Information Retrieval - Academic Year 2019/2020

General Information

Teacher : Paolo Ferragina
Course ID: 289AA
CFU: 6 (first semester)
Language: English
Question time: Monday 15-17, or appointment
Official Lecture's Log: Here it is the registro.
News about this course will be distributed via a Telegram channel

Goals

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.

Schedule of the Lectures

Week Schedule
Day	Time Slot	Room
Monday	11:00 - 13:00	L1
Tuesday	9:00 - 11:00	L1

Exams

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

Date	Room	Text	Notes
26/11/19, 9:00-11:00	First Midterm exam	text, results, solution	Students that got a rank >= 16 can participate to the second midterm exam. To the average of the two midterms will be added +2.
16/12/19, 11:00-13:00	room on exam's site (Second MidTerm)	text, solution, results.	Score “30 e lode” has been assigned only to the students who got rank 32 (I used ceiling and not floor of the average, and summed 2!). 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 (in the summer, too), 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.
13/01/20, 14:00-17:00	room on exam's site	text, solution, results.	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.
10/02/20, 14:00-17:00	room on exam's site	text, solution, results.	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.

Materials for study

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

Lectures

Date	Argument	Refs
16.09.2019	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]
17.09.2018	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].
23.09.2019	Few useful algorithmic techniques for crawling the Web (and not only that!): Bloom Filter and Spectral Bloom Filter. Some other uses of Bloom Filter.	Slides. For doubts on Bloom Filter see paper.
24.09.2019	Other useful algorithmic techniques for crawling the Web (and not only that!): Consistent Hashing.	Slides of the previous lecture. Sect 19.1 and 19.2 of [MRS].
30.09.2019	Locality-sensitive hashing: basics, hamming distance, proof of the probability bounds.	Slides
01.10.2019	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]
07.10.2019	Web graph properties and its compressed storage. The issue of hierarchical memories: I/O-model. Index construction: multi-way mergesort, BSBI and SPIMI.	Slides on WebGraph are at the end of slides of 23.09. Slides this lecture. Sect 20.3 and 20.4 of [MRS]. Chapter 4 of [MRS]
08.10.2019	Sketch on MapReduce. Distributed indexing: Term-based vs Doc-based partitioning. Dynamic indexing: two indexes, a cascade of indexes. Compressed storage of documents: LZ-based compression.	Slides. Chapter 4 of [MRS].
14.10.2019	Storage and Transmission of single/group of file(s): Delta compression (Zdelta), File Synchronization (rsync, zsync), and File Reconciliation.	Reading a paper.
15.10.2019	Parsing: tokenization, normalization, lemmatization, stemming, thesauri. Statistical properties of texts: Zipf law: classical and generalized, Heaps law, Luhn's consideration. Keyword extraction: statistical, chi-square test, Rake tool.	Slides. Sect. 2.1, 2.2 and 5.1 of [MRS].
21.10.2019	Exact search: hashing. Prefix search: compacted trie, front coding, 2-level indexing.	Slide.
22.10.2019	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.	Chap 3 of [MRS].
28.10.2019	Exercises
29.10.2019	Seminar on Sports Analytics	by Luca Pappalardo, slides
04.11.2019	Exercises
05.11.2019	Query processing: soft-AND, skip pointers, caching, phrase queries. Tiered index. Posting list compression, codes: gamma, variable bytes (t-nibble), PForDelta and Elias-Fano.	Sect. 2.3 and 2.4 and 5.3 of [MRS] and Ferragina's notes (only the coders presented in class). Slides and Slides.
18.11.2019	Cancellata per allerta meteo
19.11.2019	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.	Sect 6.2 and 6.3 and 7 from [MRS]. Slides.
25.11.2019	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]
26.11.2019	First MidTerm exam
02.12.2019	Random Walks. Link-based ranking: pagerank, topic-based pagerank, personalized pagerank, HITS.	Chap 21 of [MRS]. Slides
03.12.2019	Projections to smaller spaces: Latent Semantic Indexing (LSI). Random Projections: Johnson-Linderstauss Lemma and its applications.	Chap 18 from [MRS]. Slides.
05.12.2019	Semantic-annotation tools: basics, Wikipedia structure, TAGME and other annotators. Various approaches to text representation and their applications. An example of a sophisticate system: Wiser.	Slides tagme and wiser.
09.12.2019	Canceled
10.12.2019	Canceled
12.12.2019	Exercises on the second part of the course
13.12.2019	Exercises on the second part of the course
16.12.2019	Second MidTerm exam
17.12.2019	Canceled

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