40 results about "Category Type" patented technology

A method and system providing category based sort and display instructions for a computer system having a database of information stored therein are described. A database of contact information is maintained in the computer with each record containing information related to a personal contact. Each record can be assigned a custom category type defining the kind of contact that the record is. The user is allowed to display a condensed listing of the contacts associated with each category. When the list is displayed, the list can be sorted by a field specific to that category type. Each category type can have its own sorting instructions. The sorting instructions also define the way in which the lists are displayed. The user can define and edit the category based instructions at any time.

A content recommendation apparatus and method are provided. The content recommendation apparatus may record user history information of a user of a personal communication terminal where a web browsing service or mobile communication is possible. The user history information may be used to generate preference information of the user. Based on the preference information, content may be recommended to the user through a display based on a category type of the content such that different types of content are visually differentiated on the display.

A method and apparatus for automatic white balancing of an image. The method includes retrieving scene analysis of the image, determining at least one of the type of the scene and a scene content map utilizing the scene analysis of the image, performing scene adaptive white balance, if overall scene category type is used, perform white balance by applying global R, G, B gains optimized for the global scene type, and if scene segmentation map is used, perform locally adaptive white balance by applying an R, G, B gain map optimized for each scene content.

A method and system for synchronizing and using calendar information from a shared database is disclosed. Calendar information can be stored in a shared database, e.g., on a server system and accessed and synchronized with one or more portable computer systems. The calendar information is stored using particular category types which facilitate separate manipulation, access and removal of the calendar information when placed onto a portable computer system (e.g., palmtop). In one embodiment, calendar information is stored on a shared database and is assigned a unique category type. Multiple portable computer systems can then access the shared calendar information which can be displayed on each computer system along with the system's own calendar information. The unique category type is different from the default type of each system's own calendar information and the user is not able to change category types on the portable computer system. Shared calendar information can be viewed and edited and then easily removed using the unique category type.

A method and system for synchronizing and using calendar information from a shared database is disclosed. Calendar information can be stored in a shared database, e.g., on a server system and accessed and synchronized with one or more portable computer systems. The calendar information is stored using particular category types which facilitate separate manipulation, access and remobal of the calendar information when placed onto a portable computer system (e.g., palmtop). In one embodiment, calendar information is stored on a shared database and is assigned a unique category type. Multiple portable computer systems can then access the shared calendar information which can be displayed on each computer system along with the system's own calendar information. The unique category type is different from the default type of each system's own calendar information and the user is not able to change category types on the portable computer system. Shared calendar information can be viewed and edited and then easily removed using the unique category type.

Strings are recognized and annotated, or labeled, with a type label by a recognizer plug-in. Application program modules may use the type label and other metadata to provide users with a choice of electronic commerce actions. In addition, the user may be provided with a download Uniform Resource Locator (URL) and download action plug-ins for that type label. An ActionGUID may be used to specify the class ids (CLSIDs) of the action plug-ins that may provide actions for a particular semantic category type label. Each DLL has a class id (CLSID), which is a GUID. The ActionGUID is a GUID that is specified by the recognizer plug-in and which corresponds to the CLSID(s) of the only action plug-ins that should be permitted to provide actions for the semantic category type label provided by the recognizer plug-in.

The invention provides a data anonymization method and system. The data anonymization method comprises the steps of: carrying out text analysis on the attribute value of a text type in data; replacing the attribute value of the text type in the data with the attribute value of a value type or a class type according to text analysis result; and carrying out anonymization processing on the data in which the attribute value of the text type is replaced by the attribute value of the value type or the class type. According to the invention, after anonymization processing, the data comprising the attribute value of the text type not only can prevent the privacy leakage based on the attribute value, but also still has use value.

A system for locating corresponding ends of a communications or data patch cable used to conduct a signal between computing or telecommunications devices. The invention provides a physical indication of the location of an opposite end of a given patch cable when a switching means on the first end of the same cable is activated. The invention utilizes an existing pair of wires in category-type cables to send a DC voltage when activated to illuminate a light emitting diode in the opposite end of a patch cable thereby providing an immediate indication of the location of the termination of the opposite end of a patch cable making it possible to visually identify a cable without removing the cable from service or from connection of the modular plugs on either end of the cable.

A system and method for generating a hypergraph representative of a comprehensive profile of user is provided. A graphical representation of selected user's transactional behavior is generated. Further, user data is retrieved from external systems for a predetermined time period. A first variable set is derived from the retrieved data and classified into data fields such that the variables across relevant data fields are linkable based on predetermined data category types. Further, new data fields are generated for realizing classification of additional retrieved data. A second variable set from the new data is retrieved and classified into new data fields such that variables across relevant new data fields are linkable based on the predetermined data category types. Two or more graphical representations are generated by linking the variables across the relevant data fields based on the predetermined data category types. Finally, a hypergraph is generated by integrating the graphical representations.

