Task Intelligence for Search and Recommendation

Task Intelligence for Search and Recommendation PDF Author: Chirag Shah
Publisher: Springer Nature
ISBN: 3031023269
Category : Computers
Languages : en
Pages : 140

Get Book

Book Description
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.

Task Intelligence for Search and Recommendation

Task Intelligence for Search and Recommendation PDF Author: Chirag Shah
Publisher: Springer Nature
ISBN: 3031023269
Category : Computers
Languages : en
Pages : 140

Get Book

Book Description
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.

Deep Learning for Matching in Search and Recommendation

Deep Learning for Matching in Search and Recommendation PDF Author: Jun Xu
Publisher:
ISBN: 9781680837063
Category :
Languages : en
Pages : 200

Get Book

Book Description
This survey gives a systematic and comprehensive introduction to the deep matching models for search and recommendation.

Robotics and Rehabilitation Intelligence

Robotics and Rehabilitation Intelligence PDF Author: Jianhua Qian
Publisher: Springer Nature
ISBN: 9813349328
Category : Computers
Languages : en
Pages : 432

Get Book

Book Description
This 2-volume set constitutes the refereed proceedings of 1st International Conference on Robotics and Rehabilitation Intelligence, ICRRI 2020, held in Fushun, China, in September 2020. The 56 full and 4 short papers were carefully reviewed and selected from 188 submissions. The papers are divided into the following topical sections. In the first volume: Rehabilitation robotics and safety; machine vision application; electric drive and power system fault diagnosis; robust stability and stabilization; intelligent method application; intelligent control and perception; smart remanufacturing and industrial intelligence; and intelligent control of integrated energy system. In the second volume: smart healthcare and intelligent information processing; human-robot interaction; multi-robot systems and control; robot design and control; robotic vision and machine intelligence; optimization method in monitoring; advanced process control in petrochemical process; and rehabilitation intelligence.

2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT)

2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT) PDF Author: IEEE Staff
Publisher:
ISBN: 9781665401197
Category :
Languages : en
Pages :

Get Book

Book Description
The 4th International Conference on Smart Systems and Inventive Technology (ICSSIT 2022) is being organized by Francis Xavier Engineering College, Tirunelveli, India during 20 22, January 2022 ICSSIT 2022 will provide an outstanding international forum for sharing knowledge and results in all fields of science, engineering and Technology ICSSIT provides quality key experts who provide an opportunity in bringing up innovative ideas Recent updates in the field of technology will be a platform for the upcoming researchers The conference will be Complete, Concise, Clear and Cohesive in terms of research related to Smart Systems and Technology

Collaborative Information Seeking

Collaborative Information Seeking PDF Author: Preben Hansen
Publisher: Springer
ISBN: 3319189883
Category : Computers
Languages : en
Pages : 226

Get Book

Book Description
Compiled by world- class leaders in the field of collaborative information retrieval and search (CIS), this book centres on the notion that information seeking is not always a solitary activity and working in collaboration to perform information-seeking tasks should be studied and supported. Covering aspects of theories, models, and applications the book is divided in three parts: · Best Practices and Studies: providing an overview of current knowledge and state-of-the-art in the field. · New Domains: covers some of the new and exciting opportunities of applying CIS · New Thoughts: focuses on new research directions by scholars from academia and industry from around the world. Collaborative Information Seeking provides a valuable reference for student, teachers, and researchers interested in the area of collaborative work, information seeking/retrieval, and human-computer interaction.

Recommender Systems Handbook

Recommender Systems Handbook PDF Author: Francesco Ricci
Publisher: Springer
ISBN: 148997637X
Category : Computers
Languages : en
Pages : 1003

Get Book

Book Description
This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.

Programming Collective Intelligence

Programming Collective Intelligence PDF Author: Toby Segaran
Publisher: "O'Reilly Media, Inc."
ISBN: 0596550685
Category : Computers
Languages : en
Pages : 361

Get Book

Book Description
Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect

Encyclopedia of Machine Learning

Encyclopedia of Machine Learning PDF Author: Claude Sammut
Publisher: Springer Science & Business Media
ISBN: 0387307680
Category : Computers
Languages : en
Pages : 1061

Get Book

Book Description
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.

Intelligence Analysis for Tomorrow

Intelligence Analysis for Tomorrow PDF Author: National Research Council
Publisher: National Academies Press
ISBN: 0309163420
Category : Social Science
Languages : en
Pages : 116

Get Book

Book Description
The intelligence community (IC) plays an essential role in the national security of the United States. Decision makers rely on IC analyses and predictions to reduce uncertainty and to provide warnings about everything from international diplomatic relations to overseas conflicts. In today's complex and rapidly changing world, it is more important than ever that analytic products be accurate and timely. Recognizing that need, the IC has been actively seeking ways to improve its performance and expand its capabilities. In 2008, the Office of the Director of National Intelligence (ODNI) asked the National Research Council (NRC) to establish a committee to synthesize and assess evidence from the behavioral and social sciences relevant to analytic methods and their potential application for the U.S. intelligence community. In Intelligence Analysis for Tomorrow: Advances from the Behavioral and Social Sciences, the NRC offers the Director of National Intelligence (DNI) recommendations to address many of the IC's challenges. Intelligence Analysis for Tomorrow asserts that one of the most important things that the IC can learn from the behavioral and social sciences is how to characterize and evaluate its analytic assumptions, methods, technologies, and management practices. Behavioral and social scientific knowledge can help the IC to understand and improve all phases of the analytic cycle: how to recruit, select, train, and motivate analysts; how to master and deploy the most suitable analytic methods; how to organize the day-to-day work of analysts, as individuals and teams; and how to communicate with its customers. The report makes five broad recommendations which offer practical ways to apply the behavioral and social sciences, which will bring the IC substantial immediate and longer-term benefits with modest costs and minimal disruption.

House and Senate Documents

House and Senate Documents PDF Author: Virginia. General Assembly
Publisher:
ISBN:
Category : Virginia
Languages : en
Pages : 1334

Get Book

Book Description