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--- magistraleinformatica:dmi:start [22/10/2026 alle 09:39 (2 settimane fa)] – [Exam] Anna Monreale
+++ magistraleinformatica:dmi:start [05/11/2026 alle 07:07 (8 ore fa)] (versione attuale) – [First Semester] Anna Monreale
@@ Linea 11: / Linea 11: @@
 ====== News ======
+**[22-10-2026] Project Deadlines - Mid-projects**
+Dear all,
+The final deadline for the project has been set to **4 January 2027**. Please note that **this deadline is final and cannot be extended under any circumstances**. However, you are welcome to submit your project earlier.
+The **intermediate project presentations** will take place on **23 and 24 November 2026**, during the regular lecture hours. Each group will have **6 minutes for the presentation and 3 minutes for questions**. You are required to prepare a PowerPoint presentation to illustrate the current progress of your project.
+To register for the presentations, please use the shared Google Sheet. **Each group must select one available time slot** on either 23 or 24 November and enter its group information in the corresponding row. Slots are assigned on a **first-come, first-served basis**, so please choose a slot that has not already been taken by another group. **Only one member per group needs to complete the registration.**
+The **registration deadline is 6 November 2026**.
+The presentations will be **public**, meaning that other students are welcome to attend. Please remember that **these presentations are not part of the exam evaluation**. Their purpose is to provide an opportunity to discuss your progress, receive feedback, and identify potential issues before the final submission.
+Best regards,
+Lorenzo
+----
 **[01-10-2026] First Part of the Project + Q&A Google Sheet**
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 |15.  | 20.10  |Time series analysis: Motif discovery + Q&A on the project|{{ :magistraleinformatica:dmi:time_series_motif-2026.pdf |}} | {{ :magistraleinformatica:dmi:matrixprofile.pdf |}} [[https://www.cs.ucr.edu/~eamonn/MatrixProfile.html|Papers and resourse on motif]]| Monreale, Mannocci |
 |16.  | 22.10  |Python Lab - Time series analysis: Preprocessing, Clustering & Motif discovery + Q&A on the project|{{ :magistraleinformatica:dmi:10_time_series.zip |}}| | Mannocci |
+|17.  | 26.10  |Python Lab - Pattern Mining + Social Network Analysis Introduction (Theory and Python Lab)| {{ :magistraleinformatica:dmi:4_patternmining_2026.ipynb.zip |}} {{ :magistraleinformatica:dmi:social_network_analysis_2026.zip |}}| [[https://www.nature.com/articles/srep00196|Flavor network and the principles of food pairing]] [[https://d1wqtxts1xzle7.cloudfront.net/85768767/0906.0612v1-libre.pdf?1652125734=&response-content-disposition=inline%3B+filename%3DCommunity_detection_in_graphs.pdf&Expires=1793275277&Signature=gGWseP3welAubtnlnZ0vIS1iEZ6BPT-nBulvzzNV9j663C8b~gDyi69s5IthjntAqVbhOrCdzZTLCStWh8MkCIwzS6rmm78HnY99BkzC9vb~exqfoMnt94Gy5oRxmAWJczw1H54mJ3Um1ZPpSSU7DUTKgYjswf1rdHZELq9zGJDORHUlEZVTrQoxW4cGFpv5bPh28XrcdaYpk~KVy17ep9l~IPMgGTE08TCsMIoTFyZOLBe7F89ND7UkiWbHjxgFzKTsLLleaAdd0~2ZkDp0HBSvqe5Ds7vfSvXFGXrDSNYhTy6gGJ4aUu~cPSx~ErL1P2e9Y4DcgsrCnkDQEcdLcw__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA|Community detection in graphs]] [[https://onlinelibrary.wiley.com/share/IC8MKGVMFAC4NAMVXU7H?target=10.1002/sam.10133|A classification for community discovery methods in complex networks]] [[https://arxiv.org/abs/0803.0476|Fast unfolding of communities in large networks]] {{ :magistraleinformatica:dmi:collective_dynamics_of_small-world_networks.pdf |}} {{ :magistraleinformatica:dmi:mixing_patterns_in_networks.pdf |}}| Mannocci |
+|18.  | 27.10  |Clustering Heterogeneous and Multi-view data (Theory and Python Lab)|{{ :magistraleinformatica:dmi:clustering_heterogeneous_multiview_data_2026.zip |}} | {{ :magistraleinformatica:dmi:paper_clustering_heterogeneous_2026.zip |}}| Mannocci |
+|19.  | 29.10  |Topic modeling: BERTopic (Theory and Python Lab)| {{ :magistraleinformatica:dmi:topicmodeling_bertopic_2026.zip |}}| {{ :magistraleinformatica:dmi:paper_topicmodeling_bertopic_2026.zip |}}| Mannocci |
+|20.  | 02.11  |Supervised approaches + DT classification| {{ :magistraleinformatica:dmi:9.chap3_basic_classification-2026.pdf |Slides}}| Monreale |
+|21.  | 03.11  |DT classification| the same of the previous lecture same | Monreale |
+|22.  | 05.11  |Model evaluation |  {{ :magistraleinformatica:dmi:9.model_evaluation_classification-2026.pdf |}}| Monreale |