Abstract: A system and method for guiding privacy-enhancing transformations are described. The system and method include a recommendation engine configured to identify sets of transformations to mitigate a privacy risk below a user specified threshold specified in-terms of privacy-risk score for a given input dataset while keeping the utility of the dataset above the user-specified utility threshold specified in-terms of utility score. A simulation engine configured to simulate the identified set of transformations from the recommendation engine on the dataset to determine the optimal application of the plurality of transformations for maximizing the utility of the dataset, and output device to provide the optimized dataset with the privacy risk score and utility score.

Abstract: An electronic device and a controlling method thereof are provided. The electronic device includes a memory and a processor configured to obtain importance data representing an importance of each of a plurality of words included in the text data using text data related to a plurality of items written by a plurality of users, obtain a topic model representing a relationship between a topic and a word by applying a topic modelling algorithm to the obtained importance data, obtain preference data representing preference of each of the plurality of users for the topic and relationship data representing a relationship between the plurality of items and the topic, based on the obtained topic model, and train a recommendation model to output result data including an estimated preference for the plurality of items of the plurality of users, based on the preference data and the relationship data.

Abstract: Provided are an artificial intelligence (AI) system simulating a function of a human brain, such as cognition and judgment, using a machine learning algorithm, such as deep learning, and an application thereof. Also, provided is a method, performed by an electronic apparatus, of refining an artificial intelligence (AI) model, the method including: detecting information about a context of an electronic apparatus used to refine a local model stored in the electronic apparatus being changed; determining a gradient for refining the local model based on the changed information about the context; refining the local model based on the determined gradient; transmitting the gradient to a server; receiving, from the server, information about a global model refined based on the gradient; and refining the local model based on the received information.

Abstract: A system and method of harnessing knowledge and expertise to improve machine learning is disclosed. The system and method include capturing the data to input, preparing the captured data, enhancing the prepared data, modeling and learning the process associated with the enhanced data, reviewing the result of the learning and modeling to produce an output, visualizing the reviewed output, and input and recommendations from recommendations engine that make recommendations of techniques and configurations to use.

Abstract: An electronic device is provided. The device includes a processor configured to receive, from a first external device, a list of a first number of items generated based on a request of a user, and a first score of each of the first number of items, identify a first relevancy between each element of a first feature set and each of the first number of items and a second relevancy between each element of the set and the user, identify a first list of a second number of items, identify, for at least one item of the first list, a third relevancy between a first feature of the set which satisfies a condition and the at least one item and a fourth relevancy between the first feature and the user, based on the first relevancy and the second relevancy, and output the third relevancy and the fourth relevancy with the first list.

Abstract: An electronic device is provided. The device includes a processor configured to receive, from a first external device, a list of a first number of items generated based on a request of a user, and a first score of each of the first number of items, identify a first relevancy between each element of a first feature set and each of the first number of items and a second relevancy between each element of the set and the user, identify a first list of a second number of items, identify, for at least one item of the first list, a third relevancy between a first feature of the set which satisfies a condition and the at least one item and a fourth relevancy between the first feature and the user, based on the first relevancy and the second relevancy, and output the third relevancy and the fourth relevancy with the first list.

Abstract: Provided are an artificial intelligence (AI) system simulating a function of a human brain, such as cognition and judgment, using a machine learning algorithm, such as deep learning, and an application thereof. Also, provided is a method, performed by an electronic apparatus, of refining an artificial intelligence (AI) model, the method including: detecting information about a context of an electronic apparatus used to refine a local model stored in the electronic apparatus being changed; determining a gradient for refining the local model based on the changed information about the context; refining the local model based on the determined gradient; transmitting the gradient to a server; receiving, from the server, information about a global model refined based on the gradient; and refining the local model based on the received information.

Abstract: Provided are an artificial intelligence (AI) system simulating a function of a human brain, such as cognition and judgment, using a machine learning algorithm, such as deep learning, and an application thereof. Also, provided is a method, performed by an electronic apparatus, of refining an artificial intelligence (AI) model, the method including: detecting information about a context of an electronic apparatus used to refine a local model stored in the electronic apparatus being changed; determining a gradient for refining the local model based on the changed information about the context; refining the local model based on the determined gradient; transmitting the gradient to a server; receiving, from the server, information about a global model refined based on the gradient; and refining the local model based on the received information.

