33 results about "Result Category" patented technology

A method and system dynamically and contextually manage information in an electronic computational environment. In one aspect, a desired project provides a context for management of a plurality of information elements, each element being in at least one of a plurality of categories. Each category in turn is a member of a category set, and the category set includes data category, function category, and result category. The context corresponds to at least one model that is defined by the elements and a set of rules governing permissible relationships among the elements. The method includes: receiving an input to the environment specifying a relationship among at least two information elements; using an integrity engine, operating to enforce such rules, to verify dynamically correctness of the relationship specified; and upon acceptance of the relation by the integrity engine, storing automatically the relationship specified, so as to permit dynamic interaction with respect to the context. The relation can be specified and implemented on the fly, without a preconceived design process. Related systems are also provided.

A system and related techniques generate alternative search terms derived from a set of search results. A user may input a set of search terms such as keywords or other inputs, and receive a set of search results back, for instance in rank order of estimated relevance to the user's search terms and search intention. In addition to the hyperlink or other results may have associated with them a set of selectable alternative search links, for instance indicating “show me more with titles like this” when for instance a Web page title contains the user's search terms. Other results may present other attributes, depending on the evaluated distinctiveness potential alternative information content of attributes of that Web page or other result, which attributes may further include, for example, the presence of image files, PDF™ files, audio or video files or attachments, Web pages or other hits indicating certain date ranges, or other attributes or characteristics. In embodiments an attribute or attribute of a result may be assessed for inclusion as an alternative search attributes or limiter based on the attribute's deviation in an attribute space from an average of the attributes of the original set of search results, or otherwise. A user may click or otherwise select the alternative search suggestion, for instance indicating “show me more PDFs” and be presented with an updated set of search results containing Web pages or other hits, links or results each of which is, contains or has attached a file or content of that type. Users may thus receive categories of search results more closely aligned with their search intent when characteristic attributes may be a factor in desired content.

This invention relates to determining page elements to display in response to a search. A method embodiment of this invention determines a page element based on a search result. The method includes: (1) determining a set of result classifications based on the search result, wherein each result classification includes a result category and a result score; and (2) determining the page element based on the set of result classifications. In this way, a classification is determined based on a search result and page elements are generated based on the classification. By using the search result, as opposed to just the query, page elements are generated that corresponds to a predominant interpretation of the user's query within the search results. As result, the page elements may, in most cases, accurately reflect the user's intent.

A method and system is provided for controlling search criteria when searching databases using active controls. In one aspect, a search criteria control bar (SCCB) displays results of a search by identifying category selections and keywords. Category selections may be identified by a unique delimiter and any keywords may also be identified by another unique identifier. A user may optionally narrow a search by selecting any active category or active keyword(s) that may be identified in the results summary by simply clicking on the appropriate choice. This may cause only those pages associated with the selected keyword or category to be displayed. Conversely, a user may alter a search by eliminating a keyword or category from the results by a one-click action. Further, the search and results may be limited by user preferences. In this manner, a user may be able to intuitively control searches with more refinement and efficiency.

A method, system and computer program product for receiving a spoken request to obtain indexed results from a database. Like result types are assigned to categories, and within each category is a plurality of result entries. The result indices are hexadecimal encoded, and each hexadecimal encoding is preceded by an initial character representing the result category. A speech recognition system is engaged, which processes the spoken request. When a item is requested, the respective category is implicitly known by the index returned, and the index provides direct access within a database to the corresponding result based on the phonetics of the request.

The invention provides a database overlap mode abstract generating method based on multi-label propagation. The overlap mode abstract generating method comprises: mapping database mode information into a multi-label graph model; clustering the database mode information with a multi-label propagation algorithm, and generating an overlap group; clustering the overlap group with a hierarchical clustering algorithm, and further generating result categories of appropriate sizes; and and finally, on the basis of an information entropy and a random walk model, selecting a topic table for each result category, thus generating the final overlap mode abstract of the database. According to the overlap mode abstract generating scheme provided by the invention, a user can be provided with a more accurate and more meaningful database overlap mode abstract, thus helping the user to understand the database information quickly.

The invention provides a deformable object grabbing method and device and a computer readable storage medium. The deformable object grabbing method comprises the following steps: the visual information of a to-be-grabbed deformable object is obtained through an event camera, and positioning and three-dimensional reconstruction are carried out on the to-be-grabbed deformable object; a grabbing point set is obtained on the surface of the to-be-grabbed deformable object subjected to three-dimensional reconstruction; visual and tactile information is collected at the grabbing moment of each grabbing point in the grabbing point set through the event camera and a tactile sensor; the collected visual and tactile information is input into a trained grabbing quality evaluation network, the pre-result category of grabbing is judged, and the result category comprises sliding grabbing, stable grabbing and excessive grabbing; if the result category is stable grabbing, the deformable object to be grabbed is grabbed; and if the result is sliding grabbing or excessive grabbing, grabbing pre-attempt is continuously conducted on the grabbing points in the grabbing point set till the grabbing points with the stable grabbing result category are found.

