Abstract: A blog map for searching and/or navigating the blogosphere is provided. In accordance with one method for generating a blog map, a number of blog posts within the blogosphere are accessed. Each of the blog posts is converted to a feature vector, which represents the position of the blog post in a high-dimensional space. The dimensionality of the feature vectors is reduced from the high-dimensional space to a low-dimensions space, such that each blog post is represented in the low-dimensional space. A map is then generated based on the position of the blog posts in the low-dimensional space.

Abstract: In connection with a classification system for classifying media entities that merges perceptual classification techniques and digital signal processing classification techniques for improved classification of media entities, a system and methods are provided for automatically classifying and characterizing melodic movement properties of media entities. Such a system and methods may be useful for the indexing of a database or other storage collection of media entities, such as media entities that are audio files, or have portions that are audio files. The methods also help to determine media entities that have similar, or dissimilar as a request may indicate, melodic movement by utilizing classification chain techniques that test distances between media entities in terms of their properties. For example, a neighborhood of songs may be determined within which each song has similar melodic movement properties.

Abstract: The claimed subject matter provides a system and/or a method that facilitates identifying relationships between two or more trade cards. A schema component can implement a portion of user-assisted schema to create a trade card that represents a distillation of a document with document-specific data. A relationship component can identify at least one of a hard link or a soft link associated with the trade card in connection with at least one of a network or one or more trade cards, wherein the hard link is a source that derived the trade card and the soft link is directed toward a disparate trade card with a portion of substantially similar document-specific data.

Abstract: A system and method for generating a list is provided. The system includes a seed item input subsystem, an item identifying subsystem, a descriptive metadata similarity determining subsystem and a list generating subsystem that builds a list based, at least in part, on similarity processing performed on seed item descriptive metadata and user item descriptive metadata and user selected thresholds applied to such similarity processing. The method includes inexact matching between identifying metadata associated with new user items and identifying metadata stored in a reference metadata database. The method further includes subjecting candidate user items to similarity processing, where the degree to which the candidate user items are similar to the seed item is determined, and placing user items in a list of items based on user selected preferences for (dis)similarity between items in the list and the seed item.

Abstract: In connection with a classification system for classifying media entities that merges perceptual classification techniques and digital signal processing classification techniques for improved classification of media entities, a system and methods are provided for automatically classifying and characterizing sonic properties of media entities. Such a system and methods may be useful for the indexing of a database or other storage collection of media entities, such as media entities that are audio files, or have portions that are audio files. The methods also help to determine media entities that have similar sonic properties by utilizing classification chain techniques that test distances between media entities in terms of their properties. For example, a neighborhood of songs may be determined within which each song has similar sonic properties.

Abstract: A system and related techniques generate alternative search terms derived from a set of search results. A user may input a set of search terms such as keywords or other inputs, and receive a set of search results back. In addition, the set of search results may have a set of selectable alternative search links associated thereto. The association of each selectable alternative search link and the set of search results depends on the evaluated distinctiveness of alternative information content of a search result Web page against other search results. In embodiments an attribute or attribute of a result may be assessed for inclusion as an alternative search attributes based on the attribute's deviation from an average of the attributes of the set of search results. A user may select the alternative search suggestion and be presented with an updated set of search results related to the alternative search attributes.

Abstract: The present invention provides collaborative filtering systems and methods employing default scores of decision graphs/trees to quickly create a top-n prediction list that can efficiently determine a user's interest in items. In one instance of the present invention, the list is refined by utilizing a variable maximum score algorithm and/or an invalidation list algorithm to insert items that score above an inclusion threshold set by a last item in the top-n prediction list. In another instance of the present invention, an invalidation list for a decision graph and/or decision tree is utilized to create a top-n prediction list. An algorithm employing default scores is then utilized to refine the top-n prediction list to insert items with default scores above an inclusion threshold set by a last item in the top-n prediction list.

