Web Mining And Retrieval 2015/2016

Programma

Section I: Machine Learning: Kernel-based Learning and Deep Neural Networks.

Introduction to Supervised and Unsupervised Machine Learning methods.

Clustering. Semantic Similarity metrics. Agglomerative clustering methods.

Markov Models. Hidden Markov Models.

Kernel-based Learning. String and Tree kernels. Semantic kernels.

Deep Neural Network architectures: from multilayer perceptrons to convolutional neural networks.

Machine Learning Applications.

Section II: Statistical Language Processing

Supervised Language Processing tools. HMM-based POS tagging. Named Entity Recognition.

Statistical parsing. Lexicalized Parsing Methods. Shallow Semantic Parsing

Information Extraction. Question Answering.

Section III: Web Mining & Retrieval.

Ranking Models for the Web.

Introduction to Social Network Analysis: rank, centrality. Random walk models: Page Rank.

Web Search Engines. SEO. Google.

Open-domain Information Extraction. Social Web.

Graph-based algorithms for community detection. Introduction to Opinion Mining and Sentiment Analysis.