Abstract: Methods and apparatus teach a digital spectrum of a data file. The digital spectrum is used to map a file's position in multi-dimensional space. This position relative to another file's position reveals closest neighbors. Certain of the closest neighbors are grouped together, while others are differentiated. Grouping ceases upon application of a stopping function so that rightly sized, optimum numbers of file groups are obtained. Embodiments of stopping functions relate to curve types in a mapping of numbers of groups per sequential rounds of grouping, recognizing whether groups have overlapping file members or not, and/or determining whether groups meet predetermined numbers of members, to name a few. Properly grouped files can then be further acted upon.

Abstract: Methods and apparatus teach a digital spectrum of a data file. The digital spectrum is used to map a file's position in multi-dimensional space. This position relative to another file's position reveals closest neighbors. Certain of the closest neighbors are grouped together to define a set. Overlapping members in the groups may be further differentiated from one another by partitioning. An optimized partition of set S of N overlapping groups yields a maximum strength for groups and members in that partition. Among other things, the optimized partition includes relative strengths of every individual member in every possible partition and weighting functions applied to the relative strengths and to subgroups of files within the partitions.

Abstract: Methods and apparatus teach a digital spectrum of a data file. The digital spectrum is used to map a file's position in multi-dimensional space. This position relative to another file's position reveals closest neighbors. Certain of the closest neighbors are grouped together, while others are differentiated. Grouping ceases upon application of a stopping function so that rightly sized, optimum numbers of file groups are obtained. Embodiments of stopping functions relate to curve types in a mapping of numbers of groups per sequential rounds of grouping, recognizing whether groups have overlapping file members or not, and/or determining whether groups meet predetermined numbers of members, to name a few. Properly grouped files can then be further acted upon.

Abstract: Methods and apparatus teach a digital spectrum of a data file. The digital spectrum is used to map a file's position in multi-dimensional space. This position relative to another file's position reveals closest neighbors. Certain of the closest neighbors are grouped together, while others are differentiated. Grouping ceases upon application of a stopping function so that rightly sized, optimum numbers of file groups are obtained. Embodiments of stopping functions relate to curve types in a mapping of numbers of groups per sequential rounds of grouping, recognizing whether groups have overlapping file members or not, and/or determining whether groups meet predetermined numbers of members, to name a few. Properly grouped files can then be further acted upon.

Abstract: A plurality of original files represent underlying original bits of data from which a key is created in a multi-dimensional mapping space for a relevancy topic. If new data is sufficiently close to this relevancy topic key, it is related to the topic and presented to users. Various closeness measures are defined as are methods for key creation. Still other features contemplate computing arrangements and program products.

Abstract: Methods and apparatus teach a digital spectrum of a file. The digital spectrum is used to map a file's position. This position relative to another file's position reveals closest neighbors. When multiple such neighbors are arranged, first “patterns” of data are created that further define digital spectrums of new files. It is within this sorted new data that emergent relationships or second “patterns” are examined, according to the techniques for its underlying files, or “patterns of patterns.” Representatively, original files are stored on computing devices. If encoded, they have pluralities of symbols representing an underlying data stream of original bits of data. The original files are examined for relationships between each of the files. The original relationships are converted to new files. The new files are representatively encoded and examined for other relationships.

Abstract: Methods and apparatus teach a digital spectrum of a file representing underlying original data. The digital spectrum is used to map a file's position. This position relative to another file's position reveals closest neighbors. When multiple such neighbors are grouped together they can be used to indicate relevance in current data under consideration on a same or different computing device. Also, relevance can be found without traditional notions of needing structured data or users initiating searching for relevance or by examining metadata/administrative information associated with the files. A plurality of original files represent underlying original bits of data from which a key is created in a mapping space for a relevancy topic. If new data is sufficiently close to this, it is related to the topic and presented to users. Various closeness measures are defined as are methods for key creation. Still other features contemplate computing arrangements and program products.

Abstract: Methods and apparatus teach a digital spectrum of a data file. The digital spectrum is used to map a file's position in multi-dimensional space. This position relative to another file's position reveals closest neighbors. Certain of the closest neighbors are grouped together, while others are differentiated. Grouping ceases upon application of a stopping function so that rightly sized, optimum numbers of file groups are obtained. Embodiments of stopping functions relate to curve types in a mapping of numbers of groups per sequential rounds of grouping, recognizing whether groups have overlapping file members or not, and/or determining whether groups meet predetermined numbers of members, to name a few. Properly grouped files can then be further acted upon.

Abstract: Methods and apparatus teach a digital spectrum of a file. The digital spectrum is used to map a file's position. This position relative to another file's position reveals closest neighbors. When multiple such neighbors are arranged, first “patterns” of data are created that further define digital spectrums of new files. It is within this sorted new data that emergent relationships or second “patterns” are examined, according to the techniques for its underlying files, or “patterns of patterns.” Representatively, original files are stored on computing devices. If encoded, they have pluralities of symbols representing an underlying data stream of original bits of data. The original files are examined for relationships between each of the files. The original relationships are converted to new files. The new files are representatively encoded and examined for other relationships.

Abstract: Methods and apparatus teach a digital spectrum of a data file. The digital spectrum is used to map a file's position in multi-dimensional space. This position relative to another file's position reveals closest neighbors. Certain of the closest neighbors are grouped together to define a set. Overlapping members in the groups may be further differentiated from one another by partitioning. An optimized partition of set S of N overlapping groups yields a maximum strength for groups and members in that partition. Among other things, the optimized partition includes relative strengths of every individual member in every possible partition and weighting functions applied to the relative strengths and to subgroups of files within the partitions.

Abstract: A schema identifies a field in a document as a key field. Using an XML schema, the key field can be identified by attaching a property to the element or attribute to be used as a key field (if the XML schema standard is modified to support properties). Otherwise, attributes can be used to identify the element or attribute that is to be a key field. Fields can be primary keys, secondary keys, or foreign keys, as supported by data stores. The data store can analyze the schema to determine which fields are key fields. The key fields can be duplicated in the native format of the data store for use in indexing, searching, and other data store functions on the documents. The documents themselves can be stored as objects, into which the data store cannot reach, or can be stored in the native format of the data store, as desired.

Abstract: A schema identifies a field in a document as a key field. Using an XML schema, the key field can be identified by attaching a property to the element or attribute to be used as a key field (if the XML schema standard is modified to support properties). Otherwise, attributes can be used to identify the element or attribute that is to be a key field. Fields can be primary keys, secondary keys, or foreign keys, as supported by data stores. The data store can analyze the schema to determine which fields are key fields. The key fields can be duplicated in the native format of the data store for use in indexing, searching, and other data store functions on the documents. The documents themselves can be stored as objects, into which the data store cannot reach, or can be stored in the native format of the data store, as desired.

Abstract: A basic architecture for managing digital identity information in a network such as the World Wide Web is provided. A user of the architecture can organize his or her information into one or more profiles which reflect the nature of different relationships between the user and other entities, and grant or deny each entity access to a given profile. Various enhancements which may be provided through the architecture are also described, including tools for filtering email, controlling access to user web pages, locating other users and making one's own location known, browsing or mailing anonymously, filling in web forms automatically with information already provided once by hand, logging in automatically, securely logging in to multiple sites with a single password and doing so from any machine on the network, and other enhancements.