Method and apparatus for partitioning a database upon a timestamp, support values for phrases and generating a history of frequently occurring phrases
Patent 6308172 Issued on October 23, 2001. Estimated Expiration Date: 
July 6, 2019. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.
July 6, 2019. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.Patent ReferencesMethod and system for natural language translation Method and apparatus for data access and update in a shared file environment Visualization of information using graphical representations of context vector based relationships and attributes Mapping words, phrases using sequential-pattern to find user specific trends in a text database Patent #: 6006223 InventorsApplicationNo. 348595 filed on 07/06/1999US Classes:707/5, Query augmenting and refining (e.g., inexact access)704/4, Based on phrase, clause, or idiom704/8, Multilingual or national language support704/9, Natural language707/2, Access augmentation or optimizing707/6, Pattern matching access707/100, DATABASE SCHEMA OR DATA STRUCTURE707/102, Generating database or data structure (e.g., via user interface)707/203, Version management715/511, Version management715/536MultilingualExaminersPrimary: Choules, Jack M.Assistant: Channavajjala, Srirama Attorney, Agent or FirmInternational ClassG06F 017/30AbstractA method and apparatus for mining text databases, employing sequential pattern phrase identification and shape queries, to discover trends. The method passes over a desired database using a dynamically generated shape query. Documents within the database are selected based on specific classifications and user defined partitions. Once a partition is specified, transaction IDs are assigned to the words in the text documents depending on their placement within each document. The transaction IDs encode both the position of each word within the document as well as representing sentence, paragraph, and section breaks, and are represented in one embodiment as long integers with the sentence boundaries. A maximum and minimum gap between words in the phrases and the minimum support all phrases must meet for the selected time period may be specified. A generalized sequential pattern method is used to generate those phrases in each partition that meet the minimum support threshold. The shape query engine takes the set of phrases for the partition of interest and selects those that match a given shape query. A query may take the form of requesting a trend such as "recent upwards trend", "recent spikes in usage", "downward trends", and "resurgence of usage". Once the phrases matching the shape query are found, they are presented to the user.Field of SearchConcurrency (e.g., lock management in shared database)Pattern matching access Privileged access Query augmenting and refining (e.g., inexact access) Distributed or remote access Query processing (i.e., searching) Access augmentation or optimizing Sorting Query formulation, input preparation, or translation DATABASE OR FILE ACCESSING FILE OR DATABASE MAINTENANCE Coherency (e.g., same view to multiple users) Recoverability Version management Archiving or backup File allocation Garbage collection Dictionary building, modification, or prioritization Multilingual or national language support Having particular Input/Output device Based on phrase, clause, or idiom Storage or retrieval of data Natural language For partial translation LINGUISTICS Translation machine Punctuation Frequency Pattern matching vocoders Vector quantization Excitation patterns Probability Dynamic time warping Viterbi trellis Creating patterns for matching Update patterns Clustering Word recognition Preliminary matching Natural language Time element Frequency element Pattern display Knowledge representation and reasoning technique Having specific management of a knowledge base KNOWLEDGE PROCESSING SYSTEM Blackboard system Ruled-based reasoning system Reasoning under uncertainty (e.g., fuzzy logic) Non-monotonic reasoning system Having specific pattern matching or control technique Hierarchical caches Private caches Parallel caches User data cache and instruction data cache Caching Multiple caches Vector processor Cube or hypercube Partitioning History table Plural recovery data sets containing set interrelation data (e.g., time values or log record numbers) | |