Abstract: A system and methods are provided for automatically classifying data according to perceptual properties of the data to form a classification chain that is suited to the searching and sorting of large databases of media entities. During classification, experts assign each media entity in the training data set to one or more classes, with each class corresponding to a given subset of perceptual properties of the data. In conjunction with digital signal processing properties of the data corresponding to the perceptual properties, the classified data is then used to construct an initial classification chain. During operation, when presented with an unclassified entry, the classification chain returns an estimate of the class of the entry, as well as a confidence measure that is proportional to the level of confidence of the class assignment. Over time, as the classification chain evolves, the classification chain becomes more and more effective for quickly characterizing media entities.

Abstract: In connection with a classification system for classifying media entities that merges perceptual classification techniques and digital signal processing classification techniques for improved classification of media entities, a system and methods are provided for automatically classifying and characterizing tempo properties of media entities. Such a system and methods may be useful for the indexing of a database or other storage collection of media entities, such as media entities that are audio files, or have portions that are audio files. The methods also help to determine media entities that have similar, or dissimilar as a request may indicate, tempo(s) by utilizing classification chain techniques that test distances between media entities in terms of their properties. For example, a neighborhood of songs may be determined within which each song has similar tempo characteristics.

Abstract: A system and methods are provided for automatically classifying data according to perceptual properties of the data to form a classification chain that is suited to the searching and sorting of large databases of media entities. During classification, experts assign each media entity in the training data set to one or more classes, with each class corresponding to a given subset of perceptual properties of the data. In conjunction with digital signal processing properties of the data corresponding to the perceptual properties, the classified data is then used to construct an initial classification chain. During operation, when presented with an unclassified entry, the classification chain returns an estimate of the class of the entry, as well as a confidence measure that is proportional to the level of confidence of the class assignment. Over time, as the classification chain evolves, the classification chain becomes more and more effective for quickly characterizing media entities.

Abstract: In connection with a classification system for classifying media entities that merges perceptual classification techniques and digital signal processing classification techniques for improved classification of media entities, a system and methods are provided for automatically classifying and characterizing tempo properties of media entities. Such a system and methods may be useful for the indexing of a database or other storage collection of media entities, such as media entities that are audio files, or have portions that are audio files. The methods also help to determine media entities that have similar, or dissimilar as a request may indicate, tempo(s) by utilizing classification chain techniques that test distances between media entities in terms of their properties. For example, a neighborhood of songs may be determined within which each song has similar tempo characteristics.

Abstract: A system and method for generating a list is provided. The system includes a seed item input subsystem, an item identifying subsystem, a descriptive metadata similarity determining subsystem and a list generating subsystem that builds a list based, at least in part, on similarity processing performed on seed item descriptive metadata and user item descriptive metadata and user selected thresholds applied to such similarity processing. The method includes inexact matching between identifying metadata associated with new user items and identifying metadata stored in a reference metadata database. The method further includes subjecting candidate user items to similarity processing, where the degree to which the candidate user items are similar to the seed item is determined, and placing user items in a list of items based on user selected preferences for (dis)similarity between items in the list and the seed item.

Abstract: A system and method for generating a list is provided. The system includes a seed item input subsystem, an item identifying subsystem, a descriptive metadata similarity determining subsystem and a list generating subsystem that builds a list based, at least in part, on similarity processing performed on seed item descriptive metadata and user item descriptive metadata and user selected thresholds applied to such similarity processing. The method includes inexact matching between identifying metadata associated with new user items and identifying metadata stored in a reference metadata database. The method further includes subjecting candidate user items to similarity processing, where the degree to which the candidate user items are similar to the seed item is determined, and placing user items in a list of items based on user selected preferences for (dis)similarity between items in the list and the seed item.

