33 results about "Demographic Accounting" patented technology

Systems, apparatus, and methods for determining groups of similar consumers and for identifying a trend in consumer behavior are provided. Likelihoods of a transaction being initiated at various times by one consumer can be calculated based on previous transactions of the consumer. The likelihoods for different consumers can be used to determine a group of similar consumers as a demographic. The likelihoods of a transaction being initiated at various times by a consumer of a demographic (or other entity) can be used to forecast trends (such as a demand for a product) and make business decisions, such as for marketing campaigns, inventory levels (e.g. at particular stores or for all stores), pricing, and store locations. Such likelihoods when focused to a particular category of transactions can provide even greater accuracy.

The invention discloses a precision tourism marketing method based on Internet big data. The method comprises the following steps: extracting target features of a user from user behavior data acquiredby the Internet, establishing a dynamic label in combination with demographic information data, performing user portraying by tagging the user, and then identifying a target user by analyzing, locking and identifying on the basis of user clustering; and calculating the matching degree of the target user and the to-be-marketed product, sending corresponding marketing information by means of the Internet according to the matching degree, continuously obtaining user feedback, and reprocessing the marketing information. According to the method, personalized and differentiated marketing strategiescan be implemented, and the marketing strategies can be adjusted in time according to real-time effect feedback.

A method for determining financial risk tolerance for individuals is characterized by the display of portfolio allocations, potential portfolio losses, and demographic comparisons based on a risk score. The visualization of potential losses, which are based on losses to a hypothetical portfolio in a recent downturn market, help an individual better understand his or her comfort level with various investment strategies. This method is of particular benefit to financial advisors for use with their clients so that client specific investment strategies can more easily be formulated.

The current methods and apparatus provide a system that learns a private attribute, such as gender, based on at least one iteration of presenting an item to a user and receiving ratings from the user for this item. In an exemplary embodiment, the system may solicit ratings for strategically selected items, such as movies for example, and then infers the user's gender. Based on the assessed confidence in the demographic selected, the system may repeat the selection, presentation and ratings of another item. The proposed system can strategically select the sequence of items that are presented to the user for a rating. By selecting the next item to be rated based on a maximum posterior probability confidence, a demographic with a certain threshold of confidence can be inferred. The inventive arrangements are based on novel usage of Bayesian matrix factorization in an active learning setting. Such a system is shown to be feasible and can be carried out using significantly fewer rated items than previously proposed static inference methods.

The invention discloses a product personalized combination recommendation method based on a dobby machine algorithm. The method comprises the following steps: 1, obtaining information and images of all commodities in a shop and demographic information and historical behavior records of a current user to be recommended; 2, initializing feature representations of commodities and current to-be-recommended users to form clusters; 3, constructing a relationship between the to-be-recommended users and the commodities, forming a commodity cluster set, forming commodity groups from the commodity cluster set, calculating corresponding estimated return values, and selecting the commodity group with the maximum estimated return value for recommendation; 4, after the to-be-recommended user receives the recommendation, real feedback is made; and 5, updating the pre-estimation return model and clustering based on real feedback, and adjusting model parameters for re-recommendation. According to the method, the recommendation diversity and accuracy can be improved, so that personalized combined recommendation is realized.

The invention discloses a social user generation method based on emotional tendency analysis. Existing user label generation methods do not consider emotional tendency of users to topics. The method comprises the following steps: on the basis of microblog content, constructing a semantic ontology by adopting a clustering algorithm, acquiring the microblog content of a user to perform sentiment classification, processing microblog information with sentiment tendency marks to obtain a bag-of-words model, extracting words of the bag-of-words model, acquiring category information by utilizing thesemantic ontology, and counting the category information with the sentiment marks; and adding a secondary label to obtain a final label, mapping the demographic information to the corresponding label,constructing a network graph, and generating the user in a semi-supervised manner according to an edge weight between the nodes of the network graph. According to the method, problems that the current social network users cannot automatically generate the users and the generated user tags are inaccurate are solved, the social users conforming to a certain theme can be generated, and a foundationis laid for subsequent social engineering research.

In general, the subject matter described in the specification can be embodied in methods, systems and program products for a verified participant database system that verifies information on potential participants for surveys and promotions that require numerous participants with certain characteristics. Among other features, the verified participant database system aggregates and preferably verifies information, for example, the demographic and purchasing information, of potential participants by receiving permission to obtain information from third-party sources.

