Text Technologies for Data Science

Course code: INFR11145
Course details, including prerequisites, topics covered, and course objectives are: here

Note

The course material of this course is made publicly available for anyone interested to audit the course. This includes lectures slides, recordings, and labs below. However, CW submissions and lab support are provided only to those enrolled to the course.

Logistics

Live Lectures

Wednesdays, 12.00-14.30, Online. Link available on Learn

Live Labs

Tuesdays, 3 different slots on Teams: 10-11am, 12:1pm, 6-7pm.

Piazza

Piazza discussion forum of the course is here

Lectures

Handouts will be posted on the day of the lecture. Recording of lectures will be available on Learn.

Lecture 1: Introduction. Slides - Recording
Lecture 2: Definitions. slides - Recording
Lecture 3: Text Laws. slides - Recording part1, part2
Lecture 4: Preprocessing. slides - Recording
Lecture 5: Indexing (1). slides - Recording
Lecture 6: Indexing (2). slides - Recording
Lecture 7: Ranked Retrieval (1). slides - Recording
Lecture 8: Ranked Retrieval (2). slides - Recording
Lecture 9: Evaluation (1). slides - Recording
Lecture 10: Evaluation (2). slides - Recording

Labs

Lab 0: How to read a text file from disk (optional): Lab
Lab 1: Based on lectures 3 and 4: Lab
Lab 2: Based on lecture 5: lab
Lab 3: Based on lecture 7: lab
Lab 4: no lab this week, just catch up with your CW submission

Lab Format

All labs will be online this year. Labs will run in a self-learing/online-support fashion as follows:

After each lecture on Wednesday, related lab will be announced and posted online.
Students will be responsible to start implementing lab directly on their own at home (or on DICE machines). If they have any related question to the lab, they should post it on Piazza and tag their question that it is related to which lab
Demonstrators will be responsible to asnwer questions related to labs on Piazza. Other students are welcome to provide answers as well.
Please check that your question has not been asked already by another student before posting yours
A thread called "answers of Lab X" will be posted on Piazza so students can share their output of the lab.
By the next Tuesday, if some students still need some help in their lab, we will provide several slots for online meetings with demonstrators to answer your questions live. Note, online lab slots are limited, so kindly, do not register for it unless you followed all Piazza posts on the lab and still failed to produce the output.

Coursework

Coursework 1: Based on lectures 3-7: AS01. Full details here!
Submission deadline Sunday, 25 October 2020.

Readings

Textbook1: " Introduction to Information Retrieval", C.D. Manning, P. Raghavan and H. Schutze
Textbook2: Search Engines: Information Retrieval in Practice (SE). [Tables of Contents]
Information Retrieval, C.J. van Rijsbergen
Managing Gigabytes, I.H. Witten, A. Moffat, T.C. Bell
Recommended Reading for IR Research Students, A. Moffat, J. Zobel, D. Hawking

Course Coordinators: Walid Magdy and Steve Wilson

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