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Lecture Slides and References

The topics, schedule, and lecture slides listed in this page are tentative, and will be updated periodically (e.g. weekly).

A draft plan for this quarter is here . The class home page is here .
Video recording for CS293S in Fall 2020 is here but the 293S content this quarter has been changed significantly to reflect the latest advancements in information retrieval and web search.

Weeks 1 and 2: Web Search and Information Retrieval

• Introduction
• Ranking and Learning
• Information retrieval model
• BERT contextual representation.
• Projects

References:

• T. Yang, A. Gerasoulis, Web Search Engines: Practice and Experience in Computer Science Handbook (T. Gonzalez. Eds), Chapman & Hall/CRC Press, 2014.
• CMS (Chapters 7 and 8) on retrieval models
• Project info
• An Introduction to Neural Information Retrieval by B. Mitra et. al 2017. Microsoft. A related tutorial on word embeedings.
• Xiong et al. "End-to-End Neural Ad-hoc Ranking with Kernel Pooling" in SIGIR 2017. Related DRMM paper in CIKM16.
• Pretrained Transformers for Text Ranking: BERT and Beyond, Andrew Yates, Rodrigo Nogueira, and Jimmy Lin, 2021
• Jacob Devlin et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, NAACL 2019.
• Pyserini Pyserini paper by J. Lin et al. in SIGIR21

Weeks 3-4: Advanced Topics on Document Retrieval, Ranking, and Indexing

• Recent research progress on neural information retrieval
• Inverted indexing and sparse retrieval
  
• Project meeting (Mid. October).
• HW1

References:

• O. Khattab, M. Zaharia ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT SIGIR 2020. ColbertV2 .
• Y. Yang et al., Compact Token Representations with Contextual Quantization for Efficient Document Re-ranking. ACL'22.
• SPLADE and SPLADE v2 SIGIR 2021 and 2022.
• RocketQA EMNLP 2021 and NAACL 2021.
• Tonellotto, N., Macdonald, C. and Ounis, I. (2018) Efficient query processing for scalable web search. Foundations and Trends in Information Retrieval, 12(4-5), pp. 319-500

Weeks 5-6: Offline Processing and Selected Topics

• Background: SGD and deep learning
• More on search engine evaluations
• Offline data processing and systems support
• Duplicate analysis and similarity computing

References:

• MapReduce short guide
• Spark guide
• Text book MRS Chapter 19.6 (Page 437-441)
• Mining of Massive Data Sets Chapter 3.4 (Page 91-96)

Weeks 7-8: Online Systems and Selected Topics

• Nearest Neighbor Search
• Query Processing Architecture and Online Systems
• Recommendation and advertisement
• Background: Learning ensembles
• Group presentations
• HW2

References:

• J. Johnson, M. Douze and H. Jégou, "Billion-Scale Similarity Search with GPUs," 2017. An extended version appeared in in IEEE Transactions on Big Data, 2021. It uses IVFADC (inverted index with PQ) developed first in "Product Quantization for Nearest Neighbor Search" in IEEE Transactions on PAMI 2011.

Weeks 9-10: Group Presentations

• Course summary