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Recent Advances in Applied Probability
Applied probability is a broad research area that is of interest to scientists in diverse disciplines in science and technology, including: anthropology, biology, communication theory, economics, epidemiology, finance, geography, linguistics, medicine, meteorology, operations research, psychology, quality control, sociology, and statistics. Recent Advances in Applied Probability is a collection of survey articles that bring together the work of leading researchers in applied probability to present current research advances in this important area. This volume will be of interest to graduate students and researchers whose research is closely connected to probability modelling and their applications. It is suitable for one semester graduate level research seminar in applied probability.
SOFSEM 2007: Theory and Practice of Computer Science
This book constitutes the refereed proceedings of the 33rd Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2007, held in Harrachov, Czech Republic in January 2007. The 69 revised full papers, presented together with 11 invited contributions were carefully reviewed and selected from 283 submissions. The papers were organized in four topical tracks.
Information Representation and Retrieval in the Digital Age
Information representation and retrieval : an overview -- Information representation I : basic approaches -- Information representation II : other related topics -- Language in information representation and retrieval -- Retrieval techniques and query representation -- Retrieval approaches -- Information retrieval models -- Information retrieval systems -- Retrieval of information unique in content or format -- The user dimension in information representation and retrieval -- Evaluation of information representation and retrieval -- Artificial intelligence in information representation and retrieval.
Advanced Topics in Information Retrieval
Deep learning and word embeddings have made significant impacts on information retrieval (IR) by adding techniques based in neural networks and language models. This book, written by international academic and industry experts, brings the field up to date with detailed discussions of new approaches and techniques.
Advances in Information Retrieval
This book constitutes the refereed proceedings of the 27th European Conference on Information Retrieval Research, ECIR 2005, held in Santiago de Compostela, Spain in March 2005. The 34 revised full papers presented together with 2 invited keynote papers and 17 selected poster papers were carefully reviewed and selected from 124 papers submitted. The papers are organized in topical sections on peer-to-peer, information retrieval models, text summarization, information retrieval methods, text classification and fusion, user studies and evaluation, multimedia retrieval, and Web information retrieval.
String Processing and Information Retrieval
This volume of the Lecture Notes in Computer Science series provides a c- prehensive, state-of-the-art survey of recent advances in string processing and information retrieval. It includes invited and research papers presented at the 9th International Symposium on String Processing and Information Retrieval, SPIRE2002, held in Lisbon, Portugal. SPIREhas its origins in the South Am- ican Workshop on String Processing which was ?rst held in Belo Horizonte, Brazil, in 1993. Starting in 1998, the focus of the workshop was broadened to include the area of information retrieval due to its increasing relevance and its inter-relationship with the area of string processing. The call for papers for SP...
Introduction to Information Retrieval
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.
