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353 results about "Bayes classifier" patented technology
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In statistical classification the Bayes classifier minimizes the probability of misclassification.
Generating audience analytics
The present invention is directed to generating audience analytics that includes providing a database containing a plurality of user input pattern profiles representing the group of users of terminal device, in which each user of the group is associated with one of the plurality of user input pattern profiles. A clickstream algorithm, tracking algorithm, neural network, Bayes classifier algorithm, or affinity-day part algorithm can be used to generate the user input pattern profiles. A user input pattern is detected based upon use of the terminal device by the current user and the user input pattern of the current user is dynamically matched with one of the user input pattern profiles contained in the database. The current user is identified based upon dynamic matching of the user input pattern generated by the current user with one of the user input pattern profiles. The present invention processes each user input pattern profile to identify a demographic type. A plurality of biometric behavior models are employed to identify a unique demographic type. Each user input pattern profile is compared against the plurality of biometric behavior models to match each user input pattern profile with one of the biometric behavior models such that each user input pattern profile is correlated with one demographic type. Audience analytics are then based upon the identified demographic types.
Owner:COX COMMUNICATIONS
Biopotential Waveform Data Fusion Analysis and Classification Method
InactiveUS20080208072A1Improve classification accuracyElectroencephalographyMedical data miningTraining phaseData source
Biopotential waveforms such as ERPs, EEGs, ECGs, or EMGs are classified accurately by dynamically fusing classification information from multiple electrodes, tests, or other data sources. These different data sources or “channels” are ranked at different time instants according to their respective univariate classification accuracies. Channel rankings are determined during training phase in which classification accuracy of each channel at each time-instant is determined. Classifiers are simple univariate classifiers which only require univariate parameter estimation. Using classification information, a rule is formulated to dynamically select different channels at different time-instants during the testing phase. Independent decisions of selected channels at different time instants are fused into a decision fusion vector. The resulting decision fusion vector is optimally classified using a discrete Bayes classifier. Finally, the dynamic decision fusion system provides high classification accuracies, is quite flexible in operation, and overcomes major limitations of classifiers applied currently in biopotential waveform studies and clinical applications.
Owner:NEURONETRIX SOLUTIONS
Methods for display, notification, and interaction with prioritized messages
InactiveUS7120865B1Digital computer detailsTransmissionLevel of detailSupport vector machine classifier
Prioritization of document, such as email messages, is disclosed. In one embodiment, a computer-implemented method first receives a document. The method generates a priority of the document, based on a document classifier such as a Bayesian classifier or a support-vector machine classifier. The method then outputs the priority. In one embodiment, the method includes alerting the user based on an expected loss of now-review of the document as compared to an expected cost of alerting the user of the document, at a current time. Several methods are reviewed for display and interaction that leverage the assignment of priorities to documents, including a means for guiding visual and auditory actions by priority of incoming messages. Other aspects of the machinery include a special viewer that allows users to scope a list of email sorted by priority so that it can include varying histories of time, to annotate a list of messages with color or icons based on the automatically assigned priority, to harness the priority to control the level of detail provided in a summarization of a document, and to use a priority threshold to invoke an interaction context that lasts for some period of time that can be dictated by the priority of the incoming message.
Owner:MICROSOFT TECH LICENSING LLC
Face detection method and apparatus
InactiveUS7162076B2Improve accuracyHigh precisionCharacter and pattern recognitionPattern recognitionFace detection
A method and apparatus as disclosed for face detection within images. A new vector, the discriminating feature analysis vector, is introduced to represent an image to be analyzed, from the DFA vector as processed using a Bayesian Classifier technique. The methodology provides a computationally efficient manner in which to detect faces with relatively low probability of error and false detection rate.
Owner:NEW JERSEY INSTITUTE OF TECHNOLOGY
Dynamic prediction of online shopper's intent using a combination of prediction models
ActiveUS20140222503A1Accurate model 's prediction of 'sImprove accuracyMarket data gatheringMachine learningMotion estimation
Online browsing behavior is used to predict the intent of online users dynamically. The category of online user is predicted and the prediction can be used to provide assistance to the user, if required. Such prediction is based on a combination of a Naïve's Bayes classifier and a Markov model.
