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Task Intelligence for Search and Recommendation, Shah Chirag, White Ryen W.


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Цена: 9563.00р.
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Автор: Shah Chirag, White Ryen W.
Название:  Task Intelligence for Search and Recommendation
ISBN: 9781636391496
Издательство: Mare Nostrum (Eurospan)
Классификация:


ISBN-10: 1636391494
Обложка/Формат: Paperback
Страницы: 160
Вес: 0.29 кг.
Дата издания: 30.06.2021
Серия: Synthesis lectures on information concepts, retrieval, and services
Язык: English
Размер: 23.50 x 19.05 x 0.89 cm
Читательская аудитория: Professional and scholarly
Ключевые слова: Computer science,Information retrieval,Natural language & machine translation, COMPUTERS / Information Technology,COMPUTERS / Natural Language Processing,COMPUTERS / System Administration / Storage & Retrieval
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Поставляется из: Англии
Описание: While great strides have been made in the field of search and recommendation, there are still challenges and opportunities to address information access issues that involve solving tasks and accomplishing goals for a wide variety of users. Specifically, we lack intelligent systems that can detect not only the request an individual is making (what), but also understand and utilize the intention (why) and strategies (how) while providing information and enabling task completion. Many scholars in the fields of information retrieval, recommender systems, productivity (especially in task management and time management), and artificial intelligence have recognized the importance of extracting and understanding people's tasks and the intentions behind performing those tasks in order to serve them better. However, we are still struggling to support them in task completion, e.g., in search and assistance, and it has been challenging to move beyond single-query or single-turn interactions. The proliferation of intelligent agents has unlocked new modalities for interacting with information, but these agents will need to be able to work understanding current and future contexts and assist users at task level. This book will focus on task intelligence in the context of search and recommendation. Chapter 1 introduces readers to the issues of detecting, understanding, and using task and task-related information in an information episode (with or without active searching). This is followed by presenting several prominent ideas and frameworks about how tasks are conceptualized and represented in Chapter 2. In Chapter 3, the narrative moves to showing how task type relates to user behaviors and search intentions. A task can be explicitly expressed in some cases, such as in a to-do application, but often it is unexpressed. Chapter 4 covers these two scenarios with several related works and case studies. Chapter 5 shows how task knowledge and task models can contribute to addressing emerging retrieval and recommendation problems. Chapter 6 covers evaluation methodologies and metrics for task-based systems, with relevant case studies to demonstrate their uses. Finally, the book concludes in Chapter 7, with ideas for future directions in this important research area.


Spatio-Temporal Recommendation in Social Media

Автор: Hongzhi Yin; Bin Cui
Название: Spatio-Temporal Recommendation in Social Media
ISBN: 9811007470 ISBN-13(EAN): 9789811007477
Издательство: Springer
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Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book covers the major fundamentals of and the latest research on next-generation spatio-temporal recommendation systems in social media.

Point-of-Interest Recommendation in Location-Based Social Networks

Автор: Zhao
Название: Point-of-Interest Recommendation in Location-Based Social Networks
ISBN: 9811313482 ISBN-13(EAN): 9789811313486
Издательство: Springer
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Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book systematically introduces Point-of-interest (POI) recommendations in Location-based Social Networks (LBSNs). Lastly, the book discusses future research directions in this area. This book is intended for professionals involved in POI recommendation and graduate students working on problems related to location-based services.

Hands-On Recommendation Systems with Python

Автор: Banik Rounak
Название: Hands-On Recommendation Systems with Python
ISBN: 1788993756 ISBN-13(EAN): 9781788993753
Издательство: Неизвестно
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Цена: 6068.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Recommendation systems are at the heart of almost every internet business today; from Facebook to Netflix to Amazon. Providing good recommendations, whether it`s friends, movies or groceries, goes a long way in defining user experience and enticing your customers to use and buy from your platform. This book teaches you to do just that.

Fintech and Data Privacy in Germany: An Empirical Analysis with Policy Recommendations

Автор: Dorfleitner Gregor, Hornuf Lars
Название: Fintech and Data Privacy in Germany: An Empirical Analysis with Policy Recommendations
ISBN: 3030313379 ISBN-13(EAN): 9783030313371
Издательство: Springer
Цена: 16769.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 1. Introduction.- 2. Players in the German FinTech industry.- 3. FinTechs and data protection.- 4. FinTechs and data protection after the implementation of the GDPR.- 5. FinTech business models.- 6. Need for regulation in the German FinTech market.- 7. A summary in eleven theses.

