magistraleinformatica:ir:ir18:start

**Teacher**: Paolo Ferragina**Course ID**: 289AA**CFU:**6 (first semester)**Language:**English**Question time:**After lectures it will be announced via Twitter**Official Lecture's Log:**Here it is the registro.- News about this course will be distributed via a Tweeter-channel

Study, design and analysis of IR systems which are efficient and effective to process, mine, search, cluster and classify documents, coming from textual as well as any unstructured domain. In the lectures, we will:

- study and analyze the main components of a modern search engine: Crawler, Parser, Compressor, Indexer, Query resolver, Query and Document annotator, Results Ranker;

- dig into some basic algorithmic techniques which are now ubiquitous in any IR application for data compression, indexing and sketching;

- describe few other IR tools which are used either as a component of a search engine or as independent tools and build up the previous algorithmic techniques, such as: Classification, Clustering, Recommendation, Random Sampling, Locality Sensitive Hashing.

Week Schedule | ||
---|---|---|

Day | Time Slot | Room |

Monday | 11:00 - 13:00 | L |

Tuesday | 9:00 - 11:00 | L1 |

The exam will consist of a written test plus an oral discussion on the exercises.

Date | Room | Text | Notes |
---|---|---|---|

29 oct 2018, 16:00-18:00 | C1, L1 | First Midterm exam: text, results, solution | Students that got a rank >= 16 can participate to the second midterm exam. Friday 9th November, hr 16:00, room L1, correction of the written exam. |

19 dec 2018, 16:00-18:00 | A1, L1 | Second Midterm exam: text, results, solution | Correction and registration will occur in Sala Seminari Ovest, Dip. Informatica, Wednesday 9th January, hr 17:00. Score “30 e lode” is assigned only to the students who got in both exams the score 30. The score is lost if the student participates to one of the next exams (just sitting is enough !). The score can be registered in any of the following exam dates (even in the summer), but PLEASE do not write your name in the ESAMI platform if you want to register your exam score, just show yourself in one of those dates. |

18 jan 2018, 09:00-11:00 | A1 | text, results, solution | Correction and registration will occur in Room C, Polo Fibonacci, Thursday 24th January, hr 9:00. The score is lost if the students participate to one of the next exams (just sitting is enough !). The score can be registered also in any one of the following exam dates (even in the summer), but PLEASE do not write your name in the ESAMI platform if you want to register your exam score, just show yourself in one of those dates. |

15 feb 2018, 09:00-11:00 | A1 | text, results, solution | Correction and registration will occur in Sala Seminari EST, Dip. Informatica, Monday 18th February, hr 16:00. The score can be registered in any of the following exam dates (even in the summer). The score is lost if the student participates to one of the next exams (just sitting is enough !). |

4 apr 2019, 11:00-13:00 | text | Results: Sabiu (30 L), Cardia (30). Correction and registration will occur in Ferragina's office: Monday 15th april at 14:30 (sharp), otherwise in any other following exam's date. | |

18 jun 2019, 09:00-13:00 | L1 | text | Results. If a student wishes to take also the Algorithm Engineering exam, s/he has to write to Prof. Ferragina for scheduling it in the same morning and avoid overlapping. |

17 jul 2019, 09:00-13:00 | L1 | text | Results. If a student wishes to take also the Algorithm Engineering exam, s/he has to write to Prof. Ferragina for scheduling it in the same morning and avoid overlapping. |

**[MRS]**C.D. Manning, P. Raghavan, H. Schutze.*Introduction to Information Retrieval*. Cambridge University Press, 2008. [ link ]- Some copies of papers (linked below).
- Some notes by Prof. Paolo Ferragina (linked below).

Date | Argument | Refs |
---|---|---|

17.09.2018 | Introduction to the course: modern IR, not just search engines! Boolean retrieval model. Matrix document-term. Inverted list: dictionary + postings. How to implement an AND, OR and NOT queries, and their time complexities. | Slides. Chapter 1 of [MRS] |

18.09.2018 | Web search engine: its structure, difficulties in their design and their epochs. The Web graph: some useful structural properties (such as Bow Tie). Crawling: problems and algorithmic structure. An example: Mercator. | Slides. Sections 19.1, 19.2, 19.4, 20.1, 20.2 of [MRS]. |

24.09.2018 | Few useful algorithmic techniques for crawling the Web (and not only that!): Bloom Filter and Spectral Bloom Filter. | Slides. For doubts on Bloom Filter see paper. |