Abstract: A system has a primary server storing search data sets (“staks”) and a linked social network server.

Abstract: A system, method, and computer program product are provided for determining information associated with an extracted portion of content. In use, a user is identified. Additionally, content generated by the user is identified. Additionally, a portion of the content is extracted. Further, information associated with the extracted portion of the content is determined. Further still, the determined information is added to a profile of the user. Also, an action is initiated, based on the profile of the user.

Abstract: A system for search and discovery of information in a real time network, comprising: means for gathering data indicative of a message posted in an real time network, the data comprising information identifying a uniform resource locator, URL and textual information associated with the URL; means for indexing the gathered data; means for querying the indexed data; and means for ranking the queried data.

Abstract: A user inputs a request (1) for a commodity recommendation. A computer system accesses (2) a plurality of commodity reviews. The computer system extracts feature indicators (3) and sentiment indicators (4) from each commodity review. The computer system determines (5) the popularity of each feature indicator and the similarity between a first commodity (Q) and a second commodity (C). The computer system evaluates the sentiment indicators and evaluates the similarity indicator to form (7) the commodity recommendation. After the commodity recommendation has been formed in step (7), the computer system delivers (8) the commodity recommendation for the second commodity (C) to the user using a website interface.

Abstract: A searching system may include a primary server with interfaces for communication with databases or with underlying search engines. The primary server may be adapted to receive a search query from a client under instructions from a user; and retrieve search results and transmit the results as a response to the client. The primary server may be adapted to store search data sets of relevant results for queries by users who are member of the set. The primary server may be adapted to select a search data set of which the user for the query is a member, and to use said search data set in providing the response to the query. The primary server may be adapted to download data concerning the selected search data set to the user. The primary server may be adapted to automatically update the search data set according to the results selected by the user.

Abstract: 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.

Abstract: A system has a primary server storing search data sets (“staks”) and a linked social network server.

Abstract: A method for generating product recommendations comprises analyzing a database of messages, comprising a set of messages posted by users of a micro-blogging service to generate a user index and a product index. The user index comprises for each of a plurality of users of the system, a ranked set of terms included by the user in their posted messages. The product index comprises for each product which is to be potentially recommended, a ranked set of terms derived from messages posted by users and referencing the product. Responsive to a query identifying a user, the user index for the user is compared to the product indices to return a limited set of product identifiers corresponding to product indices most similar to the user index. The set of product identifiers are provided as recommendations to a service provider.

Abstract: A searching system may include a primary server with interfaces for communication with databases or with underlying search engines. The primary server may be adapted to receive a search query from a client under instructions from a user; and retrieve search results and transmit the results as a response to the client. The primary server may be adapted to store search data sets of relevant results for queries by users who are member of the set. The primary server may be adapted to select a search data set of which the user for the query is a member, and to use said search data set in providing the response to the query. The primary server may be adapted to download data concerning the selected search data set to the user. The primary server may be adapted to automatically update the search data set according to the results selected by the user.

Abstract: A computer program product comprising a non-transitory computer readable medium for storing or recording instructions in machine readable form. The instructions, when executed in a motion sensor enabled smart phone, record target data associated with a response of the motion sensor to a desired sequence of movements of a user performing a therapeutic exercise while wearing the smart phone, map the target data to run-time target parameters of a software application, receive performance data associated with a response of the motion sensor to a subsequent sequence of movements of the user performing the therapeutic exercise while wearing the smart phone, map the performance data to the target parameters of the software application to determine the operation of the software application and provide information for display on a remote monitor visible to the user indicating the quality of the user's performance of the exercise.

Abstract: 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.

Abstract: In an information retrieval method a meta search engine receives a user information query in the form of key words; and submits the query to a search engine, and also submits the query to a snippet database storing previously selected results, indexed by a snippet index of terms included in snippets of the results when they were previously selected. The meta search engine then receives results from the search engine; and receives a response from the snippet database. It merges the results from the search engine with those from the snippet database; and submits re-ranked results to the user. The snippet database processes in parallel with the underlying search engine. The meta search engine also monitors which results of the returned re-ranked results are selected by the user, and updates the snippet index accordingly.