Metadata repository

About: Metadata repository is a research topic. Over the lifetime, 5841 publications have been published within this topic receiving 121778 citations.

Techniques for relating arbitrary metadata to media files

Abstract: A metadata text file is used to make media files searchable and rearrangeable. The metadata file includes a sequence of relaters that relate items of metadata to segments of media files. The metadata file can be searched for an item of metadata and the item's relater used to locate the corresponding media file segment, or be used to “play” the metadata files by displaying segments in an order depending on the order of the relaters. New combinations of media file segments may be made by adding, deleting, or reordering the relaters in the metadata text file. The metadata file is used to relate metadata to media files in systems for making fan vids, for comparing the text of a book with a movie, or that use temperature readings from pots being used to cook a recipe to locate sections of a cooking video.

Method and system of generating reference variations for directory assistance data

Abstract: Methods and systems of performing user input recognition are disclosed. A digital directory comprising listings is accessed. Metadata information is associated with individual listings describing the individual listings. The metadata information is modified to generate transformed metadata information. Therefore, the transformed metadata information is generated as a function of context information relating to a typical user interaction with the listings. Information is generated for aiding in an automated user input recognition process based on the transformed metadata information.

Functionalities for automatic metadata generation applications: a survey of metadata experts' opinions

Abstract: This paper reports on the automatic metadata generation applications (AMeGA) project's metadata expert survey. Automatic metadata generation research is reviewed and the study's methods, key findings and conclusions are presented. Participants anticipate greater accuracy with automatic techniques for technical metadata (e.g., ID, language, and format metadata) compared to metadata requiring intellectual discretion (e.g., subject and description metadata). Support for implementing automatic techniques paralleled anticipated accuracy results. Metadata experts are in favour of using automatic techniques, although they are generally not in favour of eliminating human evaluation or production for the more intellectually demanding metadata. Results are incorporated into Version 1.0 of the Recommended Functionalities for automatic metadata generation applications (Appendix A).

Method and Apparatus for Providing Script Data

Abstract: A method includes receiving script metadata extracted from a script for a program, wherein the script metadata includes clip metadata associated with a particular portion of the program, associating the clip metadata with a clip corresponding to the particular portion of the program, receiving a request to revise the clip metadata, revising the clip metadata in accordance with the request to revise the clip metadata to generate revised clip metadata associated with the clip, and generating a revised script using the revised clip metadata.

Knowledge-based metadata extraction from PostScript files

Abstract: The automatic document metadata extraction process is animportant task in a world where thousands of documents are just one``click'' away. Thus, powerful indices are necessary to support effective retrieval. The upcoming XML standard represents an important step in this direction as itssemistructuredrepresentation conveys document metadata together with the text of the document. For example, retrieval of scientific papers by authors or affiliations would be a straightforward tasks if papers were stored in XML.Unfortunately, today, the largest majority of documents on the web are available in forms that do not carryadditional semantics. Converting existing documents to a semistructured representation is time consuming and no automatic process can be easily applied. In this paper we discuss a system, based on a novel spatial/visualknowledge principle, for extracting metadata from scientific papers storedas PostScript files. Our system embeds the general knowledge about the graphical layout of a scientific paper to guide the metadata extraction process. Our system can effectively assist the automatic index creation for digital libraries.