Rovi Technologies Corporation

Joonas Asikainen

Brian Kenneth Vogel

Kenneth Olson

A method and a system are provided for searching content (e.g., text, metadata and/or a fingerprint, etc.). In one example, the system receives content and a query for matching the content. The content includes computer readable data. The system generates a feature vector for the content. Generating the feature vector comprises generating a signal from the content, generating a spectrogram from the signal, and generating the feature vector from the spectrogram. The system searches for at least one feature vector that matches the feature vector for the content.

Searching text and other types of content by using a frequency domain

An input feature vector is computed from an input text record, the input feature vector comprising one or more features, each feature including a subsequence of characters and a frequency of occurrence of the associated subsequence. A input fingerprint is generated out of the input feature vector by choosing one or more features with non-zero frequencies and alphabetizing the features chosen. One or more input indices are generated by alphabetizing features in the input fingerprint and concatenating features occurring in subsequent locations of the input fingerprint. The input text record is matched against a target text record if (1) one or more of the input indices match a target index corresponding to the target text record and (2) the corresponding input fingerprint matches a target fingerprint corresponding to the target text record. The target text record is outputted as a search result if it matches the input text record.

Text-based fuzzy search

A processor retrieves, from a database, an identifier of a first media item rated by a target user, user identifiers of users having provided media item ratings for the first media item, and the media item ratings provided by the users, correspondingly. Each of the media item ratings is randomized, resulting in randomized media item ratings. A user identifier corresponding to a maximum of the randomized media item ratings is selected from the user identifiers. Additional media item ratings associated with the selected user identifier are retrieved from the database. Each of the additional media item ratings are randomized, resulting in additional randomized media item ratings. An identifier of a recommended media item corresponding to a maximum of the randomized media item ratings and the additional randomized media item ratings is selected. Metadata associated with the recommended media item is transmitted to a user device over a network.

Method, medium, and system for providing a recommendation of a media item

A method and a system are provided for recommending a media item (e.g., movie and/or television program). In one example, the system receives a seed media item (e.g., seed movie and/or seed television program). A seed media item is an audio-visual recording that is identified as being of interest to a user. The system recognizes one or more recognized audio tracks (e.g., audio tracks and/or songs) from the seed media item. A recognized audio track is an audio recording that is contained in the seed media item. The system retrieves audio track metadata associated with at least one of the recognized audio tracks from the seed media item. Audio track metadata are data that describes an audio recording. The system recommends one or more recommended media items based on the audio track metadata. A recommended media item is an audio-visual recording (e.g., movie and/or television program).

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Zurich, Switzerland

Joonas Asikainen