Task Intelligence for Search and Recommendation

Автор: Shah Chirag, White Ryen W.
Название: Task Intelligence for Search and Recommendation
ISBN: 1636391516 ISBN-13(EAN): 9781636391519
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 12751.00 р.
Наличие на складе: Нет в наличии.

Описание: While great strides have been made in the field of search and recommendation, there are still challenges and opportunities to address information access issues that involve solving tasks and accomplishing goals for a wide variety of users. Specifically, we lack intelligent systems that can detect not only the request an individual is making (what), but also understand and utilize the intention (why) and strategies (how) while providing information and enabling task completion. Many scholars in the fields of information retrieval, recommender systems, productivity (especially in task management and time management), and artificial intelligence have recognized the importance of extracting and understanding people's tasks and the intentions behind performing those tasks in order to serve them better. However, we are still struggling to support them in task completion, e.g., in search and assistance, and it has been challenging to move beyond single-query or single-turn interactions. The proliferation of intelligent agents has unlocked new modalities for interacting with information, but these agents will need to be able to work understanding current and future contexts and assist users at task level. This book will focus on task intelligence in the context of search and recommendation. Chapter 1 introduces readers to the issues of detecting, understanding, and using task and task-related information in an information episode (with or without active searching). This is followed by presenting several prominent ideas and frameworks about how tasks are conceptualized and represented in Chapter 2. In Chapter 3, the narrative moves to showing how task type relates to user behaviors and search intentions. A task can be explicitly expressed in some cases, such as in a to-do application, but often it is unexpressed. Chapter 4 covers these two scenarios with several related works and case studies. Chapter 5 shows how task knowledge and task models can contribute to addressing emerging retrieval and recommendation problems. Chapter 6 covers evaluation methodologies and metrics for task-based systems, with relevant case studies to demonstrate their uses. Finally, the book concludes in Chapter 7, with ideas for future directions in this important research area.

Advances in Bias and Fairness in Information Retrieval: Second International Workshop on Algorithmic Bias in Search and Recommendation, Bias 2021, Luc

Автор: Boratto Ludovico, Faralli Stefano, Marras Mirko
Название: Advances in Bias and Fairness in Information Retrieval: Second International Workshop on Algorithmic Bias in Search and Recommendation, Bias 2021, Luc
ISBN: 3030788172 ISBN-13(EAN): 9783030788179
Издательство: Springer
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes refereed proceedings of the Second International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2021, held in April, 2021.

Personalized Task Recommendation in Crowdsourcing Systems

Автор: David Geiger
Название: Personalized Task Recommendation in Crowdsourcing Systems
ISBN: 3319222902 ISBN-13(EAN): 9783319222905
Издательство: Springer
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Цена: 11179.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book examines the principles of and advances in personalized task recommendation in crowdsourcing systems, with the aim of improving their overall efficiency.

Personalized Task Recommendation in Crowdsourcing Systems

Автор: David Geiger
Название: Personalized Task Recommendation in Crowdsourcing Systems
ISBN: 3319370588 ISBN-13(EAN): 9783319370583
Издательство: Springer
Рейтинг:
Цена: 11179.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book examines the principles of and advances in personalized task recommendation in crowdsourcing systems, with the aim of improving their overall efficiency.

Recommendation systems in software engineering

Название: Recommendation systems in software engineering
ISBN: 366252404X ISBN-13(EAN): 9783662524046
Издательство: Springer
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Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book surveys and analyzes information on recommendation systems in software engineering, in separate sections on Techniques, Evaluation and Applications. A supplemental website offers additional material, including lecture slides, source code and more.

Music Recommendation and Discovery

Автор: ?scar Celma
Название: Music Recommendation and Discovery
ISBN: 3642439535 ISBN-13(EAN): 9783642439537
Издательство: Springer
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Цена: 9781.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: As more and more of us use automated music recommendation, this book describes how these systems work, explores some of their limitations, offers techniques for evaluating their effectiveness, and uses real-life examples to show how to build them effectively.

Recommendation Systems in Software Engineering

Автор: Martin P. Robillard; Walid Maalej; Robert J. Walke
Название: Recommendation Systems in Software Engineering
ISBN: 3642451349 ISBN-13(EAN): 9783642451348
Издательство: Springer
Рейтинг:
Цена: 20962.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book surveys and analyzes information on recommendation systems in software engineering, in separate sections on Techniques, Evaluation and Applications. A supplemental website offers additional material, including lecture slides, source code and more.


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