CS5143701: Information Retrieval and Applications

13:20~16:20, Friday, @TR-514

 

Instructor: ³¯«a¦t

TA: ÃCÐk®p

 

Date Syllabus Homework
9/14 Course Overview
9/21 Classic Models Homework-1
9/28 Extended Probabilistic Models
10/5 Break @ Rocling 2018
10/12 Evaluation & Benchmark Collections Homework-2 & HW2 Description
10/19 Latent Semantic Analysis and Topic Models Homework-3
10/26 Search Results Diversification
11/2 Midterm Exam
11/9 Pseudo-Relevance Feedback & Query Models Homework-4
11/16 From Information Retrieval to Language Processing (Mr. Huang-Wei Chen, ASUS)
11/23 Introduction to Deep Learning Submit Your Member List and Paper Title!
11/30 Representation Learning for Information Retrieval Homework-5
12/7 Supervised Retrieval Models & Web Search Submit Your Paper Title!
12/14
  1. ªô0­Û ­J0¹Å ¦¿0¨¹ ³¯0¾ç NPRF: A Neural Pseudo Relevance Feedback Framework
  2. ¤ý0·¢ ªL0­õ ¨H0¤@ ¬I0¥õ Co-PACRR: A Context-Aware Neural IR Model for Ad-hoc Retrieval
  3. Ĭ0¸s ¾G0¤¸ ªL0¦t Áé0ªä A Rank-Based Similarity Metric for Word Embeddings
  4. ù0­ì ²0©¨ ®}0ªN ·¨0¿o Modeling Diverse Relevance Patterns in Ad-hoc Retrieval
  5. §d0µX ¶À0ºö ³\0·Ø ©P0¿« A Concept Language Model for Ad-hoc Retrieval
  6. ³¢0ä~ ³¯0ºÍ ¾G0Á¾ ·¨0²a Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks
12/21
  1. §E0¯E ·¨0´_ ®É0ËÕ §d0ºÂ Deep Neural Network for Learning to Rank Query-Text Pairs
  2. ¤à0½U ¹ù0©ú ¾G0¬° Learning a Deep Listwise Context Model for Ranking Refinement
  3. ¤ý0­× ©P0ÑÔ ³¯0¾± ªL0ñZ An accelerated PSO for query expansion in web information retrieval: application to medical dataset
  4. §d0±d ·¨0¬v ½²0°a Bag of Tricks for Efficient Text Classification
  5. ÂÅ0¤¤ ¥v0ºû §f0¦t Soft Similarity and Soft Cosine Measure: Similarity of Features in Vector Space Model
  6. ®}0Â{ §f0²» ²0Ãü ¤ý0µ¾ IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models
12/28 Break
1/4 Final Competition Final Project