At the end of this course, the students; 1) Know the theoretical and modeling issues in information retrieval. 2) Know the techniques used in automatic indexing, searching and ranking output 3) Know classical and user-oriented approaches used in automatic classification 4) Know the roles of decision models and machine learning 5) Comprehend the importance of "learning by induction"
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
Theoretical and modeling issues in information retrieval: Automatic indexing. Techniques for searching and ranking output. Retrieval output evaluation. Classical and user-oriented approaches to automatic classification. Relevance feedback. Markov models. Distributed retrieval. Document filtering. Cross-language retrieval. The role of decision models and machine learning, in particular learning by observation and learning by induction, in the above processes.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Theoretical and modeling issues in information retrieval: Automatic indexing;
2nd Week
Techniques for searching and ranking output
3rd Week
Retrieval output evaluation
4th Week
Classical and user-oriented approaches to automatic classification
5th Week
Relevance feedback
6th Week
Markov models
7th Week
Markov models
8th Week
Mid-term
9th Week
Distributed retrieval
10th Week
Document filtering
11th Week
Cross-language retrieval
12th Week
Cross-language retrieval
13th Week
The role of decision models and machine learning, in particular learning by observation and learning by induction, in the above processes.
14th Week
The role of decision models and machine learning, in particular learning by observation and learning by induction, in the above processes.
RECOMENDED OR REQUIRED READING
1. Manning, C.D., Raghavan, P. & Schütze, H., "Introduction to Information Retrieval", Cambridge University Press, (2008). 2. Baeza-Yates, R. & Ribeiro-Neto, B., "Modern Information Retrieval: The Concepts and Technology behind Search", 2nd Edition, Addison-Wesley, (2011).
