Natural Language Processing for Online Applications: Text Retrieval, Extraction, and Categorization

Natural language processing for online a

📁 Natural language processing for online applications: text retrieval, extraction and categorization

✍ Peter Jackson, Isabelle Moulinier 📂 Library 📅 2002 🏛 John Benjamins Publishing Co 🌐 English

This text covers the emerging technologies of document retrieval, information extraction, and text categorization in a way which highlights commonalities in terms of both general principles and practical issues. It seeks to satisfy a need on the part of technology practitioners in the internet space

Natural Language Processing and Informat

📁 Natural Language Processing and Information Retrieval; Principles and Applications

✍ Muskan Garg, Sandeep Kumar, Abdul Khader Jilani Saudagar 📂 Library 📅 2023 🏛 CRC Press 🌐 English

This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, co

Natural Language Processing and Informat

📁 Natural Language Processing and Information Retrieval; Principles and Applications

✍ Muskan Garg, Sandeep Kumar, Abdul Khader Jilani Saudagar 📂 Library 📅 2023 🏛 Taylor & Francis Group 🌐 English

This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, co

Advanced Applications of Natural Languag

📁 Advanced Applications of Natural Language Processing for Performing Information Extraction

✍ Mário Rodrigues, António Teixeira (auth.) 📂 Library 📅 2015 🏛 Springer International Publishing 🌐 English

<p><p>This book explains how can be created information extraction (IE) applications that are able to tap the vast amount of relevant information available in natural language sources: Internet pages, official documents such as laws and regulations, books and newspapers, and social web. Readers are

Learning to Rank for Information Retriev

📁 Learning to Rank for Information Retrieval and Natural Language Processing

✍ Hang Li 📂 Library 📅 2011 🏛 Morgan & Claypool Publishers 🌐 English

Learning to Rank for Information Retriev

📁 Learning to Rank for Information Retrieval and Natural Language Processing

✍ Hang Li 📂 Library 📅 2011 🏛 Morgan & Claypool Publishers 🌐 English