The invention provides a total demographic method and device based on terminal signaling data, and a server. The method comprises the steps of: acquiring a preset demographic aperture rule, and searching a database of an operator for corresponding valid phone card number based on the demographic aperture rule; based on the market occupancy rate of the operator, performing sample expansion processing on the number of valid phone cards according to the market occupancy rate so as to obtain the total number of terminal users of the operator; and metering the total number of the terminal users according to a population tending ratio to obtain the total number of population corresponding to the current demographic aperture rule. According to the method and the device, the problems of relativelylow accuracy of the counted population quantity and high cost of traditional home-entry investigation in the prior art are alleviated, and a total population quantity is counted more accurately.

The present invention is a computer-implemented method of online opinion for filtering of poll respondents by demographic and credibility attributes, the method comprising steps of providing a plurality of questions by a plurality of questioners, wherein each the questions are assigned a topic; receiving a plurality of answers by a plurality of respondents, wherein each the respondents has different level of expertise in the topic; receiving a plurality of votes for the answers by the respondents; receiving a plurality of reasons for the answers or the votes by the respondents; storing a demographic profile data of the respondent at a time of response to the question, vote or provide reason; analyzing related data for the questioners and the responders; providing an answer with most votes out of all respondents, all ranked answers, all ranked reasons for each the answers; filtering the answers based on demographic settings and credibility of the respondent, wherein the filtering step comprises of creating a temporary table to estimate the data size of each of a demo filter value by a database statistic to keep data size small for high performance filtering; executing in a loop row by row for every row in the temporary table by an iterative approach to minimize work-in-progress data size and memory requirement, resulting in higher performance, and ranking the answers, wherein the ranking is by highest number of votes within the filtered set of respondents.

The invention provides a demographic method and device and a server, and the method comprises the steps: obtaining the effective cellphone travel chain data in an HIVE database; setting screening parameters of a time scale and a space scale according to a preset demographic rule; and screening the valid mobile phone travel chain data based on the screening parameters and the demographic rules to obtain a demographic quantity corresponding to the current demographic rule. According to the invention, the preset demographic rule and the screening parameters of the time scale and the space scale are utilized to count the demographic quantity; the technical problems that in the prior art, each statistical project needs to independently develop a program to design population complexity, and theaccuracy is low can be solved, and therefore the population number can be counted more flexibly, accurately and comprehensively.

Methods for determining whether different first names are nicknames of each other and are to be used for matching different patient records with the same person are provided. At least one method includes obtaining the different first names and demographic information associated with each of the different first names, determining whether at least a threshold number of instances of the patient records include pairs of the different first names each associated with a household, measuring a likelihood of affinity between the different first names in each of the pairs based on the demographic information associated with each of the different first names, comparing the likelihood of affinity with an affinity threshold, identifying the different first names in at least one of the pairs as the nicknames of each other responsive to the likelihood of affinity exceeding the affinity threshold, and updating or creating a database storing associations between the nicknames.

A data processing system for machine-learning driven data analysis and reminders implements obtaining an electronic copy of demographic information and an electronic copy of insurance and benefits information associated with a user; providing the demographic information and the insurance and benefits information to a first machine learning model; analyzing the demographic information and the insurance and benefits information with the first machine learning model to output a first benefits utilization prediction that the one or more benefits are available to the user; providing the first benefits utilization prediction as an input to a recommendation engine; generating, using the recommendation engine, a benefits usage summary recommendation report that presents the information regarding the one or more benefits available to the user based on the first benefits utilization prediction; and causing a user interface of a display of a computing device to present the benefits usage summary recommendation report.

A method for enabling a user to customize, prioritize, and view information filtered to align with the user's life state that includes interaction with an online market place. The user provides priority, positioning, and custom information about the user's life state which allows the user to view information in a life view. This information may include at least demographic information, logistical information, ethnic information, social information and psychological information. The partners may use the information about the user's life to filter its information according to the information about the user's life, which is then viewed in a life view by a user, according to the user defined positioning, prioritization, and other custom parameters. The method also enables the user to view partner and user participation in a marketplace to procure the information about the user's life, user ratings according to the user's behavior, and partner ratings according to the partner's information delivery.