The invention discloses a method for semi-supervised learning of structured data, and the method comprises the steps: building a semi-supervised adversarial neural network model for the structured data, carrying out the preprocessing of original structured data X, and enabling the features of the original data X to be divided into a category type feature subset xCT and a numerical type feature subset xNL; the original input of the model discriminator is {x1, x2, xg}, wherein x1 is a positive integer;, xu is respectively a labeled sample and an unlabeled sample; wherein xg is a sample generatedby the generator; feature sets contained in x1 and xu are the same; inputting the class feature subset xCT of the sample into an Engineering layer; obtaining a corresponding dense embedding vector E(xCT), combining the dense embedding vector E (xCT) with the numeric feature subset xNL to obtain a sample E(xCT) + xNL with a new feature set, obtaining a normalized sample containing the new featureset by applying a BN technology, inputting the new sample into a discriminator for training, and generating a sample xg which is directly used as the input of the discriminator; the generator is composed of three layers of full-connection networks, BN is applied to the output of each layer to prevent gradient dispersion, noise serves as the output, and a production sample xg with the characteristic E(xCT) + xNL is obtained.

A system for locating corresponding ends of a communications or data patch cable used to conduct a signal between computing or telecommunications devices. The invention provides a physical indication of the location of an opposite end of a given patch cable when a switching means on the first end of the same cable is activated. The invention utilizes an existing pair of wires in category-type cables to send a DC voltage when activated to illuminate a light emitting diode in the opposite end of a patch cable thereby providing an immediate indication of the location of the termination of the opposite end of a patch cable making it possible to visually identify a cable without removing the cable from service or from connection of the modular plugs on either end of the cable.

Method for assigning an assortment of products to an existing planogram includes: providing an existing planogram which includes an existing assortment of products in association with a geometrical placement layout of these products on shelves and storing the existing planogram in memory; providing a user-defined new assortment of products and storing the new assortment in memory; furnishing, by a processor having read / write access to the memory, an output planogram by removing, from the output planogram, products in the existing assortment but not in the new assortment and adding, to the output planogram, products in the new assortment but not in the existing assortment; storing the output planogram in memory. The method further includes: generating a set of at least one segmentation tree which describes the relative geometrical placement of products in the existing planogram according to several ordered category types, each type corresponding to a level of the segmentation tree.

A device for enabling content selection is configured to display one or more sub-categories of content included within a category of content. The one or more sub-categories of content may be displayed using stack structures. The stack structures may include a plurality of icons representing available content. The stack structures may enable thumbnail browsing of content available from a plurality of diverse sources. The device may enable a user to cycle through sub-category types.

The invention relates to a pulse baseline value calculation method and a particle counting method for a blood cell analyzer. The pulse baseline value calculation method comprises the step of calculating the average value of n consecutive sampling data on the condition that the absolute value of the difference between two arbitrary adjacent data among the n consecutive sampling data is smaller than a baseline threshold value and the n consecutive sampling data are nearest to a pulse starting point within a pulse non-sustainable period, wherein the average value represents the baseline threshold value. According to the technical scheme of the invention, the baseline threshold value is preset and compared, and the sampling data of a noise-superimposed baseline are avoided. Meanwhile, sampling data within a noise / interference allowable range are selected and calculated. In this way, the noise is accumulated onto a final baseline value, so that the baseline value is more close to real data. The misjudgment of the baseline value is greatly reduced, so that the particle counting result is more accurate. The method can be applied to the particle counting operations of three-category type blood cell analyzers, five-category type blood cell analyzers, flow cytometers and other biochemical instruments.

An exemplary queuing congestion mechanism and method are disclosed that provide congestion management at an egress port of a packet switch. The queuing congestion mechanism includes at least a first, a second and a third queue, which each have an input, an output, and a capacity. Each queue is operable to receive packets of information of a designated type, such as a service category type, at its input that are destined to be communicated to the egress port through its output. The queuing congestion mechanism further includes a scheduler and a queue shaper. The scheduler, which may be implemented as a strict scheduler, is operable to receive the packets of information from the output of the queues and to communicate the packets of information to the egress port of the packet switch based on a schedule. The queue shaper is operable to set an adjustable rate in which the packets of information of the third queue are communicated to the scheduler, and the adjustable rate is controlled by a loading of the capacity of the second queue. The queuing congestion mechanism may include a discard policy that is enabled for one or more of the queues and that is based on the loading of the capacity of one of the other queues.

