355 results about "Canonicalization" patented technology

The invention provides a method for predicting which network objects are likely to be requested by a web user from a web server, such as that used in conjunction with an internetworking environment. A request made by a web user for a web object is parsed and dynamic values contained therein normalized. A prediction is made based on the normalized request, statistical measures, and other factors about what other web objects the web user is likely to request. The predictive information is then made available to the web server and the predicted net objects are pre-downloaded to the Web client. A pre-download statistics server may be used to record and provide statistics to assist in the prediction process. Examples described herein relate to web pages, but the invention is broadly applicable to many different types of requests for information (such as, for example, database queries and other libraries of information.)

In response to the provision of a collection of semi-structured data (or its schema), a mapper generates a structured organization to store the collection of semi-structured data. The mapper further collaterally generates a description of how the semi-structured data are stored under the structured organization. In one embodiment, normalized relational tables are used for the structured organization. In alternate embodiments, non-normalized relational tables or other structured organization may also be used. The reverse, that is, the creation of a semistructured data organization for a collection of structured data may also be performed.

The present invention involves a system and method that facilitate extracting data from messages for spam filtering. The extracted data can be in the form of features, which can be employed in connection with machine learning systems to build improved filters. Data associated with origination information as well as other information embedded in the body of the message that allows a recipient of the message to contact and/or respond to the sender of the message call be extracted as features. The features, or a subset thereof, can be normalized and/or deobfuscated prior to being employed as features of the machine learning systems. The (deobfuscated) features can be employed to populate a plurality of feature lists that facilitate spam detection and prevention. Exemplary features include an email address, an IP address, a URL, an embedded image pointing to a URL, and/or portions thereof.

A system and method is provided for efficiently adapting information content for an electronic device. A normalizer includes a template normalizer for matching and applying a document tree to a template tree, and applying changes to the document tree. If the template normalizer does not find an appropriate template match, an automatic normalizer is utilized. The automatic normalizer utilizes weighting heuristics and pattern recognition with formatting rules to partition content into folders. The automatic normalizer can also utilize embedded normalization markup in the information content to assist in normalizing the information content. Information content can be represented by document object tree. A document object tree is created by storing information relating to the information content into arrays. The stored information describes a document object tree structure and tree dependencies as a mutable object.

Characteristic normalization (or leveling) is a process that yields consistent and equitable characteristic definitions across multiple sources of credit information. This leveling ensures that when the same data is present for multiple credit sources, for example two or more credit reporting agencies, it is interpreted in the same manner, acknowledging that differences in the data itself may still be present.

A method is provided for monitoring, predicting performance of, and managing Business Operations by the simultaneous, real-time Integration, Normalization and Correlation of direct measurements at the Business Layer and other Layers of Business Operations. The other Layers considered, may include, for example, Application and Infrastructure Layers. The system enables the user to automate sophisticated management tasks by Correlating measurements of activity, performance and availability at all Layers of Business Operations. Significantly, the techniques described herein extend the domain of the Correlations across real-time measurements from all Layers of Business Operations, giving central importance to the measurements in the Business Layer within the Correlations.

The present invention relates generally to a system and method for categorization of strings of words. More specifically, the present invention relates to a system and method for normalizing a string of words for use in a system for categorization of words in a predetermined categorization scheme. A method for adaptive categorization of words in a predetermined categorization scheme may include receiving a string of text, tagging the string of text, and normalizing the string of text. Normalization may be performed with a three-stage algorithm including a literal match processing stage, an approximation match processing stage, and a nearest neighbor match processing stage. The normalized string of text can be compared to a number of sequences of text in the predetermined categorization scheme.

A system suited to self-troubleshooting includes a processor which identifies normalized forms of at least some of the words of a natural language user query input by a user. The user query may describe a problem experienced with a machine, such as a printer. The processor retrieves text strings which may comprise problem statements stored in memory. Each retrieved problem statement includes at least one word with a normalized form which is recognized by the processor as being equivalent to one of the identified normalized forms. Each of the retrieved problem statements may be associated with at least one solution sequence for addressing the problem with the machine. In the event that the stored problem statements in memory are not fully responsive, the processor provides one or more options for refinement of the user query based on tags associated with those words of the problem statements which are responsive.

Apparata, articles and methods for discovering partially periodic temporal associations, referred to herein as p-patterns, are provided. For example, a p-pattern in computer networks might comprise five repetitions every 30 seconds of a port-down event followed by a port-up event, which in turn is followed by a random gap until the next five repetitions of these events. In one embodiment, the present invention comprises: (i) a normalization step to convert application-oriented event data into an application-independent normalized table; (ii) an algorithm for finding significant period lengths from normalized events (e.g., 30 seconds) using a Chi-squared test; and (iii) an algorithm for finding a partially periodic temporal association (e.g., port-down followed by port-up) given a known period.

A method, system and computer program product for transformation, normalization and correlation techniques that are effective for matching names of foreign origin that may be spelt in any number of ways. It addresses the problem of matching names that may belong to the same person but may be spelt differently. The main technique is to convert both strings to be matched into a representation of their original language, i.e., transform them into idealized (normalized) versions of themselves based on their true spelling in their original, native language. This process of idealization can be done either by employing a dictionary of standard, idealized names, or by implementing the idealization in real time by following a finite-state algorithm to convert the strings into their true representation in their original language. The idealization process can be viewed as a phonetic searching method, as it resolves the problem of vowel representations or their incorrect use as well as handling the representation of consonants that do not exist in the English language. Further probabilistic and elastic matching techniques, using a correlation function, can be invoked manually or automatically to match names where the quality of or the completeness of names may be suspect. A new approach to "probabilistic" and "sliding-elastic" matching (which give a level of confidence as a percentage against each match) can be used with or without the phonetic (idealized) searching function. The results of the search are displayed on the computer screen or printed, showing all the successful matches, together with the type of search that has been used to obtain the match. Results can be filtered by comparing attributes of the persons associated with the Suspect and Data names (such as age, country of birth, etc.) to minimize reporting on irrelevant matches.

