- Mathematical Foundations: Formal Grammars and Languages
- Finite-State Technology
- Statistical Methods: Fundamentals
- Statistical Models for Natural Language Processing
- Machine Learning
- Word Representation
- Deep Learning
- Sublanguages and Controlled Languages
- Corpus Annotation
- Text Segmentation
- Part-of-Speech Tagging
- Semantic Role Labelling
- Word Sense Disambiguation
- Computational Treatment of Multiword Expressions
- Textual Entailment
- Anaphora Resolution
- Natural Language Generation
- Speech Recognition
- Temporal Processing
- Text-to-Speech Synthesis
- Machine Translation
- Translation Technology
- Information Retrieval
- Information Extraction
- Question Answering
- Text Summarization
- Term Extraction
- Web Text Mining
- Opinion Mining and Sentiment Analysis
- Spoken Language Dialogue Systems
- Multimodal Systems
- Natural Language Processing for Educational Applications
- Automated Writing Assistance
- Text Simplification
- Biomedical Computational Linguistics and Natural Language Processing
- Author Profiling and Related Applications
- Recent Developments in Natural Language Processing
Abstract and Keywords
Web search has become a ubiquitous commodity for Internet users. This fact puts a large number of documents with plenty of text content at our fingertips. To make good use of this data, we need to mine web text. This triggers the two problems covered here: sentiment analysis and entity retrieval in the context of the Web. The first problem answers the question of what people think about a given product or a topic, in particular sentiment analysis in social media. The second problem addresses the issue of solving certain enquiries precisely by returning a particular object: for instance, where the next concert of my favourite band will be or who the best cooks are in a particular region. Where to find these objects and how to retrieve, rank, and display them are tasks related to the entity retrieval problem.
Ricardo Baeza-Yates is Director of Data Science for Northeastern University at Silicon Valley. Before he was VP of Research at Yahoo Labs, based in Barcelona, Spain, and later in Sunnyvale, California, from 2006 to early 2016. He obtained a Ph.D. in CS from the University of Waterloo, in 1989. He is co-author of the best-seller Modern Information Retrieval textbook published by Addison-Wesley, 2011 (2ed), that won the ASIST 2012 Book of the Year award. In 2009 he was named ACM Fellow and in 2011, IEEE Fellow.
Roi Blanco is a senior scientist at Amazon in Barcelona, Spain, working on large scale machine learning and search. Before joining Amazon in 2017, he worked as a research scientist at Yahoo Labs in London and Barcelona. He is interested in applications of natural language processing for information retrieval, web search and mining and large scale information access in general, and has been active publishing at international conferences in those areas. Previously he taught computer science at A Coruña University, from which he received his Ph.D. degree (cum laude) in 2008.
Malú Castellanos is Senior Manager of the Data Science Engineering team at Teradata. Previously, she was a senior researcher at HP Labs, working on different areas of data management. Later, at Vertica (HPE), she managed an engineering team in the Advanced Analytics R&D group. Earlier, she was on the Faculty of the Department of Information Systems at the Polytechnic University of Catalunya (Barcelona), where she received her Ph.D. She has authored over 60 publications and has more than 25 patents. She has served in different roles in the organization and PC of prestigious international data management conferences (ICDE, VLDB, SIGMOD).
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