Big Data Analytics

Big Data Analytics
Author: Anirban Mondal
Publisher: Springer
Total Pages: 429
Release: 2018-12-11
Genre: Computers
ISBN: 3030047806

This book constitutes the refereed proceedings of the 6th International Conference on Big Data analytics, BDA 2018, held in Warangal, India, in December 2018. The 29 papers presented in this volume were carefully reviewed and selected from 93 submissions. The papers are organized in topical sections named: big data analytics: vision and perspectives; financial data analytics and data streams; web and social media data; big data systems and frameworks; predictive analytics in healthcare and agricultural domains; and machine learning and pattern mining.

Information Retrieval and Management: Concepts, Methodologies, Tools, and Applications

Information Retrieval and Management: Concepts, Methodologies, Tools, and Applications
Author: Management Association, Information Resources
Publisher: IGI Global
Total Pages: 2373
Release: 2018-01-05
Genre: Computers
ISBN: 1522551921

With the increased use of technology in modern society, high volumes of multimedia information exists. It is important for businesses, organizations, and individuals to understand how to optimize this data and new methods are emerging for more efficient information management and retrieval. Information Retrieval and Management: Concepts, Methodologies, Tools, and Applications is an innovative reference source for the latest academic material in the field of information and communication technologies and explores how complex information systems interact with and affect one another. Highlighting a range of topics such as knowledge discovery, semantic web, and information resources management, this multi-volume book is ideally designed for researchers, developers, managers, strategic planners, and advanced-level students.

Information Retrieval

Information Retrieval
Author: Ayse Goker
Publisher: John Wiley & Sons
Total Pages: 320
Release: 2009-12-15
Genre: Technology & Engineering
ISBN: 9780470033630

This book is an essential reference to cutting-edge issues and future directions in information retrieval Information retrieval (IR) can be defined as the process of representing, managing, searching, retrieving, and presenting information. Good IR involves understanding information needs and interests, developing an effective search technique, system, presentation, distribution and delivery. The increased use of the Web and wider availability of information in this environment led to the development of Web search engines. This change has brought fresh challenges to a wider variety of users’ needs, tasks, and types of information. Today, search engines are seen in enterprises, on laptops, in individual websites, in library catalogues, and elsewhere. Information Retrieval: Searching in the 21st Century focuses on core concepts, and current trends in the field. This book focuses on: Information Retrieval Models User-centred Evaluation of Information Retrieval Systems Multimedia Resource Discovery Image Users’ Needs and Searching Behaviour Web Information Retrieval Mobile Search Context and Information Retrieval Text Categorisation and Genre in Information Retrieval Semantic Search The Role of Natural Language Processing in Information Retrieval: Search for Meaning and Structure Cross-language Information Retrieval Performance Issues in Parallel Computing for Information Retrieval This book is an invaluable reference for graduate students on IR courses or courses in related disciplines (e.g. computer science, information science, human-computer interaction, and knowledge management), academic and industrial researchers, and industrial personnel tracking information search technology developments to understand the business implications. Intermediate-advanced level undergraduate students on IR or related courses will also find this text insightful. Chapters are supplemented with exercises to stimulate further thinking.

Information Retrieval and Hypertext

Information Retrieval and Hypertext
Author: Maristella Agosti
Publisher: Springer Science & Business Media
Total Pages: 287
Release: 2012-12-06
Genre: Computers
ISBN: 1461313732

Information Retrieval (IR) has concentrated on the development of information management systems to support user retrieval from large collections of homogeneous textual material. A variety of approaches have been tried and tested with varying degrees of success over many decades of research. Hypertext (HT) systems, on the other hand, provide a retrieval paradigm based on browsing through a structured information space, following pre-defined connections between information fragments until an information need is satisfied, or appears to be. Information Retrieval and Hypertext addresses the confluence of the areas of IR and HT and explores the work done to date in applying techniques from one area, to the other leading to the development of `hypertext information retrieval' (HIR) systems. An important aspect of the work in IR/HT and in any user-centred information system is the emergence of multimedia information and such multimedia information is treated as an integral information type in this text. The contributed chapters cover the development of integrated hypertext information retrieval models, and the application of IR and HT techniques in hypertext construction and the approaches that can be taken in searching HIR systems. These chapters are complemented by two overview chapters covering, respectively, information retrieval and hypertext research and developments. Information Retrieval and Hypertext is important as it is the first text to directly address the combined searching/browsing paradigm of information discovery which is becoming so important in modern computing environments. It will be of interest to researchers and professionals working in a range of areas related to information discovery.

Learning to Rank for Information Retrieval

Learning to Rank for Information Retrieval
Author: Tie-Yan Liu
Publisher: Springer Science & Business Media
Total Pages: 282
Release: 2011-04-29
Genre: Computers
ISBN: 3642142672

Due to the fast growth of the Web and the difficulties in finding desired information, efficient and effective information retrieval systems have become more important than ever, and the search engine has become an essential tool for many people. The ranker, a central component in every search engine, is responsible for the matching between processed queries and indexed documents. Because of its central role, great attention has been paid to the research and development of ranking technologies. In addition, ranking is also pivotal for many other information retrieval applications, such as collaborative filtering, definition ranking, question answering, multimedia retrieval, text summarization, and online advertisement. Leveraging machine learning technologies in the ranking process has led to innovative and more effective ranking models, and eventually to a completely new research area called “learning to rank”. Liu first gives a comprehensive review of the major approaches to learning to rank. For each approach he presents the basic framework, with example algorithms, and he discusses its advantages and disadvantages. He continues with some recent advances in learning to rank that cannot be simply categorized into the three major approaches – these include relational ranking, query-dependent ranking, transfer ranking, and semisupervised ranking. His presentation is completed by several examples that apply these technologies to solve real information retrieval problems, and by theoretical discussions on guarantees for ranking performance. This book is written for researchers and graduate students in both information retrieval and machine learning. They will find here the only comprehensive description of the state of the art in a field that has driven the recent advances in search engine development.

Introduction to Information Retrieval

Introduction to Information Retrieval
Author: Christopher D. Manning
Publisher: Cambridge University Press
Total Pages:
Release: 2008-07-07
Genre: Computers
ISBN: 1139472100

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

Advances in Information Retrieval

Advances in Information Retrieval
Author: Center for Intelligent Information Retrieval
Publisher: Springer Science & Business Media
Total Pages: 326
Release: 2000-04-30
Genre: Computers
ISBN: 0792378121

The NSF Center for Intelligent Information Retrieval (CIIR) was formed in the Computer Science Department of the University of Massachusetts, Amherst, in 1992. Through its efforts in basic research, applied research, and technology transfer, the CIIR has become known internationally as one of the leading research groups in the area of information retrieval. The CIIR focuses on research that results in more effective and efficient access and discovery in large, heterogeneous, distributed text and multimedia databases. The scope of the work that is done in the CIIR is broad and goes significantly beyond `traditional' areas of information retrieval such as retrieval models, cross-lingual search, and automatic query expansion. The research includes both low-level systems issues such as the design of protocols and architectures for distributed search, as well as more human-centered topics such as user interface design, visualization and data mining with text, and multimedia retrieval. Advances in Information Retrieval: Recent Research from the Center for Intelligent Information Retrieval is a collection of papers that covers a wide variety of topics in the general area of information retrieval. Together, they represent a snapshot of the state of the art in information retrieval at the turn of the century and at the end of a decade that has seen the advent of the World-Wide Web. The papers provide overviews and in-depth analysis of theory and experimental results. This book can be used as source material for graduate courses in information retrieval, and as a reference for researchers and practitioners in industry.