The invention discloses a credit assessment model training and assessment method and device, and a credit assessment model is obtained through the training method and the training method comprises thesteps of obtaining user data and an assessment result of a user with a correct credit assessment result in a credit investigation system; preprocessing user data in the collected user data, converting the user data into numerical data, including but not limited to performing One hot transform on the category type data, and normalizing the numerical data; constructing m SDT sub-classifiers, m being a positive integer, and constructing an SDT weight generator for generating weight probability distribution of the m SDT sub-classifiers; and performing end-to-end training on the WSDF model with m+ 1 soft decision trees by using the preprocessed user data. The credit assessment model and device constructed by the method has higher working efficiency, and can reduce the bad account rate; and meanwhile, a visual decision-making process is generated.

The invention discloses a data classification regression method and a data classification regression device. The method comprises the following steps of dividing an initial sample vector set into a continuous type data sequence, a category type data sequence and a binary data sequence; respectively converting the continuous type data sequence and the category type data sequence into a first vector sequence and a second vector sequence which are in a binary form; merging the first vector sequence, the second vector sequence and the binary data sequence to generate a classification regression vector sequence; and obtaining a classification regression result of the initial sample vector set according to each vector in the classification regression vector sequence. By adopting the technical scheme, the obtaining of the data classification regression result is not limited by the data dimension number and the data volume; and the data classification regression can be realized without adopting an iterative algorithm, so that the complexity for obtaining the data classification regression result is lowered.

The invention belongs to the technical field of data mining, medical information and big data, and particularly to a medicine analysis method based on full memory event sequence mining model. The method converts original medication datum into a medication event occurrence sequence with category type, converts each medication event node of the medication event occurrence sequence with category type into a multidimensional vector representation of euclid space, and then weighted summation is conducted for all the historical events according to the previous node of the medication event to be predicted to form a character representation of the memory of a predict event and served as a standard input of a classifier for predicting the next event vector, the multidimensional vector representation of the event to be predicted is served as an output, a predictive model is trained, the multidimensional vector of euclid space is mapped back to the original space with category type, all the medication event sequences are trained, finally the models trained are input to predict future events for the new medication event sequence. The method can use data as many as possible for decision-making, thereby reducing decision-making mistakes.

Various embodiments provide systems, computer program products and computer implemented methods. Some embodiments include a method of updating an expert corpus set, including obtaining a query from a user, obtaining a raw data source, determining a relevance score for the raw data source with respect to the query, by performing actions including creating a first vector of statistical variables for the query using at least one natural language processing (NLP) socket, the statistical variables having category types, creating a second vector for the first raw data source, having category types that are the same as those for the query and generating a hypothesis regarding the relevance of the raw data source, testing the hypothesis by comparing relative statistical variables, calculating a gradient between the vectors to determine the relevance score and updating the expert corpus set with the raw data in response to the relevance score exceeds a threshold.

A method and apparatus for automatic white balancing of an image. The method includes retrieving scene analysis of the image, determining at least one of the type of the scene and a scene content map utilizing the scene analysis of the image, performing scene adaptive white balance, if overall scene category type is used, perform white balance by applying global R, G, B gains optimized for the global scene type, and if scene segmentation map is used, perform locally adaptive white balance by applying an R, G, B gain map optimized for each scene content.

The invention relates to the technical field of network ordering, and discloses a food type management method and device. The method comprises the steps of establishing category information accordingto all food products, wherein the category information comprises a category name, a category code and a category type; establishing single-product information for each food product, wherein the single-product information comprises the category that the food product belongs, state information and the price information; combining a plurality of food products into a package, establishing the packageinformation for the package, wherein the package information comprises category information and single-product information corresponding to each food product in the package. The food product attributes are enriched, more food information is presented for users, and maintenance is facilitated. The management efficiency of food product is improved, and different food products are combined into nutrition packages, thereby improving user experience.

A system, a method and a computer program product are provided in order to determine the value of a parcel based upon a number of different attributes and keywords relating to a number of features of the parcel. In the context of a system, a receiver module is configured to receive one or more attributes of the first parcel and one or more keywords of the first parcel. Each keyword may include a category type and a corresponding value. The system may also include an associative memory configured to compare the one or more attributes and one or more keywords of the first parcel with attributes and keywords, respectively, of a plurality of other parcels in order to determine a plurality of similar parcels. Further, the system may include an assessment module configured to determine the value of the first parcel based upon the prices of the plurality of similar parcels.

