2442 results about "Recommender system" patented technology

The present invention relates to a system and method for recommending tags and / or content items in response to requests received from remote computing devices. In one aspect, a content item recommendation system comprises a database configured to store an identifier of a first content item, a first tag and information from which a tag density associated with the first tag and with the first content item may be derived. The tag density may be a measure of times a tag has been associated with a content item by any user of a plurality of users who are members of a community. The system also comprises a recommendation engine configured to receive search results containing the first tag from a search engine and to correlate the first tag with information stored in the database. The recommendation engine may be further configured to determine a recommended tag, based on a recommendation threshold and a tag density, the tag density associated with both the recommended tag and the first content item.

Systems and methods of utilizing communications networks and multivariate analysis to predict or recommend optimal products from a predefined population of commercially available products are disclosed. The recommendations are based on intelligence contained in processing elements and subjective and / or objective product information received from consumers or input to the systems as part of their initial setup. The output of the systems comprise sets of products that they predict the consumer will prefer and / or perform well for the problem or concern identified by the consumer. The performance and preference predictions are a function of consumer problems and product responsiveness patterns. Objective product information is generally obtained with diagnostic instruments. Data measured with the diagnostic instruments may be communicated to the data processing portions of the invention via the Internet. The outputs of the data processing portion of the system may be presented to consumers via the Internet as well.

A method of buying or selling items having at least one market and its associated processes are disclosed. The method includes the steps of, under control of a client system, displaying information identifying at least one item and a bid and / or ask price for the item in the market; and specifying transaction conditions based on a user directed position of a moveable icon, where the transaction conditions are related to the buying or selling of the identified item in the active market. Then, in response to an action of the user sending a user transaction request at the transaction conditions displayed at the time of said action, facilitating financial transactions for the user in accordance with the transaction conditions to complete the transaction. In this manner, the item may be bought or sold by the user at the transaction conditions specified. A user interface to facilitate this method is also disclosed. A quantity recommendation system to facilitate the quantity decision of a financial transaction is further disclosed.

A music recommendation system receives a user selection of desired music, retrieves analysis data associated with the selected music, and generates a playlist of songs based on the analysis data. The analysis data is generated based on a processing of one or more audio signals associated with the selected music. The analysis data may downloaded from a central server. If the analysis data is not available from the central server, it is generated locally at a user end, and uploaded to the central server. A plurality of user-selectable shuffling mechanisms are provided to allow the order of the songs to be shuffled according to the selected shuffling mechanism. The end user device may also receive recommendation of new music from different providers based on the analysis data of music for which the recommendation is to be based.

A search and recommendation system employs the preferences and profiles of individual users and groups within a community of users, as well as information derived from categorically organized content pointers, to augment electronic commerce related searches, re-rank search results, and provide recommendations for commerce related objects based on an initial subject-matter query and an interaction history of a user. The search and recommendation system operates in the context of a content pointer manager, which stores individual users' content pointers (some of which may be published or shared for group use) on a centralized content pointer database connected to a network. The shared content pointer manager is implemented as a distributed program, portions of which operate on users' terminals and other portions of which operate on the centralized content pointer database. A user's content pointers are organized in accordance with a local topical categorical hierarchy. The hierarchical organization is used to define a relevance context within which returned objects are evaluated and ordered.

A system and method in a network of devices, which ascertains the user's context to suggest the most preferred task for the user to perform. User's context includes his / her location, the content he / she is interested in, the devices which are being used by him / her, and the devices and content allowed to be used by the user. Using this context, the system suggests tasks to the user that are appropriate to that context. The determination of context and the suggestion of tasks are performed by keeping track of the content and the devices available to the user at any given time. The suggestion of tasks is performed in accordance with certain policies. For example, the user can control the behavior of the system by changing the rules in the policy. Tasks are in the form of simple sentences that can be easily understood by the user. If, based on certain context, more than one task is possible, the system suggests the task with the highest priority to the user.

