Advanced Topics in Information Retrieval and Natural Language Processing

Spring Semester 2017

The seminar will explore advanced topics in the areas of information retrieval. Students will select papers and prepare a 30-45 min presentation in the seminar followed by discussions. You will learn to read and critically evaluate current research papers. It is expected that all students regularly participate in the seminar and the discussions.

Course Catalogue Info

Course Material

Introduction Slides
Paper Selection Form

Course Schedule

1 21.02.2017 Start-up Phase
2 28.02.2017 Start-up Phase
3 07.03.2017 Start-up Phase
4 14.03.2017 Optimizing Search Engines Using Clickthrough Data Georgios Touloupas
Adarank: A Boosting Algorithm for Information Retrieval Junlin Yao
5 21.03.2017 Distributed Representations of Words and Phrases and their Compositionality Loris Diana
Glove: Global Vectors for Word Representation Lukas Drescher
6 28.03.2017 No Seminar
7 04.04.2017 Distributed Representations of Sentences and Documents Ankit Srivastava
Learning Composition Models for Phrase Embeddings Jie Huang
8 11.04.2017 A Deep Architecture for Matching Short Texts Thomas Asikis
Text Matching as Image Recognition Zuoyue Li
9 18.04.2017 Easter Break
10 25.04.2017 Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks Benjamin Gallusser
Learning Deep Structured Semantic Models for Web Search using Clickthrough Data Jessica Pape
11 02.05.2017 Improving Document Ranking with Dual Word Embeddings Haohui Deng
A Deep Relevance Matching Model for Ad-hoc Retrieval Moyuan Zhou
12 09.05.2017 Exploring Session Context using Distributed Representations of Queries and Reformulations Frederic Lafrance
13 16.05.2017 Search Result Prefetching Using Cursor Movement Pengfei Ji
User Behavior in Asynchronous Slow Search Lídia Freitas
14 23.05.2016 Personalized ranking metric embedding for next new POI recommendation Yanping Xie
Learning Graph-based POI Embedding for Location-based Recommendation Zhichao Han
15 30.05.2016 Convolutional Neural Tensor Network Architecture for Community-based Question Answering GuanJu Li
Neural Responding Machine for Short-text Conversation Robin Vaaler


Lecturer Carsten Eickhoff