Author: Diane Rasmussen Neal
Publisher: Walter de Gruyter
Published: 2012-10-30
Total Pages: 440
ISBN-13: 3110260581
DOWNLOAD EBOOKThe scope of this volume will encompass a collection of research papers related to indexing and retrieval of online non-text information. In recent years, the Internet has seen an exponential increase in the number of documents placed online that are not in textual format. These documents appear in a variety of contexts, such as user-generated content sharing websites, social networking websites etc. and formats, including photographs, videos, recorded music, data visualizations etc. The prevalence of these contexts and data formats presents a particularly challenging task to information indexing and retrieval research due to many difficulties, such as assigning suitable semantic metadata, processing and extracting non-textual content automatically, and designing retrieval systems that "speak in the native language" of non-text documents.
Book Synopsis Indexing and Retrieval of Non-Text Information by : Diane Rasmussen Neal
Download or read book Indexing and Retrieval of Non-Text Information written by Diane Rasmussen Neal and published by Walter de Gruyter. This book was released on 2012-10-30 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scope of this volume will encompass a collection of research papers related to indexing and retrieval of online non-text information. In recent years, the Internet has seen an exponential increase in the number of documents placed online that are not in textual format. These documents appear in a variety of contexts, such as user-generated content sharing websites, social networking websites etc. and formats, including photographs, videos, recorded music, data visualizations etc. The prevalence of these contexts and data formats presents a particularly challenging task to information indexing and retrieval research due to many difficulties, such as assigning suitable semantic metadata, processing and extracting non-textual content automatically, and designing retrieval systems that "speak in the native language" of non-text documents.