The invention is a system and method for computing a result for a location, wherein the result indicates how novel it is for a wireless device to occupy a specific location. After determining the location of a wireless device through various means, a Novelty Index Value (NIV) is calculated for the location, and the NIV is then stored into a database. The NIV may then be subsequently used by application programs to compute a desired result from the NIV. Multiple users may utilize and / or share the same NIV values. The NIV may also be used to alter the configuration of a wireless device as well. A recommendation system is also disclosed, wherein user context is utilized along with NIV values to compute particular results for a user.

A recommendation system is used to provide suggestions in environments such as message boards, RSS aggregators, blogs and the like by comparing member interests and creating recommendation items corresponding to categorized topics or other members. In some instances a natural language can assist in processing content to sort it into the appropriate topic bin. An advertising module cooperates with the system to provide content based ads relevant to the recommended items.

A method, system, and computer program product for performing searching that generates improved queries, retrieves meaningful and relevant information, and presents the retrieved information to the user in a useful and comprehensive manner is described. The method of searching comprises the steps of: receiving from a user a search query requesting information, retrieving at least one recommendation relating to the search query, generating an expanded query based on the received query, performing a search using the expanded query to retrieve documents, and generating themes relating to the retrieved documents. The at least one recommendation relating to the search query is retrieved from a recommendation database. The recommendation database is generated by performing the steps of: performing data mining using users search query logs, user search patterns, and user profile information to generate a plurality of recommendations relating to search query strings, generating a data structure including the recommendations relating to search query strings, and generating a text index based on information in the data structure.

Systems and methods are provided for an automatic user or friend recommendation system that matches players that have compatible play styles, play schedules, or the like. Behavioral data is collected or entered from players, and a profile of each player is created and compared to calculate a compatibility score. If the compatibility score exceeds a predetermined threshold, then the players are marked as compatible, or a degree of compatibility may be calculated and displayed as well. Users can edit their profile, e.g., on a web application or in-game. Users may also interact with optional and incremental demographic survey questions as they log in. A notification of compatible players may be provided via the web application or via an in-game indication. For example, a glow may appear around a compatible player, or compatible players may be displayed in a list, such as an instant messaging client.

A diagnosis and repair recommendation system for a railroad locomotive is disclosed. The system uses generalized repair recommendations and instantiates them to a specific repair process for a unique road number locomotive. In addition to repair steps to be executed by the technician, the method and system remotely provides supporting documentation specifically tailored for each step in the repair process. As the repair is being conducted, feedback information is entered by the technician. The repair recommendations and the supporting documents are available to the technician via a remote unit, thereby allowing the technician to access the repair steps and supporting documentation while the repair is in progress.

Systems and methods of utilizing communications networks and multivariate analysis to predict or recommend optimal products from a predefined population of commercially available products are disclosed. The recommendations are based on intelligence contained in processing elements and subjective and / or objective product information received from consumers or input to the systems as part of their initial setup. The output of the systems comprise sets of products that they predict the consumer will prefer and / or perform well for the problem or concern identified by the consumer. The performance and preference predictions are a function of consumer problems and product responsiveness patterns. Objective product information is generally obtained with diagnostic instruments. Data measured with the diagnostic instruments may be communicated to the data processing portions of the invention via the Internet. The outputs of the data processing portion of the system may be presented to consumers via the Internet as well.

An Internet-based customer referral system enables individuals and other business entities (“associates”) to refer customers to a merchant's web site in return for compensation, such as commissions on resulting sales. Entities initially register with the merchant web site as associates, and are provided with instructions for creating links to the merchant web site. An associate may, for example, set up an associate web site (or other information dissemination system) with reviews, recommendations, and / or editorials of specific products in the merchant's online catalog, together with links to associated pages in the catalog. When a user follows such a link and then makes a purchase (as tracked by the merchant web site), the system preferably awards a commission to the associate. The system also preferably generates feedback reports that provide each associate with data regarding the effectiveness of each link provided by that associate.