Abstract: In a hierarchical taxonomy of document, the categories of information may be structured as a binary tree with the nodes of the binary tree containing information relevant to the search. The binary tree may be ‘trained’ or formed by examining a training set of documents and separating those documents into two child nodes. Each of those sets of documents may then be further split into two nodes to create the binary tree data structure. The nodes may be generated to maximize the likelihood that all of the training documents are in either or both of the two child nodes. In one example, each node of the binary tree may be associated with a list of terms and each term in each list of terms is associated with a probability of that term appearing in a document given that node. New documents may be categorized by the nodes of the tree. For example, the new documents may be assigned to a particular node based upon the statistical similarity between that document and the associated node.

Abstract: A system and method for determining the similarity of music files based on a perceptual metric is disclosed. In accordance with one aspect of the invention, harmonic, rhythmic, and melodic components are generated for each of the music files. The dimensionality of the components is then reduced to six by a mapper. This reduction is part of what allows the present invention to process large collections of music files very quickly. The mapper maps the components to positions on two-dimensional feature maps. The feature maps are trained by a trainer. The top N positions in each feature map, along with their amplitudes, are taken as the representative vectors for the music files. To compare the similarity between two music files, the distance between the two representative vectors are calculated.

Abstract: In connection with a classification system for classifying media entities that merges perceptual classification techniques and digital signal processing classification techniques for improved classification of media entities, a system and methods are provided for automatically classifying and characterizing melodic movement properties of media entities. Such a system and methods may be useful for the indexing of a database or other storage collection of media entities, such as media entities that are audio files, or have portions that are audio files. The methods also help to determine media entities that have similar, or dissimilar as a request may indicate, melodic movement by utilizing classification chain techniques that test distances between media entities in terms of their properties. For example, a neighborhood of songs may be determined within which each song has similar melodic movement properties.

Abstract: A system and methods are provided for automatically classifying data according to perceptual properties of the data to form a classification chain that is suited to the searching and sorting of large databases of media entities. During classification, experts assign each media entity in the training data set to one or more classes, with each class corresponding to a given subset of perceptual properties of the data. In conjunction with digital signal processing properties of the data corresponding to the perceptual properties, the classified data is then used to construct an initial classification chain. During operation, when presented with an unclassified entry, the classification chain returns an estimate of the class of the entry, as well as a confidence measure that is proportional to the level of confidence of the class assignment. Over time, as the classification chain evolves, the classification chain becomes more and more effective for quickly characterizing media entities.

Abstract: A system and method for generating a list is provided. The system includes a seed item input subsystem, an item identifying subsystem, a descriptive metadata similarity determining subsystem and a list generating subsystem that builds a list based, at least in part, on similarity processing performed on seed item descriptive metadata and user item descriptive metadata and user selected thresholds applied to such similarity processing. The method includes inexact matching between identifying metadata associated with new user items and identifying metadata stored in a reference metadata database. The method further includes subjecting candidate user items to similarity processing, where the degree to which the candidate user items are similar to the seed item is determined, and placing user items in a list of items based on user selected preferences for (dis)similarity between items in the list and the seed item.

Abstract: A system for generating recommendations which automatically optimizes over time without human intervention is disclosed. While known recommendation systems tended to be either attribute based or collaborative filtering based, the present system adjusts its internal parameters in response to the measured performance of the recommendations as determined by user behavior. In one embodiment, the user provides feedback in the form of ratings for the recommendations. This feedback is processed and then utilized to adjust the internal parameters of the system. Over time, the system settles on optimal parameter values.

Abstract: A system and method for generating a list is provided. The system includes a seed item input subsystem, an item identifying subsystem, a descriptive metadata similarity determining subsystem and a list generating subsystem that builds a list based, at least in part, on similarity processing performed on seed item descriptive metadata and user item descriptive metadata and user selected thresholds applied to such similarity processing. The method includes inexact matching between identifying metadata associated with new user items and identifying metadata stored in a reference metadata database. The method further includes subjecting candidate user items to similarity processing, where the degree to which the candidate user items are similar to the seed item is determined, and placing user items in a list of items based on user selected preferences for (dis)similarity between items in the list and the seed item.