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Statistical Language Models for Information Retrieval

been a central research problem in information retrieval for several decades. In the past ten years, a new generation of retrieval models;

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Text Retrieval and Filtering

as a secondary text for a graduate level course on Information Retrieval or Linguistics, and as a reference for researchers and practitioners;

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Textual Information Access

exploration. Contents Part 1: Information Retrieval 1. Probabilistic Models for Information Retrieval, Stephane Clinchant and Eric Gaussier. 2;

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An Introduction to Neural Information Retrieval

Neural models have been employed in many Information Retrieval scenarios, including ad-hoc retrieval, recommender systems, multi-media;

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Bayesian Speech & Language Processing

and latent topic models, along with applications including automatic speech recognition, speaker verification, and information retrieval;

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Foundations of Statistical Natural Language Processing

comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for;

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Machine Learning for Text

intersecting topics of information retrieval, machine learning, and natural language processing. Particular importance is placed on deep learning;

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Information Retrieval

for Meaning and Structure Cross-language Information Retrieval Performance Issues in Parallel Computing for Information Retrieval This book;

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Graph-based Natural Language Processing and Information Retrieval

Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these;

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Experiment and Evaluation in Information Retrieval Models

Experiment and Evaluation in Information Retrieval Models explores different algorithms for the application of evolutionary computation to;

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Neural Networks for Natural Language Processing

highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and;

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Neural Networks for Natural Language Processing

highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and;

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A Feature-Centric View of Information Retrieval

and industry. Such large collections pose a new set of challenges for information retrieval researchers. In this work, Metzler describes;

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Search Engines

Search Engines: Information Retrieval in Practice is ideal for introductory information retrieval courses at the undergraduate and graduate;

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Knowledge Organization and Classification in International Information Retrieval

in International Information Retrieval examines current efforts to deal with the increasing globalization of information and knowledge. International;

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Information Retrieval Models

Information Retrieval (IR) models are a core component of IR research and IR systems. The past decade brought a consolidation of the family;

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Predicting Information Retrieval Performance

distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and;

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Predicting Information Retrieval Performance

distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and;

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Statistical Language and Speech Processing

; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural;

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Statistical Language and Speech Processing

; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural;

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Multidisciplinary Information Retrieval

research areas: information retrieval, semantic web technologies for IR, natural language processing for IR, and large-scale or distributed;

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Handbook on Neural Information Processing

Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning Kernel methods for structured data Multiple;

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Multimedia Information Retrieval

Novel processing and searching tools for the management of new multimedia documents have developed. Multimedia Information Retrieval (MIR;

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Introduction to Information Retrieval and Quantum Mechanics

for modeling information representation and retrieval processes. The book is divided into four chapters. Chapter 1 illustrates the main;

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Introduction to Information Retrieval and Quantum Mechanics

for modeling information representation and retrieval processes. The book is divided into four chapters. Chapter 1 illustrates the main;

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The Geometry of Information Retrieval

Information retrieval, IR, the science of extracting information from any potential source, can be viewed in a number of ways: logical;

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Information Retrieval

requests? The authors answer these and other key information retrieval design and implementation questions. This book is not yet another high;

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