A system and method of providing media recommendations and media segments based on expert choice lists is disclosed. Expert choice lists consisting of media segment references are retrieved through a data network and stored cumulatively in a database as records with text descriptor fields. Users of the suggestion system make requests in the form of text search descriptors and a desired output descriptor type. Descriptors of the output type in the expert choice list database are scored by the frequency with which they appear in expert choice lists possessing matches to the search descriptors. A list of the top-scoring descriptors is returned. In an alternate preferred embodiment, media segment references are scored by the frequency of their appearance in lists with matches to the search descriptors. The highest-scoring segment references are used to generate a playlist so that the recommended media segments can be presented to the user automatically.

A diagnosis and repair recommendation system for a railroad locomotive is disclosed. The system uses generalized repair recommendations and instantiates them to a specific repair process for a unique road number locomotive. In addition to repair steps to be executed by the technician, the method and system remotely provides supporting documentation specifically tailored for each step in the repair process. As the repair is being conducted, feedback information is entered by the technician. The repair recommendations and the supporting documents are available to the technician via a remote unit, thereby allowing the technician to access the repair steps and supporting documentation while the repair is in progress.

A recommendation system uses feedback from users on specific item recommendations to assess the quality of the recommendation rules used to generate such recommendations. The feedback may be explicit (e.g., a user rates a particular recommended item), implicit (e.g., a user purchases a recommended item), or both. The system may use these assessments to modify the degree to which particular recommendation rules are used to generate recommendations. For instance, if a particular recommendation rule leads to negative feedback relatively frequently, the system reduce or terminate its reliance on the rule. In some embodiments, the system may also increase its reliance on recommendation rules that tend to produce positive feedback.

Specific advertisements and other information can be communicated to the user of a mobile vehicle depending on the vehicles or occupants needs or preferences.

A system and method for recommending a social interaction space to an individual are disclosed. Real-time information about users and a social interaction environment are gathered. A real-time, general model of the social interaction environment, including social interaction space states, trajectories, and rhythms, is created, as well as real-time profiles of the users. Affinities are calculated between modeled environment and user profiles, and social interaction spaces of the modeled environment are recommended to the user based upon the calculated affinities.

A real time information feed system comprises an interface to receive a real time information feed and a data mining engine for retrieving data concerning a subscriber. A recommendation engine automatically modifies the real time information feed according to the mined data; and a subscriber interface outputs the modified real time information for delivery to the subscriber. The data mining engine is adapted to mine data in a real time communication medium used by the subscriber, such as a micro-blogging service. The data mining engine comprises an indexer for mining and indexing the real time information feed and the subscriber data to provide a plurality of indexes; and to generate vectors representing the separate indexes and to compare the vectors to modify. The data mining engine and the recommendation engine combine recommendation and information retrieval settings from a plurality of online and offline sources to produce a single amalgamated list of results to harness a user's usage patterns and social graph activity on a social network or updating service, that further allows the generation of user profiles as part of a media recommendation system.

An artificial intelligence song / music recommendation system and method is provided that allows music shoppers to discover new music. The system and method accomplish these tasks by analyzing a database of music in order to identify key similarities between different pieces of music, and then recommends pieces of music to a user depending upon their music preferences. An embodiment enables a user to evaluate a new song's similarity to songs already established as commercially valuable.

The invention discloses a personalized commodity recommending method which integrates attributes and structural similarity. In the method, users and commodities are used as nodes with characteristic information to be mapped to a network by integrating the attribute information and structural similarity information, and an information network chart is established according to the purchasing relation between customers and the commodities; and interests and preference among user node pairs are measured by the integrated attributes and structural similarity in the information network chart, and the nearest neighbor is selected by the interests and the preference to improve the accuracy of recommending. On the basis of the recommending method, the invention also discloses a personalized commodity recommending method which integrates the measurement of the attributes and the structural similarity. In the system, the interests and the preference of the users are measured accurately by a computing method of integrating the similarity of the attributes and the similarity of node structure backgrounds in the information network chart, and the generation efficiency of the nearest neighbor is improved by utilizing clustering technology. The method and the system can be applied to electronic commerce, and provide personalized commodity recommending for the users.

