Corpus de violencia en México

$500.00

Corpus de violencia en México de blogs, noticias web y llamados para acción. Vectores proximamente.

Categories: ,

Description

Corpus de violencia en México de blogs, noticias web y llamados para acción. Estos datos están normalizados (sin caracteres especiales o html) en formato utf-8. Existe un consensos entre 4 analistas mexicanos sobre si estos datos pertenecen en dichas categorías con las fuentes siendo libre dominio, accesible por el internet y con sus respectivos autores nombrados. El contenido incluye mas de 9600 oraciones dentro de los posts.  Asumiendo que los titulares equivalen a por lo menos una oración por titular. Entonces, este corpus tiene mas de 10,000 oraciones total.

Quien compre el derecho de uso de este corpus también recibirá actualizaciones por 2 años ya que el grupo de Sugar Bear AI continua expandiendo el corpus de violencia. El corpus de violencia en México contiene mas de 350 documentos completos de varias fuentes. Los datos incluyen lo siguiente: post_title, post_content, categoria y meta. Meta contiene datos como fecha, autor o fuente.

 

License Summary _______________ Licensor: Technical Specifications: Data: Distribute: no Label: yes Re-represent: yes Models: Benchmark: yes Research: yes Publish: yes Internal use: yes Output commercialization: yes Credit / Attribution Notice: Designated Third Parties: Additional Conditions: _______________ The following licensing language is made available under CC-BY4. Attribution should be made to “Montreal Data License (MDL)”, or “License language based on Montreal Data License”. The authors are not legal advisors to the individuals and entities making use of these licensing terms.The licensing terms can be combined as needed to match the rights conferred by the licensor. The language below assumes that all rights are granted, however each right should be conferred or not based on the user’s intent. Data License for use in AI and ML This license covers the Data made available by Licensor to you (“Licensee”) under the following terms.Licensee’s use of the data consists acceptance of the terms of this license agreement(“License”). 1. Definitions a.”Data” means the informational content(individually or as a whole) made available by Licensor. b.”Model” means machine – learning or artificial – intelligence based algorithms, or assemblies thereof that, in combination with different techniques, may be used to obtain certain results.Without limitation, such results can be insights on past data patterns, predictions on future trends or more abstract results. c.”Output” means the results of operating a Trained Model as embodied in informational content resulting therefrom. d.”Representation” means a Model that mimics the effects of the Data, but does not contain any individual data points or allow third parties to infer individual data points with currently existing technology. e.”Labelled Data” means the associated metadata and informational content derived from Data which identify, comment or otherwise derive information from Data, such as tags and labels. f.”Third Parties” means individuals or entities that are not under common control with Licensee. g.”Train” means to expose an Untrained Model to the Data in order to adjust the weights, hyperparameters and / or structure thereof. h.”Trained Model” means a Model that is exposed to Data such that its weights, parameters and architecture embody insights from the Data. i.”Untrained Model” means Model that is conceived and reduced to practice as to its structure, components and architecture but that has not been trained on Data such that its weights, parameters and architecture do not embody insights from the Data. 2. General Clauses a.Unless otherwise agreed in writing by the parties, the data is licensed “as is” and “as available”. Licensor excludes all representations, warranties, obligations, and liabilities, whether express or implied, to the maximum extent permitted by law. b.Nothing in this License permits Licensee to make use of Licensor’s trademarks, trade names, logos or to otherwise suggest endorsement or misrepresent the relationship between the parties. c.The rights granted under this license are deemed to be non – exclusive, worldwide, perpetual and irrevocable, unless otherwise specified in writing by Licensor. d.Without limiting Licensee’s rights available under applicable law, all rights not expressly granted hereunder are hereby reserved by Licensor.The Data and the database under which it is made available remain the property of Licensor(and / or its affiliates or licensors). e.This license shall be terminated upon any breach by Licensee of the terms of this License. 3. Licensed Rights to the Data. a.Licensor hereby grants the following rights to Licensee with respect to making use of the Data itself. 1. Access the Data, where “access” means to access, view and / or download the Data to view it and evaluate it(evaluation algorithms may be exposed to it, but no Untrained Models). Creation of Tagged Data. Creation of a Representation of the Data. b.The rights granted in (a) above exclude the following rights with respect to making use of the Data itself: Distribute the Data, i.e. to make all or part of the Data available to Third Parties. 4. Licensed Rights in Conjunction with Models. a.Licensor hereby grants the following rights to Licensee with respect to making use of the Data in conjunction with Models. To access the Data, use the Data as training data to evaluate the efficiency of different Untrained Models, algorithms and structures, but excludes reuse of the Trained Model, except to show the results of the Training. This includes the right to use the dataset to measure performance of a Trained or Untrained Model, without however having the right to carry-over weights, code or architecture or implement any modifications resulting from the Evaluation. To access the Data, use the Data to create or improve Models, but without the right to use the Output or resulting Trained Model for any purpose other than evaluating the Model Research under the same terms. To make available to Third Parties the Models resulting from Research, provided however that third parties accessing such Trained Models have the right to use them for Research or Publication only. To access the Data, use the Data to create or improve Models and resulting Output, but without the right to Output Commercialization or Model Commercialization. The Output can be used internally for any purpose, but not made available to Third Parties or for their benefit. To access the Data, use the Data to create or improve Models and resulting Output, with the right to make the Output available to Third Parties or to use it for their benefit, without the right to Model Commercialization. b.The rights granted in (a) above exclude the following rights with respect to making use of the Data in conjunction with Models: None 5. Attribution and Notice The origin of the Data and notices included with the Data shall be made available to Third Parties to whom the Data, Output and / Model have been made available.Licensee shall make commercially reasonable efforts to link to the source of the Data.If so indicated by the Licensor in writing alongside the Data that the use shall be deemed confidential, then Licensee shall not publicly refer to Licensor and / or the source of the Data.

Reviews

There are no reviews yet.

Be the first to review “Corpus de violencia en México”

Your email address will not be published. Required fields are marked *