[ Formal Data | Course Tools | Syllabus & Schedule | Course Book | Course Materials | BlackBoard | Links ]
Lecture | Objectives | Concepts | Readings | Handouts |
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Lecture 1 Information System Design |
Introduction to the course. Logistics. Information Systems: Designer's view. Evolution and Evaluation. Abstractions. Documents and queries. Documents and document surrogates. What is in surrogates? What is in documents? | information retrieval, information system, information, data, information need, ectosystem, endosystem, user, funder, server, medium, device, algorithm, hypertext, effectiveness, efficiency, economy, abstraction, knowledge, wisdom, information theory, knowledge base, expert system, information retrieval system, information retrieval, SGML, HTML, RTF, HTML, GIF, JPEG, JBIG, MIDI, MPEG, EBCDIC, ASCII, MP3, SMILE, QuickTime, query, document, formatted document, unformatted document, document surrogate, matching, mapping, keyword, key phrase, extract, abstract, document identifier, review, uncontrolled vocabulary, vocabulary, controlled vocabulary, byte, atomic data, bit, ANSI, data compression, stemming, Huffman code, Ziv-Lempel code, data model, adaptive model, static model, semi-static model, synchronization point, level of compression, prefix property, markup language, segmentation, integrated media document, integrated media system, multimedia document, multimedia system, geographic information system, run length encoding, fine structure, metadata, document encoding, rich text, bit map |
Korfhage:
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Slides |
Lecture 2: Models of Information Retrieval |
Search and Browsing. Introduction to Hypertext. Classic IR paradigm. Queries and matching. Classic Boolean model. | exact match, range match, approximate match, proximity, elementary query, Boolean query, conjunctive normal form, conjunct, conjunctive query, disjunctive normal form, disjunct, disjunctive query, proximity operator, normalization, truth table, full disjunctive normal form, term, DeMorgan's Laws, Law of Double Negation, characteristic function, measure, Boolean query matching, Boolean query system, AND, OR, NOT, NOF |
Korfhage:
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Slides |
Lecture 3: Models of IR - II |
Document space, measure, similarity. Classic vector model. Queries and matching for advanced models. Problems with classic Boolean model. Extended Boolean model. Fuzzy model, Other models and aspects of matching. | proximity, vector, vector model, vector of terms, 0-1 vector, weight vector, contingency table, dimensional compatibility, judging dilemma, document space, lexical similarity, distance measure, dissimilarity measure, distance to similarity transformation, cosine measure, inner product, intrinsic measure, extrinsic measure |
Korfhage:
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Slides |
Lecture 4: Retrieval Effectiveness |
Measures for relevancy. Precision, recall, fallout, generality. Coverage ratio, novelty ratio, relative recall, recall effort. Average precision and recall. Expected search length. Normalized precision and recall. Sliding ratio. Satisfaction and frustration. |
Korfhage, Chapter 8 (skip 8.5) AND ("R. Baeza-Yates, B. Ribeiro-Neto: 1999. "Modern Information Retrieval", Chapter 3: pp. 73-96" OR "Mizzaro, S.:1997. Relevance: the whole history. Journal of the American Society for Information Science 48(9): 810-832.") |
Slides | |
Lecture 5: Text Analysis |
From text to index. Types of indexing. Zipf's law. The problem of choosing significant terms. TF*IDF. Stop lists and stemming.Thesauti. Document similarity. Multi-language retrieval. | Korfhage: Chapter 5 | Slides | |
Lecture 6: Data Structures and Algorithms |
Document processing, storage, search. Document files. Search problem. Simple search solution. Algorithms for searching and sorting. Complexity. Advanced searchable data structures: index files, inverted files, B-trees. |
Korfhage, Appendix B R. Baeza-Yates, B. Ribeiro-Neto: 1999. "Modern Information Retrieval", Chapter 8: Indexing and Searching |
Slides B-Trees Slides |
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Lecture 7: Taking user into account |
Improving Effectiveness: Relevance Feedback and Query Expansion; Adapting to the user: User profiles, user models, adaptive information retrieval, adaptive presentation |
Korfhage: Chapter 6, Chapter 9 R. Baeza-Yates, B. Ribeiro-Neto: 1999. "Modern Information Retrieval", Chapter 5: Query Operations |
Lecture Slides User Modeling in Information Retrieval Slides (Nick Belkin) |
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Lecture 8: Output presentation and visualization |
What to present, ranking, clustering, output exploration, visual interfaces for output exploration: GUIDO, VIBE, BIRD, TileBars, LyberWorld |
Korfhage: Chapter 11, Chapter 7 R. Baeza-Yates, B. Ribeiro-Neto: 1999. "Modern Information Retrieval", Chapter 10: User Interfaces and Visualization |
Slides |
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Lecture 9: Alternative retrieval techniques |
Natural language processing, citation processing, hypertext browsing, dynamic queries and implicit queries. Multimedia IR and digital libraries. |
Korfhage: Chapter 10 R. Baeza-Yates, B. Ribeiro-Neto: 1999. "Modern Information Retrieval", Chapters 11 and 12 |
Slides |
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Lecture 10: Web IR and other modern problems of information retrieval |
Characterising the Web. Search engines. Meta-search. Search services. Agents and bots. Clustering and information exploration. Use of hyperlinks. Web recommenders and other adaptive Web-based information systems. |
R. Baeza-Yates, B. Ribeiro-Neto: 1999. "Modern Information Retrieval", Chapter 13 |
Slides |
Copyright © 2001 Peter Brusilovsky