46 results about "Snippet" patented technology

A clustering architecture that dynamically groups the search result documents into clusters labeled by phrases extracted from the search result snippets. Documents related to the same topic usually share a common vocabulary. The words are first clustered based on their co-occurrences and each cluster forms a potentially interesting topic. Keywords are chosen and then clustered by counting co-occurrences of pairs of keywords. Documents are assigned to relevant topics based on the feature vectors of the clusters.

This invention relates generally to a system for processing database queries, and more particularly to a method for generating high level language or machine code to implement query execution plans. in one preferred embodiment, the method begins by receiving a subject query, and then forming an execution plan corresponding to the subject query. The execution plan will typically have a sequence of component snippets or pieces and corresponding processes for implementing the pieces. For at least one piece in the plan, the process then (a) generates source code using different code generation techniques as a function of expected runtime processing machine types; and then (b) compiles the generated source code to form machine executable code for implementing the subject query. As a result, the query executed directly as machine executable code thereby avoiding runtime interpretation of the pieces in the execution plan.

Methods, systems, and computer program products to serialize user interface objects having custom object types and serialization formats. A serialization manager may coordinate standard serialization providers to identify standard serializers for standard object types or serialization formats, and as needed, may be extended by loading custom serialization providers to identify custom serializers for custom object types or serialization formats, which may not be covered by the standard serialization providers. From available serialization providers, the serialization manager identifies a serializer for a particular serialization format and object type. The object, custom or standard, is serialized using the identified serializer to a custom or standard format, including source code representations, XML representations, etc. Certain serialization formats produce a snippet of code without producing a class representation of an object; to help coordinate and enhance modularity among serializers and their providers; the serialization manager may maintain and share context information.

A system and method for a comparative web search engines, search result summarization, web snippet processing, comparison analysis, information visualization, meta-clustering, and quantitative evaluation of web snippet quality are disclosed. The present invention extends the capabilities of web searching and informational retrieval by providing a succinct comparative summary of search results at either the object or thematic levels.

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. Exclude Terms are particularly useful when the lexical units, representing an Object-of-Interest, are ambiguous. When in the mode of searching for Exclude Terms, the Object-of-Interest of interest is sought, in the Corpus-of-Interest, in a broader context than when the Exclude Terms are utilized as part of an actual query. The Object-of-Interest can match anywhere in a snippet, rather than just in the focus sentence. Using the “To” operator, the focus sentences thus found are converted into role values. Statistical sampling of the role values may be used to reduce the data for the next step of processing. The role values are subjected to frequency and cluster analysis, at the lexical unit level, in order to identify candidate Exclude Terms that a user can select. Frequency and clustering information, is presented to the user, to aid in the decision process. The search for Exclude Terms can be repeated, using the Exclude Terms located thus far.

Webpages are optimizing through the use of experiments that compare the responses of viewers that are either presented with the original webpage or a variant thereof. One or more variants are first defined through the use of a browser-based editor application that initially examines the webpage for a snippet of code. The snippet can be added to the webpage, if missing, and the webpage returned to the editor application. Changes made to the webpage to define a variant are saved in variation code. When the webpage is later requested by multiple viewers, in each instance the viewer receives the webpage with the snippet, the snippet instructs the browser to download a file, and the instructions of the file determine whether the viewer will see the variant or the original webpage. Tracking viewer responses to the webpage and the variant allow a statistical basis for comparison to be developed.

The disclosure relates to a method for converting source codes into numeric identifiers and comparison against data sets, specifically to a system and method for identifying a characteristic of an input code by converting the input code into simplified code and using the simplified code to generate snippets that can be compared to code in a database. Preferably, code is simplified by at least oneof: unifying of capitalization, removing characters, and replacing at least one of a character and a keyword with an identifier.

The invention relates to a system detection method, in particular to an algorithm for detecting the MBR content rationality. The algorithm for detecting the MBR content rationality is characterized in that startup code sample snippets of startup zones of different operating systems in an Legacy mode are collected to form an MBR sample code mode base and are compiled and integrated into firmware; in a pre-os stage, the firmware surrenders the control power to be before the startup code of the OS; the startup zone content of startup equipment is read; a feature extraction algorithm is used for performing comparison detection on the startup zone content and the MBR sample code mode base; if the detection is passed, the direct startup is performed; and if the detection is not passed, restoration is performed or diagnosis information is given and output to a console. The invention provides an algorithm framework achieving the effects that in the pre-os stage, the firmware detects the content of the MBR startup sector of the startup equipment through the comparison algorithm, and then, the content is fed back to the user for restoration, or the valuable diagnosis information is provided.

The present invention proposes a method and device for processing measurement data, wherein the method includes: generating an original sequence according to the measurement data at each measurement time point, dividing the original sequence into multiple time segments, and for each time segment, according to the time The measurement data of the measurement time point in the segment is expanded by using various algorithms to obtain the sequence of each dimension of the time segment. For each dimension sequence of the time segment, various features are extracted respectively to obtain the symbol vector of the time segment. The sequence of symbolic vectors generated by the symbolic vectors of time segments is processed by a motif discovery algorithm. It solves the technical problem that the time series conversion algorithm in the prior art reduces the dimensionality of the time series, so that the time series fragments provide too few features and information, resulting in inaccurate motif discovery, resulting in poor behavior recognition effect.