Information Extraction Sample Clauses

Information Extraction. You shall not, without explicit prior written authorization from Frappe specifically permitting such an action, perform reverse look-up, trace or seek to trace any information on any other User or Customer of Service, including any account on the Service not owned by You, to its source, or exploit the Website, or any service or information made available or offered by or through the Website, in any way where the purpose is to reveal any information, including but not limited to personal identification or information, other than Your own information, as provided for by the Website.
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Information Extraction. The information extraction was shared between two individuals. The themes of interest are: the study goal (noted for context); model type; model input data; model validation data. Records included mathematical models for the spread of ILIs (influenza like illnesses); mathematical models for the spread of human infectious diseases across the globe; mathematical models for the spread of human infectious diseases across localised regions, but which could be reparameterised to become global models; human infectious disease spread papers which refer to population movement data. Records were classified as one of four broad categories: metapopulation model; individual-based model; data analysis; or probabilistic model. Model input data could be broken down thematically into: epidemiological data; population data; and travel data. Epidemiological data concerns model parameters which describe the disease, such as the average length of infection. Population data relates to difference within the total modelled population, for example splitting the population into different age brackets or determining how many individuals live in a particular region. Travel data consists of information on travel patterns of individuals, either commuting or long-distance travel. Validation data should be from a source independent to all input data sources so that model outputs can be compared against it.
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Information Extraction. Named Entity Recognition 13 4.2 Mathematical Formula Recognition 14 4.2.1 Segmentation 16 4.3 Formula Parsing 17 4.3.1 Projection Profile Cutting 17 4.3.2 Virtual Link Networks 18 4.3.3 Graph Rewriting 20 4.3.4 Baseline Parsing with Grammars 20
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Related to Information Extraction

  • Project Information describing each Eligible Project that started, ended, or was ongoing in the reporting year.

  • Information/Cooperation Executive shall, upon reasonable notice, furnish such information and assistance to the Bank as may be reasonably required by the Bank, in connection with any litigation in which it or any of its subsidiaries or affiliates is, or may become, a party; provided, however, that Executive shall not be required to provide information or assistance with respect to any litigation between Executive and the Bank or any other subsidiaries or affiliates.

  • Information Sources The Custodian may rely upon information received from issuers of Investments or agents of such issuers, information received from Subcustodians and from other commercially reasonable sources such as commercial data bases and the like, but shall not be responsible for specific inaccuracies in such information, provided that the Custodian has relied upon such information in good faith, or for the failure of any commercially reasonable information provider.

  • Root-­‐zone Information Publication ICANN’s publication of root-­‐zone contact information for the TLD will include Registry Operator and its administrative and technical contacts. Any request to modify the contact information for the Registry Operator must be made in the format specified from time to time by ICANN at ▇▇▇▇://▇▇▇.▇▇▇▇.▇▇▇/domains/root/.

  • Payroll Information Payroll checks shall include all required information, a clear designation as to the amount and category, e.g., regular, overtime or holiday pay, of compensation for which payment is being made.