9; BCC: Ch. 5 | Klaus | |
| November 28 | [PDF] | Index compression, top-k query processing | MRS: Ch. 5; BY: Ch. 9; BCC: Ch. 6 | Klaus | |
| December 3 | PDF] | MapReduce, open-source search engines, efficient similarity search & hashing, LSH | BCC: Ch. 5; see also lecture slides |
Klaus | |
Chapter VI: Information extraction | |||||
| December 5 | [PDF] | IE overview & motivation, NLP basics | Klaus | ||
| December 10 | [PDF] | Rule- and learning-based extraction, HMMs | see lecture slides | Klaus | |
| December 12 | Entity reconciliation, knowledge base construction, Open-IE | see lecture slides | Klaus | 2nd short test | |
Chapter VII: Frequent itemsets and association rules | |||||
| December 17 | [PDF] | Frequent itemsets & association rules | ZM: Ch. 10; TSK: Ch. 6 | Pauli | |
| December 19 | [PDF] | Association rules and summarizing itemsets | ZM: Ch. 10, 11; TSK: Ch. 6 | Pauli | |
No lectures from December 23 - January 3 | |||||
Chapter VIII: Clustering | |||||
| January 7 | [PDF] | Representation clustering | ZM: Ch. 13; TSK: Ch. 8 | Pauli | |
| January 9 | [PDF] | Hierarchical, density-based, and co-clustering | ZM: Ch. 14&15; TSK: Ch. 8 | Pauli | |
Chapter IX: Classification | |||||
| January 14 | [PDF] | Decision trees and Naïve Bayes | ZM: Ch. 18, 19; TSK: Ch. 4, 5.3 - 5.6 | Pauli | |
| January 16 | [PDF] | Support vector machines and ensemble techniques | ZM: Ch. 21, 22; TSK: Ch. 5.3 | Pauli | |
Chapter X: Graph mining | |||||
| January 21 | [PDF] | Centrality, random graphs, and frequent subgraph mining | ZM: Ch. 4 & 11 | Pauli | |
| January 23 | [PDF] | Graph clustering | ZM: Ch. 16 | Pauli | |
Chapter XI: Two Matrix Factorization Methods | |||||
| January 28 | [PDF] | Two matrix factorization methods | Pauli | 3rd short test | |
Chapter XII: Data Pre and Post Processing | |||||
| January 30 | [PDF] | Curse of dimensionality and data pre-processing | ZM: Ch. 2.4, 6 & 8 | Pauli | |
| February 4 | [PDF] | Analyzing and visualizing results & tales from the real life | ZM: Ch. 2.2 | Pauli | |
Chapter XIII: Summary | |||||
| February 6 | [PDF-dm]&[PDF-ir] | Wrap up, summary, and Q & A | [PDF-qa | Pauli & Klaus | |
Final Exam, February 13, 2014 from 2PM to 5PM. Place: E 2.2, Guenter Hotz Lecture Hall | |||||
Re-Exam, March 17, 2014 from 2PM to 5PM. Place: E 2.2, Guenter Hotz Lecture Hall | |||||