Owner:24 7 AI INC
Method for automatically assigning priorities to documents and messages
InactiveUS7194681B1Data processing applicationsDigital computer detailsDistractionText categorization
Methods for prioritizing documents, such as email messages, is disclosed. In one embodiment, a computer-implemented method first receives a document. The method assigns a measure of priority to the document, by employing a text classifier such as a Bayesian classifier or a support-vector machine classifier. The method then outputs the priority. In one embodiment, the method includes alerting the user about a document, such as an email message, based on the expected loss associated with delays expected in reviewing the document as compared to the expected cost of distraction and transmission incurred with alerting the user about the document.
Owner:MICROSOFT TECH LICENSING LLC
Emotion analyzing system and method
InactiveCN103034626AEasy to judgeImproving the performance of sentiment orientation classificationSpecial data processing applicationsViewpointsSupport vector machine classifier
The invention discloses an emotion analyzing system and an emotion analyzing method. The system comprises a language database establishing module, a data preprocessing module, a perspective sentence identifying module and an emotion tendency analyzing module, wherein the language database establishing module is used for establishing a training set needed by perspective sentence identification and emotion tendency analysis; the data preprocessing module is used for preprocessing sentences in the training set; the perspective sentence identifying module is used for performing perspective sentence identification on the preprocessed sentences by adopting a support vector machine classifier and a Bayes classifier respectively, and integrally processing results of the classifiers to obtain a final classifying result; and the emotion tendency analyzing module is used for directly classifying the preprocessed sentences into positive, negative and non-viewpoint sentences respectively on the basis of the support vector machine classifier and the Bayers classifier, and integrating the classifying results of the vector machine classifier and the Bayers classifier through an integration formula to obtain a classifying result of a current sentence. Due to the adoption of the emotion analyzing system and the emotion analyzing method, the viewpoint sentence judging and emotion tendency classifying properties of Chinese microblogs can be improved.
Owner:SHANGHAI JIAO TONG UNIV
Number plate identification method and identification system thereof
The invention belongs to the technical field of vehicle identification and particularly discloses a number plate identification method and an identification system of the number plate identification method. The method comprises the steps of number plate image positioning, character separation and character identification, wherein the character identification step comprises pre-treatment, coarse classification, Chinese character identification and number and letter identification. Through the improvement on a Chinese character identification method (through a Gabor filter and a minimum distance classifier) and a number and letter identification method (based on correlation feature selection (CFS) and a Bayes classifier), the number plate Chinese character identification rate and the number plate number and letter identification rate are greatly improved.
Owner:ZHUHAI YEARING TECH
Macroblock level no-reference objective quality estimation of video
InactiveUS20100316131A1Image enhancementPulse modulation television signal transmissionReduced modelFeature vector
A no-reference estimation of video quality in streaming video is provided on a macroblock basis. Compressed video is being deployed in video in streaming and transmission applications. MB-level no-reference objective quality estimation is provided based on machine learning techniques. First the feature vectors are extracted from both the MPEG coded bitstream and the reconstructed video. Various feature extraction scenarios are proposed based on bitstream information, MB prediction error, prediction source and reconstruction intensity. The features are then modeled using both a reduced model polynomial network and a Bayes classifier. The classified features may be used as feature vector used by a client device assess the quality of received video without use of the original video as a reference.
Owner:GOOGLE TECH HLDG LLC
Integration of a computer-based message priority system with mobile electronic devices
InactiveUS7444384B2Multiplex system selection arrangementsSpecial service provision for substationPagerText categorization
Methods for integrating mobile electronic devices with computational methods for assigning priorities to documents are disclosed. In one embodiment, a computer-implemented method first receives a new document such as an electronic mail message. The method assigns a priority to the document, based on a text classifier such as a Bayesian classifier or a support-vector machine classifier. The method then alerts a user on an electronic device, such as a pager or a cellular phone, based on an alert criteria that can be made sensitive to information about the location, inferred task, and focus of attention of the user. Such information can be inferred under uncertainty or can be accessed directly from online information sources. One embodiment makes use of information from an online calendar to control the criteria used to make decisions about relaying information to a mobile device.
