Abstract: Given a search result, the set of authors-identifiers appearing in it can be determined by use of a hash function, and an array-type data structure called an audience fingerprint (AF). The AF has as many storage locations as the hash function has possible output values. The number of possible output values is chosen to be large enough, with respect to the maximum number of unique authors expected in any one search result, to create a very high probability of a unique output value for each unique author-identifier that is hashed. At the AF location, addressed with a hash value, is stored an indicator that the author-identifier is present. The indicator can be a single bit, simplifying set operations on AFs. When not in working memory, an AF can be stored as a compacted sparse array. The actual author-identifiers present can be determined, from an AF, with an inverse hash function.

Abstract: To the standard operations of an inverted index database, a new “To” operator is added. The “To” operator treats the standard single-level linear collection of records as being organized into localized clusters. Techniques for hierarchical clusters are presented. During indexing, hierarchical clusters are serialized according to a uniform visitation procedure. Serialization produces bit maps, one for each hierarchical level, that preserve the hierarchical level of each record and its location in the serialization sequence. For non-hierarchical clusters, byte maps can be produced. The “To” operator accepts a list of records, each at a same hierarchical level in a cluster, and a specification of a hierarchical level that all the input records should be converted into. The “To” operator outputs a list of records, representing a conversion of the input records to the specified new level. Logical Forms, against which frame extraction rules match, can be stored in hierarchical clusters.

Abstract: To the standard operations of an inverted index database, a new “To” operator is added. The “To” operator treats the standard single-level linear collection of records as being organized into localized clusters. Techniques for hierarchical clusters are presented. During indexing, hierarchical clusters are serialized according to a uniform visitation procedure. Serialization produces bit maps, one for each hierarchical level, that preserve the hierarchical level of each record and its location in the serialization sequence. The “To” operator accepts a list of records, each at a same hierarchical level in a cluster, and a specification of a hierarchical level that all the input records should be converted into. The “To” operator outputs a list of records, representing a conversion of the input records to the specified new level. When searching a Corpus-of-Interest for an Object-of-Interest, techniques are presented for greatly improving the process by which Exclude Terms are identified.

Abstract: To the standard operations of an inverted index database, a new “To” operator is added. The “To” operator treats the standard single-level linear collection of records as organized into localized clusters. The “To” operator accepts a list of records, each at a same hierarchical level in a cluster, and a specification of a hierarchical level that all the input records should be converted into. The “To” operator outputs a list of records, representing a conversion of the input records to the specified new level. Logical Forms, against which frame extraction rules match, can be stored in hierarchical clusters. A database query can be formulated, that matches against such Logical Forms, that provides the same or similar functionality to a frame extraction rule. Such queries extend the range of applications of a particular inverted index database and/or can aid in the development of new frame extraction rules.

Abstract: Given a search result, the set of authors-identifiers appearing in it can be determined by use of a hash function, and an array-type data structure called an audience fingerprint (AF). The AF has as many storage locations as the hash function has possible output values. The number of possible output values is chosen to be large enough, with respect to the maximum number of unique authors expected in any one search result, to create a very high probability of a unique output value for each unique author-identifier that is hashed. At the AF location, addressed with a hash value, is stored an indicator that the author-identifier is present. The indicator can be a single bit, simplifying set operations on AFs. When not in working memory, an AF can be stored as a compacted sparse array. The actual author-identifiers present can be determined, from an AF, with an inverse hash function.