25.09.2018 | Other useful algorithmic techniques for crawling the Web (and not only that!): Consistent Hashing. Web graph properties and its compressed storage. | Slides of the previous lecture. Sect 19.1 and 19.2, 20.3 and 20.4 of [MRS]. |

01.10.2018 | Locality-sensitive hashing: basics, hamming distance, proof of the probability bounds. | Slides |

02.10.2018 | Exact-duplicate documents: Karp-Rabin's rolling hash (with properties and error probability). Near-duplicate documents: Shingling, Jaccard similarity, min-hashing (with prob property), LSH on integer vectors, cosine-similarity among vectors of real-features. | slides. Sect 19.6 of [MRS] |

08/10/2018 | The issue of hierarchical memories: I/O-model. Index construction: multi-way mergesort, BSBI and SPIMI. Sketch on MapReduce. Distributed indexing: Term-based vs Doc-based partitioning. Dynamic indexing: two indexes, a cascade of indexes. | slides. Chapter 4 of [MRS]. |

09/10/2018 | Compressed storage of documents: LZ-based compression. Storage and Transmission of single/group of file(s): Delta compression (Zdelta), File Synchronization (rsync, zsync), and Set Reconciliation. | Slides. Reading a paper. |

15/10/2018 | Parsing: tokenization, normalization, lemmatization, stemming, thesauri. Statistical properties of texts: Zipf law: classical and generalized, Heaps law, Luhn's consideration. | Slides. Sect. 2.1, 2.2 and 5.1 of [MRS]. |

16/10/2018 | Keyword extraction: statistical, chi-square test, Rake tool. Exact search: hashing. Prefix search: compacted trie, front coding, 2-level indexing. | |

22/10/2018 | Exercises. | |

23/10/2018 | Exercises. | |

Midterm exam | ||

05/11/2018 | Edit distance via brute-force approach, or Dynamic Programming (possibly weighted). Overlap measure with k-gram index. Edit distance with k-gram index. One-error match. Wild-card queries (permuterm, k-gram). Phonetic match. Context-sensitive match. | Slides (new version). Chap 3 of [MRS]. |

06/11/2018 | Query processing: soft-AND, skip pointers, caching, phrase queries. Tiered index. Posting list compression, codes: gamma, variable bytes (t-nibble), PForDelta and Elias-Fano. | Slide query, Slide integer compressors. Sect. 2.3 and 2.4 and 5.3 of [MRS] and Ferragina's notes (only the coders presented in class). |

09/11/2018 | Correction of the midterm exam | |

12/11/2018 | Rank and Select data structures, two approaches: the case of B untouched and extra o(B) bits, and the case of Elias-Fano's approach with B compressed. | Slides. |

13/11/2018 | Succinct representation of binary trees and its navigational operations: heap like notation and LOUDS. | Slides. |

19/11/2018 | Text-based ranking: dice, jaccard, tf-idf. Vector space model. Storage of tf-idf and use for computing document-query similarity. Fast top-k retrieval: high idf, champion lists, many query-terms, fancy hits, clustering. | Slides. Sect 6.2 and 6.3 and 7 from [MRS]. |

20/11/2018 | Exact Top-K: WAND and blocked-WAND. Relevance feedback, Rocchio, pseudo-relevance feedback, query expansion. Performance measures: precision, recall, F1 and user happiness. | Chap 8 and 9 of [MRS] |

26/11/2018 | Random Walks. Link-based ranking: pagerank, topic-based pagerank, personalized pagerank, CoSim rank. HITS. | Slides. Chap 21 of [MRS] |

27/11/2018 | Exercises | |

3/12/2018 | Projections to smaller spaces: Latent Semantic Indexing (LSI). Random Projections: Johnson-Linderstauss Lemma and its applications. | Slides. Chap 18 from [MRS]. |

4/12/2018 | Semantic-annotation tools: basics, Wikipedia structure, TAGME and other annotators. Various approaches to text representation and their applications. Exercises | Slides |

10/12/2018 | A glimpse on Sport Analytics, and discussion of possible topics for a master thesis. | Slides and Thesis ideas. |

11/12/2018 | Exercises. |

magistraleinformatica/ir/ir18/start.txt · Ultima modifica: 13/04/2019 alle 12:15 (9 giorni fa) da Paolo Ferragina