The invention relates to systems and methods of providing in-view and out-of-view request-related result regions for respective result categories. The system may facilitate result presentation by providing, in response to a user request, at least one region that is designated to initially be in-view and at least one region that is designated to initially be out-of-view where: (i) the initial in-view region comprises one or more results related to the user request and a first category; and (ii) the initial out-of-view region comprises one or more results related to the user request and the second category. A result related to a category may comprise a result related to a specific topic, a result of a specific type, a result from a specific source, or other result. A user request may comprise a query, a command, or other user request.

The invention provides a wafer test pattern yield loss calculation method comprising the following steps: grouping chips included in all test result categories in a wafer bin map to get multiple chip groups; getting multiple characteristic values of each chip group based on the chips included in each chip group; comparing the characteristic values with a model database to get test patterns corresponding to the chip groups; and calculating the yield loss of each test pattern. Therefore, a variety of test patterns in a wafer bin map can be identified automatically, and the yield loss of each test pattern can be calculated automatically.

The present invention provides a simulation method for an apparatus which produces refrigeration effect by means of heat exchange between refrigerant and air, wherein the simulation method provides good expandability to allow new parts to be added and so on. The method includes the steps of: classifying models which represent phenomena occurring in various components of an apparatus for producing refrigeration effect by means of heat exchange between refrigerant and air into categories independent of one another; defining the resulting categories as classes; defining an abstract class by extracting characteristics common to a plurality of similar parts contained in each category if these parts need to be distinguished for the purpose of calculation; providing, under the abstract class, as many subclasses which inherit character of the abstract class as there are necessary types of part; implementing a phenomenological model of each defined class; and creating a simulation program in an object-oriented language based on the classes.

The invention discloses a scientific research project budget auditing method based on big data, comprising the following steps: obtaining historical records of scientific research project budget audit, and transmitting the historical records to a cloud computing platform; obtaining first expert evaluation information, and dividing scientific research project budget audit results into multiple audit result categories; establishing correlations between each historical record of scientific research project budget audit and the multiple audit result categories; obtaining second expert evaluation information, and generating suggestion information for each of the multiple audit result categories; establishing a neural network for judging scientific research project budget audit results; obtaining budget audit information of a to-be-judged scientific research project, and transmitting the budget audit information of the to-be-judged scientific research project to the cloud computing platform;and based on the budget audit information of the to-be-judged scientific research project, using the neural network for judging scientific research project budget audit results to generate a scientific research project budget audit result for a to-be-judged scientific research project.

A query results preview generation method and system that receives a preliminary query while a query for a search is being constructed, determines a distribution of result items that would be retrieved if the search were executed using the preliminary query, among a new result category including new result items and a previous result category including result items previously retrieved in a session, generates the query results preview using the distribution of result items that would be retrieved if the search were executed using the preliminary query, and provides the query results preview while the query for the search is being constructed and prior to execution of the search using the query.

The invention discloses a classification model prediction result processing method, apparatus and device, and a storage medium, and relates to artificial intelligence, machine learning and big data technologies in the computer technology. According to the specific implementation scheme, ciphertext calculation is carried out based on a classification prediction result of a ciphertext, category label data of the ciphertext and statistical information, index information of the ciphertext of the classification prediction result is obtained, and a calculation participant does not need to obtain plaintexts of the classification prediction result, the category label data and the statistical information; based on the classification prediction result, the category label data and the statistical information of the ciphertext, the calculation of the index information can be completed by performing ciphertext calculation, the classification prediction result, the category label data and the statistical information of the ciphertext cannot be decrypted in the calculation process of the index information, and the data cannot be leaked. On the premise of ensuring that a classification predictionresult, classification label data and statistical information are not leaked, evaluation index information of a model can be obtained through calculation, and the data safety is improved.

The invention discloses a mode classification method for dimensional check results of a flat panel display layout, belongs to the field of semiconductor integrated circuit design automation, and mainly relates to how to classify the dimensional check results and improve manual screening efficiency. The dimensional check of the flat panel display layout uses an integrated circuit layout for reference, but a handling situation is more complex, and not all violation results need to be subjected to layout modification. At present, violation result screening depends on artificial judgment, and the violation results needed to be subjected to layout modification are screened out from all hundreds of thousands of results, so that the working efficiency is very low. According to the method, the results violating the dimensional check and surrounding environments are defined as mode features, and result categories are classified according to the mode features, so that hundreds of thousands of the results can be classified into dozens of to hundreds of categories. During manual screening, each category only needs to be judged once, so that the workload is reduced to the scale of dozens of to hundreds of the categories from hundreds of thousands of the results, the layout check efficiency is remarkably improved, the iterative modification cycle of the layout is shortened, and the design process is accelerated.

