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Task Intelligence for Search and Recommendation [Synthesis Lectures on Informati
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Item specifics
- Condition
- ISBN
- 9781636391496
- Subject Area
- Computers, Language Arts & Disciplines
- Publication Name
- Task Intelligence for Search and Recommendation
- Publisher
- Morgan & Claypool Publishers
- Item Length
- 9.3 in
- Subject
- Natural Language Processing, Library & Information Science / General, System Administration / Storage & Retrieval, Information Technology
- Publication Year
- 2021
- Series
- Synthesis Lectures on Information concepts, Retrieval, and Services Ser.
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Width
- 7.5 in
- Number of Pages
- 160 Pages
About this product
Product Identifiers
Publisher
Morgan & Claypool Publishers
ISBN-10
1636391494
ISBN-13
9781636391496
eBay Product ID (ePID)
26057261933
Product Key Features
Number of Pages
160 Pages
Publication Name
Task Intelligence for Search and Recommendation
Language
English
Subject
Natural Language Processing, Library & Information Science / General, System Administration / Storage & Retrieval, Information Technology
Publication Year
2021
Type
Textbook
Subject Area
Computers, Language Arts & Disciplines
Series
Synthesis Lectures on Information concepts, Retrieval, and Services Ser.
Format
Trade Paperback
Dimensions
Item Length
9.3 in
Item Width
7.5 in
Additional Product Features
Intended Audience
Scholarly & Professional
Dewey Edition
23
Dewey Decimal
005.56
Table Of Content
Preface Acknowledgments Introduction Task Frameworks, Expressions, and Representations Using Task Construct in IR Explicating Task Applying Task Information for Search and Recommendations Task-Based Evaluation Conclusions and Future Directions Bibliography Authors' Biographies
Synopsis
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 focuses on task intelligence in the context of search and recommendation., 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.
LC Classification Number
ZA3075
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