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IBM PowerKVM: Configuration and Use
This IBM® Redpaper Redbooks® publication presents the IBM PowerKVM virtualization for scale-out Linux systems, including the new LC IBM Power SystemsTM. PowerKVM is open source server virtualization that is based on the IBM POWER8® processor technology. It includes the Linux open source technology of KVM virtualization, and it complements the performance, scalability, and security qualities of Linux. This book describes the concepts of PowerKVM and how you can deploy your virtual machines with the software stack included in the product. It helps you install and configure PowerKVM on your Power Systems server and provides guidance for managing the supported virtualization features by using...
String Processing and Information Retrieval
This book constitutes the refereed proceedings of the 14th International Symposium on String Processing and Information Retrieval, SPIRE 2007. Coverage in the 27 revised full papers includes dictionary algorithms, text searching, pattern matching, text compression, text mining, natural language processing, sequence driven protein structure prediction, XML, SGML, information retrieval from semi-structured data, text mining and generation of structured data from text.
Flexible Pattern Matching in Strings
Presents recently developed algorithms for searching for simple, multiple and extended strings, regular expressions, exact and approximate matches.
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.
Autophagy
Starting in the early 1970s, a type of programmed cell death called apoptosis began to receive attention. Over the next three decades, research in this area continued at an accelerated rate. In the early 1990s, a second type of programmed cell death, autophagy, came into focus. Autophagy has been studied in mammalian cells for many years. The recen
Mining User Generated Content
Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other networking sites, the social media shared by users and the associated metadata are collectively known as user generated content (UGC). To analyze UGC and glean insight about user behavior, robust techniques are needed to tackle the huge amount of real-time, multimedia,
Ranking for Web Data Search Using On-The-Fly Data Integration
Ranking - the algorithmic decision on how relevant an information artifact is for a given information need and the sorting of artifacts by their concluded relevancy - is an integral part of every search engine. In this book we investigate how structured Web data can be leveraged for ranking with the goal to improve the effectiveness of search. We propose new solutions for ranking using on-the-fly data integration and experimentally analyze and evaluate them against the latest baselines.
Demand-Driven Associative Classification
The ultimate goal of machines is to help humans to solve problems. Such problems range between two extremes: structured problems for which the solution is totally defined (and thus are easily programmed by humans), and random problems for which the solution is completely undefined (and thus cannot be programmed). Problems in the vast middle ground have solutions that cannot be well defined and are, thus, inherently hard to program. Machine Learning is the way to handle this vast middle ground, so that many tedious and difficult hand-coding tasks would be replaced by automatic learning methods. There are several machine learning tasks, and this work is focused on a major one, which is known as classification. Some classification problems are hard to solve, but we show that they can be decomposed into much simpler sub-problems. We also show that independently solving these sub-problems by taking into account their particular demands, often leads to improved classification performance.
String Processing and Information Retrieval
This book constitutes the refereed proceedings of the 29th International Symposium on String Processing and Information Retrieval, SPIRE 2022, held in Concepción, Chile, in November 2022. The 23 full papers presented in this volume were carefully reviewed and selected from 43 submissions. They cover topics such as: data structures; algorithms; information retrieval; compression; combinatorics on words; and computational biology.
String Processing and Information Retrieval
This book constitutes the refereed proceedings of the 19th International Symposium on String Processing and Information Retrieval, SPIRE 2012, held in Cartagena de Indias, Colombia, in October 2012. The 26 full papers, 13 short papers, and 3 keynote speeches were carefully reviewed and selected from 81 submissions. The following topics are covered: fundamentals algorithms in string processing and information retrieval; SP and IR techniques as applied to areas such as computational biology, DNA sequencing, and Web mining.
