Multimedia Search


Feedsee Search : Multimedia Search : Digital media server helped consumers categorize, manage, and locate entertainment content

In 2007, Hitachi and Blue Peach announced the Blue Peach NAS Digital Media Server with next generation multimedia search provided by the Hitachi Entier relational database management system, which delivered an application-optimized platform with powerful local search capabilities. The addition of the Entier database provided developers using the Blue Peach Digital Media Server solution the ability to design devices that allowed consumers to search for the digital entertainment content they wanted in a more natural manner. The platform for manufacturers of digital media devices contained content management functionality thanks to Entier. This functionality allowed users to personalize search by tagging, browsing and finding content the way they wanted: quickly and efficiently. With Entier, the solution enabled consumers to network their home entertainment devices to search and gain access to music, movies, and other digital files from any networked device in the home.

Searching digital media server collections can be done through various ways to help users locate specific content effectively. Here are some common methods:

  1. Keyword Search: This is the simplest and most common method. Users enter a keyword or phrase, and the server searches through file names, tags, and sometimes even the content of files for matches.
  2. Advanced Search: This involves using multiple criteria to narrow down search results. Users can specify various parameters such as file type, date of creation, size, or other metadata associated with the files.
  3. Tag-based Search: Many digital media servers allow users to add tags to their files. These tags can then be used to search for specific types of content. For example, a user might tag all family photos with "family" and all vacation photos with "vacation".
  4. Faceted Search: This type of search allows users to refine their search results by applying multiple filters (facets) at once. For example, if a user is searching for a video, they could select facets such as length, format, date, and more.
  5. Semantic Search: This approach goes beyond simple keyword matching and tries to understand the user's intent and the context of the query. For example, a semantic search for "latest action movies" would return recent films in the action genre.
  6. Voice Search: With the rise of smart home devices, voice search has become increasingly popular. Users can simply say what they're looking for, and the server uses natural language processing algorithms to find relevant results.
  7. Visual Search: Some advanced media servers may have visual search capabilities, where users can upload an image and the server finds similar images in its collection.
  8. AI-Powered Search: Artificial intelligence (AI) and machine learning can be used to enhance search capabilities. For example, AI can be used to automatically tag and categorize content, or to make suggestions based on past user behavior.