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8 produkter
8 produkter
Del 10478 - Lecture Notes in Computer Science
Text Processing
FIRE 2016 International Workshop, Kolkata, India, December 7–10, 2016, Revised Selected Papers
Häftad, Engelska, 2018
545 kr
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This book constitutes the refereed post-conference proceedings of a Workshop focussing on Text Processing, held at the Forum for Information Retrieval Evaluation, FIRE 2016, in Kolkata, India, in December 2016. 16 full papers have been selected for inclusion in the book out of 19 submissions. The papers refer to the following seven tracks: Consumer Health Information Search (CHIS), Detecting Paraphrases in Indian Languages (DPIL), Information Extraction from Microblogs Posted during Disasters, Persian Plagiarism Detection (PersianPlagDet), Personality Recognition in SOurce COde (PR-SOCO), Shared Task on Mixed Script Information Retrieval (MSIR), and Shared Task on Code Mix Entity Extraction in Indian Languages (CMEE-IL).
E-bok
Engelska, 2018734 kr
Läs direkt efter köp
This book constitutes the refereed post-conference proceedings of a Workshop focussing on Text Processing, held at the Forum for Information Retrieval Evaluation, FIRE 2016, in Kolkata, India, in December 2016. 16 full papers have been selected for inclusion in the book out of 19 submissions. The papers refer to the following seven tracks: Consumer Health Information Search (CHIS), Detecting Paraphrases in Indian Languages (DPIL), Information Extraction from Microblogs Posted during Disasters, Persian Plagiarism Detection (PersianPlagDet), Personality Recognition in SOurce COde (PR-SOCO), Shared Task on Mixed Script Information Retrieval (MSIR), and Shared Task on Code Mix Entity Extraction in Indian Languages (CMEE-IL).
562 kr
Skickas inom 10-15 vardagar
This book constitutes the thoroughly refereed post-proceedings of the Second and Third Workshops of the Forum for Information Retrieval Evaluation, FIRE 2010 and 2011, on Multi-lingual Information Access in South Asian Languages held in Gandhinagar, India, in February 2010 and in Bombay, India, in December 2011. The volume brings together revised and expanded versions of a total of 29 papers. The papers are organized in topical sections on various aspects of multi-lingual information access.
708 kr
Läs direkt efter köp
This book constitutes the thoroughly refereed post-proceedings of the Second and Third Workshops of the Forum for Information Retrieval Evaluation, FIRE 2010 and 2011, on Multi-lingual Information Access in South Asian Languages held in Gandhinagar, India, in February 2010 and in Bombay, India, in December 2011. The volume brings together revised and expanded versions of a total of 29 papers. The papers are organized in topical sections on various aspects of multi-lingual information access.
Inbunden, Engelska, 2019
1 116 kr
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This book describes recent advances in text summarization, identifies remaining gaps and challenges, and proposes ways to overcome them. It begins with one of the most frequently discussed topics in text summarization – ‘sentence extraction’ –, examines the effectiveness of current techniques in domain-specific text summarization, and proposes several improvements. In turn, the book describes the application of summarization in the legal and scientific domains, describing two new corpora that consist of more than 100 thousand court judgments and more than 20 thousand scientific articles, with the corresponding manually written summaries. The availability of these large-scale corpora opens up the possibility of using the now popular data-driven approaches based on deep learning. The book then highlights the effectiveness of neural sentence extraction approaches, which perform just as well as rule-based approaches, but without the need for any manual annotation. As a next step, multiple techniques for creating ensembles of sentence extractors – which deliver better and more robust summaries – are proposed. In closing, the book presents a neural network-based model for sentence compression. Overall the book takes readers on a journey that begins with simple sentence extraction and ends in abstractive summarization, while also covering key topics like ensemble techniques and domain-specific summarization, which have not been explored in detail prior to this.
E-bok
Engelska, 20191 408 kr
Läs direkt efter köp
This book describes recent advances in text summarization, identifies remaining gaps and challenges, and proposes ways to overcome them. It begins with one of the most frequently discussed topics in text summarization – ‘sentence extraction’ –, examines the effectiveness of current techniques in domain-specific text summarization, and proposes several improvements. In turn, the book describes the application of summarization in the legal and scientific domains, describing two new corpora that consist of more than 100 thousand court judgments and more than 20 thousand scientific articles, with the corresponding manually written summaries. The availability of these large-scale corpora opens up the possibility of using the now popular data-driven approaches based on deep learning. The book then highlights the effectiveness of neural sentence extraction approaches, which perform just as well as rule-based approaches, but without the need for any manual annotation. As a next step, multiple techniques for creating ensembles of sentence extractors – which deliver better and more robust summaries – are proposed. In closing, the book presents a neural network-based model for sentence compression. Overall the book takes readers on a journey that begins with simple sentence extraction and ends in abstractive summarization, while also covering key topics like ensemble techniques and domain-specific summarization, which have not been explored in detail prior to this.
Häftad, Engelska, 2020
1 116 kr
Skickas inom 10-15 vardagar
This book describes recent advances in text summarization, identifies remaining gaps and challenges, and proposes ways to overcome them. It begins with one of the most frequently discussed topics in text summarization – ‘sentence extraction’ –, examines the effectiveness of current techniques in domain-specific text summarization, and proposes several improvements. In turn, the book describes the application of summarization in the legal and scientific domains, describing two new corpora that consist of more than 100 thousand court judgments and more than 20 thousand scientific articles, with the corresponding manually written summaries. The availability of these large-scale corpora opens up the possibility of using the now popular data-driven approaches based on deep learning. The book then highlights the effectiveness of neural sentence extraction approaches, which perform just as well as rule-based approaches, but without the need for any manual annotation. As a next step, multiple techniques for creating ensembles of sentence extractors – which deliver better and more robust summaries – are proposed. In closing, the book presents a neural network-based model for sentence compression. Overall the book takes readers on a journey that begins with simple sentence extraction and ends in abstractive summarization, while also covering key topics like ensemble techniques and domain-specific summarization, which have not been explored in detail prior to this.
Inbunden, Engelska, 2026
1 372 kr
Kommande
Volume I of this two-volume series lays the foundational pillars of data science, combining statistical theory, mathematical essentials, and practical computing skills required for modern data analysis. Designed as a comprehensive entry point, this volume equips readers with the conceptual and computational tools needed to understand, explore, and model data before progressing to advanced machine learning and high-dimensional methods.The volume begins with hands-on introductions to R and Python, enabling readers with no prior programming experience to immediately engage in data exploration and analysis. Core probabilistic and statistical concepts probability theory, probability distributions, sampling, and parametric inference are developed systematically, ensuring a strong analytical backbone for data-driven reasoning. Essential mathematical tools, particularly linear algebra, are presented in an intuitive manner tailored to data science applications.Emphasis is placed on exploratory data analysis, regression modeling, causal inference, and business-oriented statistical modeling, supported throughout by real-world case studies and applied examples. Mathematical rigor is balanced with intuition, and every major concept is reinforced using executable R and Python code.This volume is ideal for undergraduate and postgraduate students, researchers, and practitioners seeking a structured and application-driven introduction to data science and business analytics. It serves as both a classroom-ready textbook and a self-study reference, preparing readers for advanced modeling techniques covered in Volume II.