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Content-based multimedia retrieval is a challenging research field with many unsolved problems. This monograph details concepts and algorithms for robust and efficient information retrieval of two different types of multimedia data: waveform-based music data and human motion data. It first examines several approaches in music information retrieval, in particular general strategies as well as efficient algorithms. The book then introduces a general and unified framework for motion analysis, retrieval, and classification, highlighting the design of suitable features, the notion of similarity used to compare data streams, and data organization.
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.
Due to increasing globalization and the explosion of media available on the Internet, computer techniques to organize, classify, and find desired media are becoming more and more relevant. One such technique to extract semantic information from multimedia data sources is Multimedia Information Retrieval (MMIR or MIR). MIR is a broad area covering both structural issues and intelligent content analysis and retrieval. These aspects must be integrated into a seamless whole, which involves expertise from a wide variety of fields. This book presents recent applications of MIR for content-based image retrieval, bioinformation analysis and processing, forensic multimedia retrieval techniques, and audio and music classification.
Everything you ever wanted to know about multimedia retrieval and management. This comprehensive book offers a full picture of the cutting-edge technologies necessary for a profound introduction to the field. Leading experts also cover a broad range of practical applications.
Novel processing and searching tools for the management of new multimedia documents have developed. Multimedia Information Retrieval (MIR) is an organic system made up of Text Retrieval (TR); Visual Retrieval (VR); Video Retrieval (VDR); and Audio Retrieval (AR) systems. So that each type of digital document may be analysed and searched by the elements of language appropriate to its nature, search criteria must be extended. Such an approach is known as the Content Based Information Retrieval (CBIR), and is the core of MIR. This novel content-based concept of information handling needs to be integrated with more traditional semantics. Multimedia Information Retrieval focuses on the tools of processing and searching applicable to the content-based management of new multimedia documents. Translated from Italian by Giles Smith, the book is divided into two parts. Part one discusses MIR and related theories, and puts forward new methodologies; part two reviews various experimental and operating MIR systems, and presents technical and practical conclusions. - Gives a complete, organic picture of MIR and CBIR - Proposes a novel conceptualisation around the ideas of Information Retrieval (IR) and digital document management in the context of Library and Information Science (LIS) - Relevant for both library and information science and information technology specialists
Multimedia Information Systems brings together in one place important contributions and up-to-date research results in this fast moving area. Multimedia Information Systems serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
At its very core multimedia information retrieval means the process of searching for and finding multimedia documents; the corresponding research field is concerned with building the best possible multimedia search engines. The intriguing bit here is that the query itself can be a multimedia excerpt: For example, when you walk around in an unknown place and stumble across an interesting landmark, would it not be great if you could just take a picture with your mobile phone and send it to a service that finds a similar picture in a database and tells you more about the building -- and about its significance, for that matter? This book goes further by examining the full matrix of a variety of query modes versus document types. How do you retrieve a music piece by humming? What if you want to find news video clips on forest fires using a still image? The text discusses underlying techniques and common approaches to facilitate multimedia search engines from metadata driven retrieval, via piggy-back text retrieval where automated processes create text surrogates for multimedia, automated image annotation and content-based retrieval. The latter is studied in great depth looking at features and distances, and how to effectively combine them for efficient retrieval, to a point where the readers have the ingredients and recipe in their hands for building their own multimedia search engines. Supporting users in their resource discovery mission when hunting for multimedia material is not a technological indexing problem alone. We look at interactive ways of engaging with repositories through browsing and relevance feedback, roping in geographical context, and providing visual summaries for videos. The book concludes with an overview of state-of-the-art research projects in the area of multimedia information retrieval, which gives an indication of the research and development trends and, thereby, a glimpse of the future world. Table of Contents: What is Multimedia Information Retrieval? / Basic Multimedia Search Technologies / Content-based Retrieval in Depth / Added Services / Multimedia Information Retrieval Research / Summary
Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic. This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.
Multimedia Information Systems brings together in one place important contributions and up-to-date research results in this fast moving area. Multimedia Information Systems serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
"This book offers an in-depth explanation of multimedia technologies within their many specific application areas as well as presenting developing trends for the future"--Provided by publisher.