Thomson Reuters Corporation is a major multinational mass media and information firm founded in Toronto and based in New York City and Toronto. It was created by the Thomson Corporation's purchase of British-based Reuters Group on 17 April 2008, and today is majority owned by The Woodbridge Company, a holding company for the Thomson family. The company operates in more than 100 countries, and has more than 60,000 employees around the world. Thomson Reuters was ranked as Canada's "leading corporate brand" in the 2010 Interbrand Best Canadian Brands ranking. Thomson Reuters' operational headquarters are located at 3 Times Square, Manhattan, New York City; its legal domicile is located at 333 Bay Street, Suite 400, Toronto, Ontario M5H 2R2, Canada. Wikipedia.
Thomson Reuters | Date: 2016-11-18
A computer implemented method of processing data containing information about relationships between contacts and a community of contact owners is provided, which includes the steps of: collecting data having contact information, contact owner information and one or more values related to the strength of a relationship between the contact and the contact owner; evaluating the strength of the relationship based on the one or more values; and storing the collected data and evaluated strength in a computer database.
Thomson Reuters | Date: 2016-07-15
A method includes receiving a corpus comprising a set of pre-segmented texts. The method further includes creating a plurality of modified pre-segmented texts for the set of pre-segmented texts by extracting a set of semantic terms for each pre-segmented text within the set of pre-segmented texts and applying at least one domain tag for each pre-segmented text within the set of pre-segmented texts. The method further includes clustering the plurality of modified pre-segmented texts into one or more conceptual units, wherein each of the one or more conceptual units is associated with one or more templates, wherein each of the one or more templates corresponds to one of the plurality of modified pre-segmented texts.
Thomson Reuters | Date: 2016-07-11
A Global Supply Chain Intelligence system (GSCF) configured as a supply chain intelligence search engine adapted to predict, discover and verify commodity trade flows. Creating and maintaining a dataset that tracks real and near real-time commodity flows as they happen as an input to the GSCI. The dataset used in a business intelligence process within the GSCI to arrive at an output, such as a predicted price behavior, a price alert, a risk alert, etc. A Commodity Flow Intelligence (CFI) component that collects and analyzes information with the timeliness, detail and accuracy required to track, forecast and predict supply and demand imbalances at the discrete flow level to aid market participants in making operational trading and investment decisions, for example, in connection with a financial services system or offering providing enhanced data and tools to promote market transparency.
Thomson Reuters | Date: 2016-06-03
The present invention provides an improved docket search and analytics engine for determining the outcome of a case for a particular entity or party, for predicting the outcome of a case for a particular entity or party, or for predicting the time to resolution of a case for a particular entity or party. More specifically, the present invention provides a system and engine for accessing and retrieving docket and other data from a plurality of databases and applying by one or more engines a set of models to the retrieved data to make a determination or prediction as to the outcome of a case for an entity or party involved in the case.
Thomson Reuters | Date: 2017-05-24
A computer-implemented system and method facilitate dynamically allocating server resources. The system and method include determining a current queue distribution, referencing historical information associated with execution of at least one task, and predicting, based on the current queue distribution and the historical information, a total number of tasks of various task types that are to be executed during the time period in the future. Based on this prediction, a resource manager determines a number of servers that should be instantiated for use during the time period in the future.
Thomson Reuters | Date: 2016-10-03
An embodiment of a method of providing identity services includes: receiving identity data for an individual for which the identity provider has provided an identity; generating a transaction to store an identifier representing the identity data in a data structure on a blockchain of a distributed system; sending the transaction to at least one node of the distributed system; and generating an identity token incorporating the identifier representing the identity data. An embodiment of a method of verifying an identity includes: receiving data extracted from the identity token, wherein the extracted data includes an identifier representing the identity data; determining whether a data structure containing the extracted identifier representing the identity data is stored on a blockchain of a distributed system; and outputting an indication of a validity of an identity associated with the identity data based on the determination.
Thomson Reuters | Date: 2017-03-07
Estimations of carbon dioxide (CO2) emission of an entity upon the condition of incomplete or missing data uses one or more algorithms implemented in a machine having a processor and a memory and data concerning the entity. The data is applied to an algorithm implemented as code executable in the processor. The algorithm produces a result that comprises an estimate of the CO2 emission of the entity. The CO2 emission estimate can be output to a user, and the underlying formula and data can inspected and optionally modified by users with suitable permissions. The CO2 emission estimate can be applied as a factor in a formula to compute a rating for the entity which can be output from the machine. Error estimates associated with the data used by the algorithm can be generated to provide improved estimates.
Thomson Reuters | Date: 2017-03-01
The present disclosure is directed towards systems and methods for providing one or more security measures in Bluetooth low energy protocol environment, which comprises broadcasting a beacon signal, wherein the beacon signal comprises one or more temporal attributes and a proximity range. A request from an access device is received to authenticate the access device with the beacon signal and is subsequently authenticated with the beacon signal when the access device is within the proximity range. One or more content items are the transmitted to the access device in accordance with the one or more temporal attributes while the access device is authenticated with the beacon signal.
Thomson Reuters | Date: 2017-07-05
The invention relates to a system and method for providing a latency floor for an electronic trading venue in which market participants who can respond within the value the floor and choose to compete in a specific race to make or take a price may each have a substantially equal chance of winning that race. The system may detect and distinguish individual races that occur on an electronic trading venue. Upon detection of the first order (or message) in such a race, the system may create a batch and a timer for that race. As orders pertaining to that race are received, they are added to its batch. Upon the timer reaching a predetermined value, typically the value of the floor, the race is determined to have ended and the orders are drained from the batch for processing (e.g., against the instruments central limit order book (CLOB)).
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-18-2016 | Award Amount: 3.99M | Year: 2017
The SPECIAL project will address the contradiction between Big Data innovation and privacy-aware data protection by proposing a technical solution that makes both of these goals realistic. We will develop technology that: (i) supports the acquisition of user consent at collection time and the recording of both data and metadata (consent, policies, event data, context) according to legislative and user-specified policies; (ii) caters for privacy-aware, secure workflows that include usage/access control, transparency and compliance verification; (iii) demonstrates robustness in terms of performance, scalability and security all of which are necessary to support privacy preserving innovation in Big Data environments; and (iv) provides a dashboard with feedback and control features that make privacy in Big Data comprehensible and manageable for data subjects, controllers, and processors. SPECIAL shall allow citizens and organisations to share more data, while guaranteeing data protection compliance, thus enabling both trust and the creation of valuable new insights from shared data. Our vision will be realised and validated via real world use cases that - in order to be viable - need to overcome current challenges concerning the processing and sharing of data in a privacy preserving manner. In order to realise this vision, we will combine and significantly extend big data architectures to handle Linked Data, harness them with sticky policies as well as scalable queryable encryption, and develop advanced user interaction and control features: SPECIAL will build on top of the Big Data Europe and PrimeLife Projects, exploit their results, and further advance the state of the art of privacy enhancing technologies.