Owner:MICROSOFT TECH LICENSING LLC
Video fire hazard smoke detecting method based on color saturation degree and movement mode
InactiveCN101441771AAccurate detectionImprove anti-interference abilityImage analysisCharacter and pattern recognitionVideo imageFalse alarm
The invention discloses a method for detecting fire disaster smog by video on the basis of color saturation and motion mode, which comprises the following steps: firstly, extracting a foreground motion block from a video image acquired by a monitoring camera through a difference method; secondly, detecting the color saturation of the foreground motion block, estimating the direction of the motion block, and calculating the cumulant and the main moving direction of the motion block; and thirdly, calculating the color saturation detection percentage of each region, the average cumulant and the main moving direction ratio to form a characteristic vector, and adopting a Bayesian classifier to judge whether the smog is the fire disaster smog. The detection of the color saturation reflects a rough color distribution of the smog and eliminates a large amount of foreground interfering objects with glowing colors. The color detection in a blocking mode further improves the anti-interference performance of a system. The cumulant shows the characteristic of continuous movement nearby a smoldering point of the smog, and has very good anti-interference performance for a non-reciprocating object. The comprehensive utilization of the color saturation detection percentage, the average cumulant and the main movement ratio can greatly reduce the rate of false alarm for the system.
Owner:UNIV OF SCI & TECH OF CHINA
Artificial intelligence system for track defect problem solving
InactiveUS6954678B1Easy searchSemiconductor/solid-state device testing/measurementVolume/mass flow measurementAlgorithmSmart technology
A system and method facilitating lithography defect solution generation is provided. The invention includes a defect solution component and a defect alert component. The defect solution component provides potential solution(s) to a defect within the lithography process utilizing artificial intelligence technique(s) (e.g., Bayesian learning methods that perform analysis over alternative dependent structures and apply a score, Bayesian classifiers and other statistical classifiers, including decision tree learning methods, support vector machines, linear and non-linear regression and / or neural network).
Owner:GLOBALFOUNDRIES INC
Probability-based state modification for query dialogues
ActiveUS20140172899A1Natural conversational interactionMathematical modelsDigital data processing detailsHigh probabilityInformation retrieval
A device may facilitate a query dialog involving queries that successively modify a query state. However, fulfilling such queries in the context of possible query domains, query intents, and contextual meanings of query terms may be difficult. Presented herein are techniques for modifying a query state in view of a query by utilizing a set of query state modifications, each representing a modification of the query state possibly intended by the user while formulating the query (e.g., adding, substituting, or removing query terms; changing the query domain or query intent; and navigating within a hierarchy of saved query states). Upon receiving a query, an embodiment may calculate the probability of the query connoting each query state modification (e.g., using a Bayesian classifier), and parsing the query according to a query state modification having a high probability (e.g., mapping respective query terms to query slots within the current query intent).
Owner:MICROSOFT TECH LICENSING LLC
Human body target detection and sexuality recognition method in video monitoring
InactiveCN101482923AImprove gender identityReduce adverse effectsCharacter and pattern recognitionVideo monitoringHuman body
The invention discloses a detection and gender identification method of a human body object in video supervision, which comprises: (a) establishing a column diagram of foreground skin and background in an HSV color space according to a collected image database; (b) utilizing the Bayes classifier to process foreground and background judgement for each pixel point of an input video, so as to cut out a human body skin region in the video; (c) utilizing biological specificity of human body skin-color to cut the foreground skin and the background again in a complex color space (E, R / G, H) so as to eliminate interference of the objects with similar skin-color in the background to obtain an accurate human body object; (d) utilizing a mode identification method according to the face image in the obtained human body object to process gender identification. The invention takes the feature of face skin of the human body as a main mark of the human body and detects the human body object in the video image so as to overcome the adverse effect caused by illumination changes and the interference of similar color in the background, and improves correct identification of the gender of the object.
Owner:QINGDAO UNIV OF SCI & TECH
Generating audience analytics
Owner:COX COMMUNICATIONS
System and Method for Lesion Detection Using Locally Adjustable Priors
According to an aspect of the invention, a method for training a classifier for classifying candidate regions in computer aided diagnosis of digital medical images includes providing a training set of annotated images, each image including one or more candidate regions that have been identified as suspicious, deriving a set of descriptive feature vectors, where each candidate region is associated with a feature vector. A subset of the features are conditionally dependent, and the remaining features are conditionally independent. The conditionally independent features are used to train a naïve Bayes classifier that classifies the candidate regions as lesion or non-lesion. A joint probability distribution that models the conditionally dependent features, and a prior-odds probability ratio of a candidate region being associated with a lesion are determined from the training images. A new classifier is formed from the naïve Bayes classifier, the joint probability distribution, and the prior-odds probability ratio.