An Internet-based customer referral system enables individuals and other business entities (“associates”) to market products sold on a merchant web site in return for commissions. Following registration, the associate sets up a web site (or other information dissemination system) to distribute hypertextual catalog documents that include marketing information (product reviews, recommendations, etc.) about selected products of the merchant. In association with each such product, the catalog document includes a hypertextual “referral link” that allows a user / customer to access the merchant web site and purchase the product. When a customer selects a referral link, the customer's computer transmits unique IDs of the selected product and of the associate to the merchant's site, allowing the merchant to identify the product and the referring associate. If the customer subsequently purchases a product from the merchant's site, a commission is automatically credited to an account of the referring associate.

A computer-implemented service recommends works to a user based on works currently or previously played or downloaded by the user on a player device or based on playlists stored on the player device. The works may be, for example, music files, video files, electronic books, or other digital content for playing by users. A user may thus obtain personalized recommendations that are based on works obtained from sources (web sites, physical CDs, etc.) that are independent of the recommendations system. In one embodiment, the service identifies pairs of works that are related to each other by virtue of the relatively high frequency with which they co-occur on playlists or within play histories of users. The resulting mappings of works to related works are in-turn used to select works to recommend to users.

A recommendations system uses probabilistic methods to select, from a candidate set of items, a set of items to recommend to a target user. Some embodiments of the methods effectively introduce noise into the recommendations process, causing the recommendations presented to the target user to vary in a controlled manner from one visit to the next. The methods may increase the likelihood that at least some of the items recommended over a sequence of visits will be useful to the target user. Some embodiments of the methods are stateless such that the system need not keep track of which items have been recommended to which users.

A system and method of providing personalized item recommendations in a communication system comprising a server and a plurality of client devices. At the server, a plurality of user rating vectors are received from a plurality of client devices and aggregated into a rating matrix that is factorized into a user feature matrix and an item feature matrix, with the product of the user feature and item feature matrixes approximating the user rating matrix. The factorization comprises the steps of the ALS1 or the IALS1 algorithm including: initializing the user feature matrix and the item feature matrix with predefined initial values; alternately optimizing the user feature matrix and the item feature matrix until a termination condition is met. The item feature matrix is transmitted from the server to at least one client device, and a predictive rating vector is generated as the product of the associated user feature vector and the item feature matrix. At least one item is selected for recommendation to a user from the items associated with the predictive rating vector.

A user-personalized product sampling, recommendation and purchasing system uses customer identification numbers and associated customer profile data to tailor specific product recommendations to a customer at a content sampling station of a retail location. The customer also can use her customer profile to receive the same information from an Internet website of the merchant. In-store sampling stations also may have the capability of checking store inventory and central warehouse inventory and providing recommendations to the customer in accordance with product availability, and optionally may provide the customer with the ability to place product orders directly through the sampling station. The recommendation system also can be used to tailor product recommendations in accordance with a rule-based model and real-time inventory data from a POS database.

A video recommendation system is provided. The video recommendation system has: an interaction device configured to receive feedback information of a video from a user, wherein the videos are composed of a plurality of video segments; a feature calculating module configured to calculate object features of at least a first video segment corresponding to the feedback information in the plurality of video segments; and an analysis module configured to recommend at least one first recommended video segment to the user from the plurality of video segments according to the calculated object features and the feedback information.

We present a data-driven system that seamlessly integrates the compilation of a diverse set of patient electronic medical records, family history, and environmental risk factor databases, a program that determines correlations and assigns weights through a neural network between illness and the state of symptoms, a program to create disease-specific questionnaires and content, a program alert that informs users of trends and potential illness outbreaks due to anomalous changes in regional or national symptom trends, and a program that enables medical practitioners to view patient-generated records and manage an online referral system. The automated diagnoses and alerts allow users to make informed and rapid medical treatment decisions.

An adaptive recommendation system and a mobile adaptive recommendation system are disclosed. The adaptive recommendation system and the mobile adaptive recommendation system include algorithms for monitoring user usage behaviors across a plurality of usage behavior categories associated with a computer-based system, and generating recommendations based on inferences on user preferences and interests. Privacy control functions and compensatory functions related to insincere usage behaviors can be applied. Adaptive recommendation delivery can take the form of visual-based or audio-based formats.