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In information retrieval, an open-domain question answering system tries to return an answer in response to the user's question. The returned answer is in the form of short texts rather than a list of relevant documents. [13] The system finds answers by using a combination of techniques from computational linguistics, information retrieval, and ...
An end-to-end open-domain question answering. This dataset includes 14,000 conversations with 81,000 question-answer pairs. Context, Question, Rewrite, Answer, Answer_URL, Conversation_no, Turn_no, Conversation_source Further details are provided in the project's GitHub repository and respective Hugging Face dataset card. Question Answering ...
Large dataset of images for object classification. Images categorized and hand-sorted. 30,607 Images, Text Classification, object detection 2007 [29] [30] G. Griffin et al. COYO-700M Image–text-pair dataset 10 billion pairs of alt-text and image sources in HTML documents in CommonCrawl 746,972,269 Images, Text Classification, Image-Language ...
HYPO is a computer program, an expert system, that models reasoning with cases and hypotheticals in the legal domain. It is the first of its kind and the most sophisticated of the case-based legal reasoners, which was designed by Kevin Ashley for his Ph.D dissertation in 1987 at the University of Massachusetts Amherst under the supervision of Edwina Rissland.
A question and answer system (or Q&A system) is an online software system that attempts to answer questions asked by users.Q&A software is frequently integrated by large and specialist corporations and tends to be implemented as a community that allows users in similar fields to discuss questions and provide answers to common and specialist questions.
Common Crawl is a nonprofit 501(c)(3) organization that crawls the web and freely provides its archives and datasets to the public. [ 1 ] [ 2 ] Common Crawl's web archive consists of petabytes of data collected since 2008. [ 3 ]
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
The number of legal cases available via electronic means is constantly increasing (in 2003, US appellate courts handed down approximately 500 new cases per day [2]), meaning that an accurate legal information retrieval system must incorporate methods of both sorting past data and managing new data. [2] [11]