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Information Retrieval (IR) and Search Engines Design/Implementation, Text Mining
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  • Entity-Oriented Search (Krisztian Balog)

    This open access book covers all facets of entity-oriented search - where "search" can be interpreted in the broadest sense of information access - from a unified point of view, and provides a coherent and comprehensive overview of the state of the art.

  • Text Mining with R: A Tidy Approach (Julia Silge, et al)

    You'll explore text-mining techniques with tidytext, a package that authors developed using the tidy principles behind R packages like ggraph and dplyr. You'll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.

  • Think Data Structures: Algorithms and Information Retrieval

    This practical book will help you learn and review some of the most important ideas in software engineering - data structures and algorithms - in a way that's clearer, more concise, and more engaging than other materials. Useful in technical interviews too.

  • O'Reilly® Elasticsearch: The Definitive Guide (Clinton Gormley)

    This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships.

  • Apache Solr Succinctly (Xavier Morera)

    This book guides you through the basics of this highly popular enterprise search tool. You'll learn how to set up an index and how to make it searchable, then query it with a simple enterprise search. Explanations for precision and recall are also included.

  • Introduction to Information Retrieval (Christopher Manning, et al)

    This book covers 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.

  • Mathematics for Classical Information Retrieval: Roots and Apps

    This book is about Information Retrieval (IR), particularly Classical Information Retrieval (CIR). The primary goal of book is to create a context for understanding the principles of CIR by discussing its mathematical bases.

  • Information Retrieval Interaction (Peter Ingwersen)

    The aims of the book are to establish a unifying scientific approach to IR - a synthesis based on the concept of IR interaction and the Cognitive Viewpoint, and to generate a consolidated framework - the Mediator Model.

  • Information Retrieval: Uncertainty and Logics (C. J. van Rijsbergen)

    This book contains a collection of exciting papers proposing, developing and implementing logical Information Retrieval (IR) models. This book is appropriate for use as a text for a graduate-level course on Information Retrieval or Database Systems.

  • Information Retrieval: A Survey (Ed Greengrass)

    This report is a tutorial and survey of the state of the art, both research and commercial, in the dynamic field of Information Retrieval.

  • Data-Intensive Text Processing with MapReduce (Jimmy Lin)

    This free book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning.

  • Theory and Applications for Advanced Text Mining (S. Sakurai)

    This book introduces advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language. It will give new knowledge in the text mining field and help many readers open their new research fields.

  • Mining the Web: Discovering Knowledge from Hypertext Data

    This is is the first book devoted entirely to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issues-including Web crawling and indexing.

  • The Beginner's Guide to Search Engine Optimization (SEO)

    This book is a concise and clear introduction to the art of search engine optimization and marketing. It presents current website optimization strategies, discusses their pitfalls and builds the foundations for long term success.

  • Search Engine Optimization (SEO) by Jacqui Carrel

    This book reveals the fundamentals of good SEO practice and gives plenty of examples. It teaches you on-site optimization: how to optimize the content on your website, and how to optimize the bits behind the scenes (the code and metatags).

  • The Fourth Paradigm: Data-Intensive Scientific Discovery

    This book presents the first broad look at the rapidly emerging field of data-intensive science, with the goal of influencing the worldwide scientific and computing research communities and inspiring the next generation of scientists.

  • Twitter Data Analytics (Shamanth Kumar, et al)

    This book provides methods for harnessing Twitter data to discover solutions to complex inquiries. The brief introduces the process of collecting data through Twitter's APIs and offers strategies for curating large datasets.

  • O'Reilly® Mining the Social Web, 2nd Edition (Matthew A. Russell)

    This book shows you how to answer these questions like how can you tap into social data and discover who's connecting with whom, which insights are lurking just beneath the surface, and what people are talking about?

  • Social Media Mining: An Introduction (Reza Zafarani, et al)

    This textbook introduces the unique problems arising from social media data and presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining.

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