Owner:SIEMENS HEATHCARE GMBH
Intelligent outpatient guiding method and device, computer device and storage medium
PendingCN108922608AImprove accuracyScientifically accurate reflectionCharacter and pattern recognitionHealthcare resources and facilitiesFeature vectorPatient registration
The present application relates to an intelligent outpatient guiding method and device, a computer device and a storage medium. The method includes: acquiring patient inquiry data; extracting inquiryelement features from the patient inquiry data; converting the inquiry element features into feature vectors; inputting the feature vectors into a preset neural network classifier to obtain a first department matching probability; inputting the feature vectors into a preset Bayesian classifier to obtain a second department matching probability; and generating a department recommendation result isaccording to the first department matching probability and the second department matching probability. The method can improve the accuracy of patient registration.
Owner:PING AN MEDICAL TECH CO LTD +1
Anomaly detection method based on network flow analysis
ActiveCN103023725AImprove performanceReduce the dimensionality of traffic featuresData switching networksFeature DimensionFeature set
The invention discloses an anomaly detection method based on network flow analysis. A complete network flow initial feature set is provided by deeply analyzing an IP (internet protocol) data packet, and the performance of an anomaly detection system can be fundamentally improved. A feature subset for anomaly detection is dynamically selected according to different types of network anomalies, finally, the class of an unknown sample is predicted according to the feature subset by a Bayes classifier, and the anomalies are prompted if the unknown sample is abnormal according to a prediction result. A data preprocessing module is used for processing preliminary data; a feature selecting module is used for selecting the proper feature subset for anomaly detection according to the types of the anomalies; and an anomaly detection module is used for prompting the anomalies after the anomalies are found. By the aid of dynamic feature selection algorithm, the optimal feature subset for detecting the anomalies can be dynamically selected according to the different types of anomalies, flow feature dimensions for detecting the anomalies can be reduced, and anomaly detection accuracy is improved.
Owner:BEIJING UNIV OF TECH
Methods for routing items for communications based on a measure of criticality
InactiveUS20060041583A1Digital data information retrievalDigital data processing detailsText categorizationSupport vector machine classifier
Owner:MICROSOFT TECH LICENSING LLC
Text sentiment classification method and system
ActiveCN102682130AImprove classification performanceReduce adverse effectsSpecial data processing applicationsText categorizationWord list
The embodiment of the invention discloses a text sentiment classification method, which comprises the steps of finding a sentiment word in a text to be classified by referring to a preset sentiment word list, and acquiring a sentiment polarity corresponding to the sentiment word according to the sentiment word; utilizing two polarity conversion rules to judge whether the sentiment word has polarity conversion or not, and calculating probability of each word in the text to be classified appearing in the text of each polarity according to the sentiment polarity of the sentiment word and the polarity conversion result of the sentiment word; and utilizing a Bayes classifier model to classify the text to be classified according to the probability of each word appearing in the text of each polarity. According to the classification method, the classification effect is far higher than that of a traditional text sentiment classification method, the unfavorable influence of the sentiment word having the sentiment polarity conversion on the classification effect of the text can be avoided, and the classification accuracy of the text sentiment can be improved.
Owner:SUZHOU UNIV
Crowd behavior identification method
InactiveCN103854027AEasy to observeEasy to analyzeCharacter and pattern recognitionSlide windowVideo sequence
The invention provides a crowd behavior identification method. The crowd behavior identification method comprises the steps that a movement track contained in a predefined movement mode is divided into a data point set, the data point set serves as a training sample of a Bayes classifier, and training is carried out through the Bayes classifier to obtain a training model; crowd movement information is obtained from a video sequence; traversal is carried out on the crowd movement information through a sliding window to obtain a movement track, the movement track is expressed through discrete track points, and the track points are clustered to obtain a detection movement mode; the detection movement mode is divided into a track point set, and the track point set serves as a test set to be input into the training model; a result of matching between the test set and the predefined movement mode is fed back by the training model, if matching is successful, crowd behaviors are determined as normal behaviors, and if matching fails, the crowd behaviors are determined as abnormal behaviors.
Owner:BEIJING UNIV OF POSTS & TELECOMM
Method for detecting image spam email by picture character and local invariant feature
InactiveCN101887523AHigh precisionImprove recallCharacter and pattern recognitionData switching networksSupport vector machine classifierText string
The invention provides a method for detecting an image spam email by local invariant features of pictures, which can extract the invariant region feature of junk information in the pictures by using a scale-invariant feature conversion algorithm and extract characters embedded into the pictures to classify the pictures so as to form a feature vector library of the pictures combining two features together. Experiments prove that the recall rate of the spam email can be improved and the program operation time and space can be saved. The method can extract the invariant region feature in the pictures to generate the feature vectors of the pictures, and a support vector machine classifier is used for training and testing. In the method, by utilizing the text messages embedded into the pictures, the text string in the pictures can be excavated by using a graphic character recognition technology and the string can be taken as the feature of the pictures, and the Bayesian classifier is used for training and testing. The feature vector of each picture is composed of the local invariant feature of the picture and the text string; and two types of classifiers are used for classifying by a stacking method to achieve the purpose of detecting the image spam email.