A construction waste classification method based on a CNN comprises the following steps that 1, construction waste pictures are collected, a construction waste material data set is self-made, and data set samples are enriched through data enhancement; step 2) using the lightweight self-made convolutional neural network model for construction waste classification: inputting the preprocessed pictures into the trained network model, and finally outputting a group of probability values, the category with the maximum probability value being a result category; 3) in the CNN, performing convolution operation on the image through a convolution kernel, extracting image feature information, in construction waste classification application, noise in data set image information is inevitable, and in order to reduce noise transmission, using a maximum pooling mode, and reducing feature image dimensions; and (4) an AdamOptimizer optimizer is used for optimizing model parameters, and therefore accurate classification of four types of construction waste materials including red bricks, foam, concrete and PVC is achieved. According to the invention, accurate classification of four types of construction waste materials is realized.

The invention discloses a citation difference matching method and apparatus based on MGLSTM, and a storage medium. The method comprises the steps of obtaining titles, authors and publishing house metadata of a to-be-discriminated citation and a trusted citation; respectively segmenting and converting titles, authors and publishing house metadata of the citation to be discriminated and the crediblecitation into a title embedding vector pair, an author embedding vector pair and a publishing house embedding vector pair by taking words and characters as segmentation granularities; respectively learning the weight of each embedded vector pair based on an attention mechanism, and updating each embedded vector pair based on the corresponding weight; and inputting each updated embedded vector pair into a pre-trained citation difference identification model, and outputting a citation difference matching result category. Citation fine-grained discrimination can be carried out, and the difference type of the citation is judged; by introducing an attention mechanism, the mutual relation between metadata of a to-be-discriminated citation and metadata of a trusted citation can be better represented, feature information in two directions is reserved at the same time in combination with a bidirectional LSTM network, and the discrimination precision is ensured.

The invention discloses an active learning short text classification method and system based on sampling frequency optimization, broadens the active learning optimization direction, and provides a simple and effective optimization framework widely used in the industry. According to the technical scheme, the method includes enabling a text classifier to learn labeled data; sampling and evaluating the unlabeled data based on the learning result of the text classifier and selecting the most valuable data; and manually labeling the selected data and adding the selected data into the labeled data,and repeating the steps until the number of iterations reaches the upper limit or the accuracy reaches the standard. In the sampling evaluation process, the labeled data is classified according to thecategory to which the labeled data belong, and the labeled data volume of each category is counted to obtain respective sampling frequency data; for the unlabeled data, the invention includes evaluating the unlabeled data to obtain an initial evaluation score and a prediction result category of the initial evaluation score, then obtaining corresponding sampling frequency data according to the prediction result category, and obtaining a final evaluation score based on the initial evaluation score and the sampling frequency data of the corresponding category.

The invention provides an image recognition method based on category consistency deep learning. The method comprises the following steps: firstly, marking a training set by using an automatic cooperative positioning method to obtain a category-consistent binary mask; constructing the recognition method by using a feature extraction module, a classifier module and a category-consistent mask learning module; during each iterative training, enabling the feature extraction module to perform feature extraction on the input image; enabling the classifier module to carry out calculation according to the extracted features and give a recognition result; enabling the category-consistent mask learning module to predict a category-consistent binary mask according to the extracted features; calculating a loss value in combination with cross entropy loss and a category-consistent loss function, performing back propagation, and adjusting network parameters of the recognition method, and repeating the steps until the training is finished, and selecting the optimal network parameters as recognition model parameters. By implementing the method, learning of the network on key features can be promoted in a self-supervised learning mode, and high-robustness and high-accuracy image recognition is realized.

The invention provides a bays cross model-based government affair approval intelligent screening method. The method comprises the following steps of S1, performing word segmentation on approval item information; S2, filtering stop word lists of a word segmentation result; S3, generating an approval item word bag model; S4, performing cross multiplication on the approval item word bag vector and the historical approval category word segmentation probability matrix of the same business domain item to obtain a probability list that the item belongs to the approval category; The historical examination and approval category word segmentation probability matrix executes the historical examination and approval item word bag model obtained in the step S1-step S3 through historical examination andapproval item information, and the historical examination and approval item word bag model and an examination and approval result category word bag are trained through a naive Bayesian model and a cross model and are obtained through a convergence result. The efficiency can be greatly improved, and the labor cost can be greatly reduced.