Master in Informatics and Computing Engineering
Information Description, Storage and Retrieval
Instance: 2020/2021
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By the end of this class, the student should be able to: ¶

• describe a test collection: documents, topics, relevance judgements; ¶
• explain the need for specific evaluation methods in information retrieval; ¶
• define precision, recall and their variants; ¶
• interpret a precision vs recall graph; ¶

1. Evaluation in Information Retrieval ¶
   • Test collections ¶
   • IR measures: precision, recall, P@n, F, MAP ¶
   • Evaluation of ranked results ¶

• Evaluation in Information Retrieval ¶

• W. Bruce Croft, Donald Metzler, Trevor Strohman, Search Engines: Information Retrieval in Practice, Slides for chapters 2, 7, 8, accessed October 2019 ¶
• Ricardo Baeza-Yates, Berthier Ribeiro-Neto, Modern Information Retrieval: The Concepts and Technology behind Search, Slides for Chapter 3: Modeling, Chapter 4: Retrieval Evaluation, accessed October 2020 ¶
• Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Chapter 6, 7, 8, 11, 12, accessed October 2020 ¶
• Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Slides for chapters 6, 7, 8, 11, 12, accessed October 2020 ¶

• Experiment with full-text indexing tools. ¶
• Milestone #2: define information needs for the full-text search task. ¶
• Milestone #2: perform indexing experiments in the project collection. ¶

• Evaluation in Information Retrieval. Test collections. IR measures: precision, recall, P@n, F, MAP. ¶
• Evaluation of non-ranked results. Evaluation of ranked results. Relevance judgements. ¶
• Work on Milestone 2 in the course project (Information Retrieval). ¶
• Indexing experiments on the working collection. ¶
• Definition of retrieval features for the domain. ¶

— MCR, JCL, SSN ¶

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