Owner:NANJING UNIV OF POSTS & TELECOMM
Personalized web page filtering method
ActiveCN101470731AAvoid limitations that are difficult to personalizeEasy expression of interestSpecial data processing applicationsPersonalizationFeature extraction
The invention relates to a web page filtering method which can be individually customized, which comprises steps: extracting the characteristics of a user example web page and a training web page base, excavating the attribute of a user interest class based on semi-supervised learning, conducting the characteristic extraction of the user interest class and the characteristic selection, and filtering the personalized web pages based on a Bayesian classifier. The invention provides a novel web page filtering frame driven by examples, the filtering demands of the users can be expressed through web page examples, the user examples can be any type web pages or multi-type composite web pages, and a web page filter in line with the individual demands of the user can be constructed by means of the semi-supervised learning, thereby overcoming the disadvantages of the limitation to single filtering or limited type web page, and unavailable realization of individual customization in a traditional web page filtering method. The method has the advantages of high accuracy, robustness and operation speed, and has excellent application prospects.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI
Road snow and rain state automatic identification method based on feature information classification
A road snow and rain state automatic identification method based on feature information classification comprises a step A of extracting a sample describing feature and constructing a Bayes classifier, and a step B of detecting the road state. The step A comprises a small step A 1 of acquiring a sample image, a small step A 2 of preprocessing the image, a small step A 3 of extracting a sampling image texture attribute value and an average gray value of a road effective coverage sample, a small step A 4 of calculating a probability density function of the road sample, and a small step A 5 of determining an operational rule of a type conditional probability density function to construct the Bayes classifier. The step B comprises a small step B 1 of acquiring a road detecting image, a small step B 2 of preprocessing the image, a small step B 3 of extracting a texture attribute value and an average gray value of a road detecting standard image frame, and a small step B 4 of judging the road surface state of the road. The road snow and rain state automatic identification method based on the feature information classification can adapt to various weather variations and complexity and changes of traffic road states, detection efficiency and accuracy are high, and cost is low, so that the road snow and rain state automatic identification method based on the feature information classification provides reference for traffic safety guarantee and traffic management.
Owner:BEIJING CHENGDA TRAFFIC TECH +1
Vehicle-borne multi-obstacle classification device and method based on Bayes classifier
InactiveCN105631414AReduce classification errorImprove accuracyScene recognitionFeature extractionIn vehicle
The present invention relates to a vehicle-borne multi-obstacle classification device and method based on a Bayes classifier. The classification device comprises a camera and a PC which is connected to the camera. The PC comprises a Kalman filter module for carrying out Kalman filtering on the vehicle front video image collected by a camera and detecting an obstacle target, a characteristic extraction module which is used for carrying out characteristic extraction on the detected obstacle target, and a Bayes classification module which is used for using a Naive Bayes classifier to obtain the classification of the obstacle target according to the characteristics of the obstacle target, wherein the characteristics comprise a symmetry characteristic, a horizontal edge straightness characteristic and a length and width ratio characteristic, and the classification comprises a cyclist / motorcycle rider, a vehicle side face, a vehicle front side and pedestrians. Compared with the prior art, the device and the method have the advantages of high recognition accuracy, strong anti-interference ability, high efficiency, and good real-time performance.
Owner:UNIV OF SHANGHAI FOR SCI & TECH
Big data text classifying method based on cloud computing
InactiveCN104699772AImprove efficiencyImprove accuracySpecial data processing applicationsText database clustering/classificationData setAlgorithm
The invention discloses a big data text classifying method based on cloud computing. The method comprises the following steps: respectively pre-processing training texts with class labels and without class labels to obtain corresponding training data sets; respectively carrying out feature selection on the training data sets to obtain corresponding dimensionally reduced training data sets; respectively calculating the dimensionally reduced training data sets according to a TFIDF weighted model, and respectively converting the training data sets to corresponding one-dimensional vectors; calculating the one-dimensional vectors with class labels according to a bayesian algorithm to obtain the prior probability of each class and the prior probability that each entry belongs to each class, and initializing the parameters of a bayesian classifier; utilizing an EM algorithm to optimize the parameters of the bayesian classifier so as to obtain a classifying model; carrying out text classification on the to-be-classified texts through the classifying model. Through combining a traditional naive bayesian classifying technology and Hadoop and EM algorithms, calculating speed limitation and training data limitation problems in actual application are improved, and the efficiency and the accuracy of the classifier are improved.
