2ID25 - Information retrieval Course

TU/e	2ID25 Information retrieval

Program: BIS, CSE, INF

Course Info: OWInfo

Lecturer: Mykola Pechenizkiy

Course materials can be found in Moodle eLearning environment. Please, create an account and register for the course in Moodle.

Course Syllabus

Date, Time, and Room	Lecture Title and Contents	Introduction to IR book (draft available online)
27 Aug 2007 Monday 13:30 – 15:15 MA1.46	Lecture 1: Introduction to the course Course overview Basic IR terminology, ideas, architecture Keyword search	Ch. 1
3 Sep 2007 Monday 13:30 – 15:15 MA1.46	Lecture 2: Basic IR Models and Indexing The dictionary and postings lists Tolerant Retrieval Index construction Index compression	Ch. 2, Ch. 3, Ch. 4, Ch. 5
10 Sep 2007 Monday 13:30 – 15:15 MA1.46	Lecture 3: Classification Naive Bayes, Bayesian Networks Nearest Neighbour and SVM Decision tree learning Ensemble learning	Ch. 13, Ch. 14, Ch. 15 Alternative reading¹
14 Sep 2007 Friday 8:45 – 10:30 AUD 9	Lecture 4: Clustering kMeans Expectation Maximization Hierarchical clustering	Ch. 16, Ch. 17 Alternative reading¹
17 Sep 2007 Monday 13:30 – 15:15 MA1.46	Lecture 5: Data/Dimensionality Reduction Sampling approaches Feature selection approaches PCA, SVD, LDA Random projections	Ch. 18 Links to reading material
21 Sep 2007 Friday 8:45 – 10:30 AUD 9	Lecture 6: Web mining Content mining Structure mining Usage mining	Links to reading material
24 Sep 2007 Monday 13:30 – 15:15 MA1.46	Lecture 7: IR Models: Vector Space Vector space retrieval Latent-Concept Models	Ch. 6, Ch. 18
1 Oct 2007 Monday 13:30 – 15:15 IPO 0.98	Online questionnaire for ML module (it is necessary to bring a laptop that has an access to TUe network (Lan or WiFi))
8 Oct 2007 Monday (extended) Deadline	Submit your reports on the 1st and 2nd Individual Assignments. **Please note, those student who attend AS (2ID55) course and do not attend IR (2ID25) course are required to do only Individual Assignent 2
8 Oct 2007 Monday 13:30 – 15:15 MA1.50	Lecture 8: Evaluation in IR and Relevance Feedback Basic evaluating principles Relevance and utility Query expansion	Ch. 8, Ch. 9
15 Oct 2007 Monday 13:30 – 15:15 MA1.50	Lecture 9: Advanced IR Models Probabilistic IR Statistical Language Models	Ch. 11, Ch. 12,
22 Oct 2007 Monday 13:30 – 15:15 MA1.50	Lecture 10: Search engines Web search basics Web crawling and indexes	Ch. 19, Ch. 20
29 Oct 2007 Monday 13:30 – 15:15 MA1.50	Lecture 11: Link Analysis Web spam, SEO Reference models Google’s Pagerank Hub and authorities	Ch. 19, Ch. 21
5 Nov 2007 Monday 13:30 – 15:15 MA1.46	No lecture this week. Please visit my office for discussing your project proposal if it has not been finalized. Nov 5 is also a dealine to submit your final proposal
9 Nov 2007 Friday 8:45 - 10:30 AUD 9	Lecture 12: Recommender Systems Content-based filtering Collaborative filtering Hybrid approaches	Links to reading material
12 Nov 2007 Monday 13:30 – 15:15 IPO 0.98	Online questionnaire for traditional IR module (it is necessary to bring a laptop that has an access to TUe network (Lan or WiFi))
26 Nov 2007 (Extended) Monday Deadline	Submit your report on the 3rd Individual Assignment
19 Nov 2007 Monday 13:30 – 15:15 MA1.46	Lecture 13: MultiMedia retrieval Automatic content based analysis GEMINI and time-series mining view Semantic gap	Links to reading material
26 Nov 2007 Monday 13:30 – 15:15 MA1.46	Lecture 14: Information extraction Question answering on the web Relation extraction Text summarization	Links to reading material
3 Dec 2007 Monday 13:30 – 15:15 MA1.46	Lecture 15: Closing Lecture Brief summary of the course Not covered topics and further reading Advanced R&D issues in IR	Links to reading material
10 Dec 2007 Monday 13:30 – 15:15 IPO 0.98	Online questionnaire for Web IR and Personalization modules (it is necessary to bring a laptop that has an access to TUe network (Lan or WiFi))
10 Dec 2007 Monday Deadline	Submission of the delayed reports (if any) on the Individual Assignments (-1 for your grade)
10 Dec 2007 Monday 13:30 – 15:15 MA1.46	Questions/feedback regarding the outcomes of the Individual Assignments and Online questionnaires
17 Dec 2007 Monday 13:30 – 15:15 MA1.46	Student presentations of their project work (A schedule will be posted a few days in advance)
21 Dec 2007 Monday Deadline	Submit your group report on the Project Assignment
14th or 21st Jan 2008 Monday 13:30 – 15:15 MA1.46	Delayed project presentations by students (-1 for your grade unless motivated and agreed at least 1 month before the deadline).

Colour agenda:

Regular IR lectures

Lectures for both IR and AS

Assignment deadline or online questionnaire

Modes of study and evaluation

15 face-to-face lectures and individual reading

Online questionnaires (cover essential issues in lectures and reading material)

3 small individual assignments (to be accomplished individually)
- Small-scale experiments with data pre-processing, and applying and evaluating machine learning techniques.
Project assignment (work in small groups)

Literature study, IR system (component) development and evaluation
Oral presentation of the project work Dec 17, 2007 and final report (about 10 pages)

No final exam; but there will be a series of online quizzes (mainly multiple-choice questions)
Final grade = 0.2 * Online Quizzes + 0.2 * Individual Assignments + 0.6 * Project Assignment

Online course materials are powered with Moodle eLearning environment.

Remarks:

Please note that lectures 2-5, and 11 (weeks 37-38, and 44) and an online questionnaire on week 40 are common for the participants of 2ID25 and 2ID55 during which Machine Learning/Data Mining module will be given.
Please note also that this schedule in indicative and some changes are still possible.
Lecture 1 and Lecture 2 are given by Prof. Paul De Bra.

[1] AS students who are not interested in IR may prefer to study the corresponding chapters from a classical DM book as e.g. "Introdution to Datamining" by Tan, Steinbach, Kumar. This source however is recommended for everyone for better understanding of Data Mining concepts and techniques.

For further questions, please contact

TU/e

2ID25 Information retrieval

Course Syllabus