Abstract: Techniques for category-based content recommendation are described. Some embodiments provide a content recommendation system (“CRS”) configured to recommend content items (e.g., Web pages, images, videos) that are related to specified categories. In one embodiment, the CRS processes content items to determine entities referenced by the content items, and to determine categories related to the referenced entities. The determined entities and/or categories may be part of a taxonomy that is stored by the CRS. Then, in response to a received request that indicates a category, the CRS determines and provides indications of one or more content items that each have a corresponding category that matches the indicated category. In some embodiments, at least some of these techniques are employed to implement a category-based news service.

Abstract: Techniques for category-based content recommendation are described. Some embodiments provide a content recommendation system (“CRS”) configured to recommend content items (e.g., Web pages, images, videos) that are related to specified categories. In one embodiment, the CRS processes content items to determine entities referenced by the content items, and to determine categories related to the referenced entities. The determined entities and/or categories may be part of a taxonomy that is stored by the CRS. Then, in response to a received request that indicates a category, the CRS determines and provides indications of one or more content items that each have a corresponding category that matches the indicated category. In some embodiments, at least some of these techniques are employed to implement a category-based news service.

Abstract: A method and system for ranking relevancy of metadata associated with media on a computer network, such as multimedia and streaming media, include categorizing the metadata into sets of metadata. The categories are broad categories relating to areas such as who, what, when, and where, such as artist, media type, and creation date, creation location. Weights are assigned to each set of metadata. Weights are related to technical information such as bit rate, duration, sampling rate, frequency of occurrence of a specific term, etc. A score is calculated for ranking the relevancy of each set of metadata. The score is calculated in accordance with the assigned weight and category. This score is available for search systems (e.g., search engines) and/or users to determine the relative ranking of search results.