Owner:INNER MONGOLIA UNIV OF SCI & TECH
Method for performing emotional tendency classification to microblog by using emoticons
ActiveCN103761239AFast classificationSmall footprint and robustWebsite content managementSpecial data processing applicationsPattern recognitionMicroblogging
The invention discloses a method for performing emotional tendency classification to microblog by using emoticons. The method comprises the following steps: building a neutral emotion set, a passive emotion set and a positive emotion set; building a neutral emotion Bayes classifier by using the neutral emotion set, the passive emotion set and the positive emotion set; building a polar emotion Bayes emotion classifier by using the passive emotion set and the positive emotion set; performing emotion classification to the microblog by using the neutral emotion Bayes classifier and the polar emotion Bayes classifier. According to the method for performing emotional tendency classification to microblog by using emoticons, two sections of classification is built, namely, building the neutral emotion classifier to remove the microblog with neutral emotion, and building the polar emotion classifier to divide the microblog with the polar emotion into the passive emotion and the positive emotion; the classifier is rapid in classifying speed, small in occupied space and robust; attitude of people to current hot topics or events and emotion of net citizens can be accurately understood through the microblog, so that the method for performing emotional tendency classification to microblog by using emoticons has important help for social scientific research and survey.
Owner:NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT
POI (point of interest) Chinese text categorizing method based on local random word density model
InactiveCN103605729AImprove classification accuracyIncrease coverageSpecial data processing applicationsText database clustering/classificationFeature vectorText categorization
The invention discloses a POI (point of interest) Chinese text categorizing method based on a local random word density model. The method includes: judging whether the subject of a text is related to POI or not, and using a modified word concentration, dispersion and frequency method to screen out feature words to build a feature space; performing local area dividing according to the similarity degree of the text and POI category, converting the text into feature vectors in each local area through feature mapping matrixes, and using SVM to perform POI text categorization. The method is good in execution efficiency and categorizing coverage and accuracy. The method is planned to be combined with large knowledge libraries of Hownet so as to capture semantic concepts of low-frequency words and unseen words and further increase the recognition capability of POI text differences, and the problem that good categorization performance cannot be obtained by existing conventional feature evaluation functions and text dimensionality reduction methods is solved.
Owner:段炼
Text classification method and device based on Hadoop
ActiveCN103810293AIncrease upload speedOvercome the disadvantage of not being suitable for handling small filesSpecial data processing applicationsData setText categorization
The invention relates to a text classification method and device based on Hadoop. The text classification method based on the Hadoop comprises the steps that text which is processed in a word segmentation mode is stored in a training data set; the text of different classes is equal in quantity; text files of the training data set are written in a SequenceFile; statistics is carried out on the number of entries contained in the text and the classes of the entries through a MapReduce module, a TF-IDF value of each entry of the text is calculated according to a TF-IDF weighting module, the text is converted into one-dimensional vectors for a Bayes classifier according to the TF-IDF values, statistics is carried out on the lengths of the text of the text files, and weighting is carried out on the one-dimensional vectors according to the lengths; a classification model is obtained; the text to be classified is classified through the classification model. The text classification method based on the Hadoop can solve the problem that data obtained through a traditional training classifier are unbalanced.
Owner:云宏信息科技股份有限公司
Integration of a computer-based message priority system with mobile electronic devices
InactiveUS20090119385A1Multiple digital computer combinationsOffice automationPagerText categorization
Methods for integrating mobile electronic devices with computational methods for assigning priorities to documents are disclosed. In one embodiment, a computer-implemented method first receives a new document such as an electronic mail message. The method assigns a priority to the document, based on a text classifier such as a Bayesian classifier or a support-vector machine classifier. The method then alerts a user on an electronic device, such as a pager or a cellular phone, based on an alert criteria that can be made sensitive to information about the location, inferred task, and focus of attention of the user. Such information can be inferred under uncertainty or can be accessed directly from online information sources. One embodiment makes use of information from an online calendar to control the criteria used to make decisions about relaying information to a mobile device.
Owner:MICROSOFT TECH LICENSING LLC
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