The invention relates to an extended category type data rapid labeling method. The method comprises the following steps of (1) obtaining an initial data set with a unified label A; (2) further dividing A into a plurality of subclasses such as a, b, c and the like in combination with the existing data set; (3) selecting a part of the initial data set as a sample, manually modifying the annotation file, and quickly renaming the annotation as a, b, c and the like from A to obtain an annotation sample; (4) based on the annotation sample, training a model by using a neural network, and pre-annotating residual data in the initial data set by using the obtained model to obtain pre-annotated data; (5) performing manual fine adjustment on the pre-annotated data to ensure that all related data labels are accurate, performing model training optimization based on the initial data and the fine adjustment data, training a better model based on more annotation samples, and finally accurately annotating all the data to improve the annotation efficiency; the method can meet the requirements of quick and accurate labeling, and better serves the practical application.

The present invention provides a fault scenario simulation method for an active distribution network based on a characteristic waveform. The method comprises the following steps: establishing a typical distribution network fault model to assort each monitoring site and obtain a characteristic waveform of each type of monitoring site by simulating; matching each monitoring site of a distribution network under test with category types in the distribution network fault model; disposing a tester in each monitoring site of the distribution network under test; for each monitoring site of the distribution network under test, predicting a fault waveform through calculation according to the characteristic waveform and an actual parameter thereof, and outputting the predicted fault waveform to the tester; setting a state sequence for each monitoring site; and after accurately setting time of the tester in each monitoring site, separately outputting the predicted fault waveform to a distribution terminal according to the state sequence to finish the simulation of the active distribution network. The simulation method is simple in modeling, effectively reduces the preparation time and testing fees of the simulation testing, and improves testing efficiency.

The invention discloses a waste and old material automatic recovery system and method based on the Internet of Things information dissemination technology. The system comprises a weighing module, a detection module, an application network platform and an application APP, wherein the weighing module and the detection module are installed on recyclingrecovery equipment; the application network platform is deployed on a server computer, and the application APP arranged on the mobile terminal; wherein the recycling equipment management platform and the client APP perform mutual operation and information sharing through a network, the mobile terminal applications are divided into client applications and administrator applications, a client scans a two-dimensional code of the recycling equipmentthrough the mobile terminal applications to open a box and put waste products, collection is completed at a mobile phone terminal, the recycling equipment detects categories types according to categories, automatic weighing is performed, and payment is completed. For an administrator APP, the state of each piece of equipment can be checked in real time, including commodity storage amount information, equipment fault information, early warning information and the like, and work orders of field staff and processing of the equipment can be dispatched.

In non-limiting examples of the present disclosure, systems, methods and devices for generating and displaying interactive charts from hierarchical datasets are presented. A dataset comprising a plurality of data points may be received, wherein each of the data points has a score and a weight associated with it, and wherein each of the plurality of data points is a member of a hierarchical category type of the dataset. A weight value that each hierarchical category type contributes to the dataset, relative to each other category type, may be calculated. A score for each of the hierarchical category types may be calculated. A plurality of objects that each represent one of the hierarchical category types may be displayed in a hierarchical format in association with an indication of the calculated score for each of the objects.

A system, method and computer program product are provided in order to determine the value of a parcel based upon a number of different attributes and keywords relating to a number of features of the parcel. In the context of a system, a receiver module is configured to receive one or more attributes of the first parcel and one or more keywords of the first parcel. Each keyword may include a category type and a corresponding value. The system may also include an associative memory configured to compare the one or more attributes and one or more keywords of the first parcel with attributes and keywords, respectively, of a plurality of other parcels in order to determine a plurality of similar parcels. Further, the system may include an assessment module configured to determine the value of the first parcel based upon the prices of the plurality of similar parcels.

The invention relates to a safe parsing method for an IOS (Iphone Operating System) dictionary. The method comprises the following steps that: inputting dictionary parsing data: firstly, judging whether the dictionary parsing data is a basic data type or not, secondly, judging whether a default value is required or not, if the default value is required, storing the default value, then, judging whether an input value is empty or not, and carrying out further parsing when the input value is not empty; during further parsing, firstly, judging whether the input is a category type or not, if the input is the category type, further judging whether the category type is in the presence or not, and otherwise, further judging whether a basic data type function is in the presence or not; and when a judgment result shows that the category type and the basic data type function are both in the presence, continuously carrying out parsing, i.e., calling a parsing algorithm to convert the dictionary parsing data into OC data, outputting a parsing value if the dictionary parsing data is successfully converted into the OC data, if the dictionary parsing data fails to be converted into the OC data, judging whether the default value is in the presence or not, outputting the default value if the default value is in the presence, and otherwise, outputting a null value. By use of the method, when theOC data is obtained by parsing, reliability is good, safety is high, an App is effectively protected, the App is not influenced by wrong data, program crash is effectively avoided, and data safety isimproved.