A system, method and program product for normalizing, sanitizing and disambiguating structured data. Structured data includes data stored in a database management system (DBMA), as well labeled files (e.g., XML data). An automated data enhancement processing system is provided, comprising: a system for ingesting data structured in at least one predefined database format; and a set of text analytics processes that treat the ingested data as unstructured, and generate normalized data represented and indexed by consistent, structured metadata.

Systems and methods for protecting client computers are described. One exemplary system includes an initial filter that gathers scripting-language-data from webpage data and a signature database of signatures of known scripting-language-data exploits. In addition, a parser generates a parse tree from the scripting-language-data, and a normalization and signature matching component reduces a complexity of the parse tree, generates a representation of at least a portion of a structure of the parse tree, and prevents the scripting-language-data from reaching an intended recipient if the representation matches one of the signatures of known scripting-language-data exploits.

A method for conversion between a decimal floating-point number and an order-preserving format has been disclosed. The method encodes numbers in the decimal floating-point format into a format which preserves value ordering. This encoding allows for fast and direct string comparison of two values. Such an encoding provides normalized representations for decimal floating-point numbers and supports type-insensitive comparisons. Type-insensitive comparisons are often used in database management systems, where the data type is not specified for values to compare. In addition, the original decimal floating-point format can be recovered from the order-preserving format.

The invention relates to a stratification synergic detection and judgment method for detecting the confused API call behavior and judging the maliciousness of the call behavior; the detection and judgment method includes three steps: firstly, the binary code for being analyzed is disassembled to establish the control flow graph (CFG) of the program; the known unconventional instruction or data sequence provided with the API function call capability and stored in the database DB1 is adopted to recognize the unconventional call behavior of the API function; secondly, the generation operation of the API sequence called by the target program is finished; the API function is recognized and recovered in the aspects of direct call and indirect call; finally, the extraction of the API sequence and the maliciousness judgment operation are finished; the extraction of the sequence is finished and based on the control flow graph (CFG) of the program; then the obtained sequence is normalized according to the format stored in the suspected API sequence database; the invention provides a stratification synergic detection and judgment method for detecting the confused API call behavior and judging the maliciousness of the call behavior, which has the advantages of wide recognition range, accurate recognition and high efficiency.

A method and system unifying existing data of a target industry from existing sources of the data by designing a data model by applying varying data integrity methods to define characteristics, features and/or functions of items in the target industry as data elements, electronically reading, parsing and transforming data from existing electronic data sources of the target industry to input to the data model, designing user interfaces to the data model, the user interfaces corresponding to user segments of the target industry, and dynamically maintaining normalization of the data model according to the varying data integrity methods during any type of access to the data model by the user segments. A data entry access to the data model comprises dynamically constructing search indexes, each search index defined as a unique data field and a text searchable concatenation of other fields' data in any given data table of the data model.

The present invention relates to a system and method to facilitate efficient and automated presentation of information to users. A decomposition component automatically decomposes an information item into sets of subcomponents in a two- or three-dimensional isometric space, and generates visualizations having interactive graphics that allow users to inspect respective subcomponents. Interface features are provided to enable hover, dwell, and clicking commands, for example, providing a variety of options to zoom in, or change configurations of the visualization in accordance with the users intentions or inferences about what they desire to see or inspect more closely. Beyond the use of decompositions into exploded views of the content of items typically viewed as singular documents, the methods can be applied to perform geometric transformations on visualizations of multiple windows and other resources based on content and activity to provide regularized visualizations of the multiple items. Such exploded views can provide visual geometric summaries of projects, and a set of handles into accessing more detail on the subcomponents of the project.

An improved normalization methodology enabling better optimization of SQL queries is described. The normalization methodology effectively handles three-valued SQL search conditions and operates in reduced memory environments. A query is examined and selectively normalized by examining each segment of the query to determine whether it is advantageous to fully convert that segment to conjunctive normal form (CNF). If full conversion of the segment to CNF is not advantageous, then only the useful conjunctive conditions (prime implicates) that can be derived from the original input are saved. These useful conjuncts (prime implicates) are unioned with the original statement, resulting in a search condition that is semantically equivalent to the original expression, but that can be better exploited by a query optimizer. This enables better optimization of the original query without the system overhead that would result from full normalization of the query.

A circuit (10) for multiplying two floating point operands (A and C) while adding or subtracting a third floating point operand (B) removes latency associated with normalization and rounding from a critical speed path for dependent calculations. An intermediate representation of a product and a third operand are selectively shifted to facilitate use of prior unnormalized dependent resultants. Logic circuitry (24, 42) implements a truth table for determining when and how much shifting should be made to intermediate values based upon a resultant of a previous calculation, upon exponents of current operands and an exponent of a previous resultant operand. Normalization and rounding may be subsequently implemented, but at a time when a new cycle operation is not dependent on such operations even if data dependencies exist.

A method for enrichment of text which enables mixed data mining includes generating a model for structured data found in tables of a database. In the model, semantically-linked terms are associated with referents, such as field names or cell content of the fields, of the structured data. The referents may be a business object or refer to a business object. A plurality of candidate referring entities in textual data in the database, such as chunks of free text, is identified. For each candidate referring entity, a similarity measure between the candidate referring entity in the textual data and the model is computed to identify referring entities of the candidate referring entities and corresponding business objects/referents to which the referring entities refer. The textual data is enriched with information derived from the business objects.