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<p>we consider GPT-4 to generate dialogues according to designed causal structures. Specifically, we, for simplicity, assumed all dialogues are composed of 4 utterances rotating from 2 speakers and designed 4 causal structures to manifest different causal relationships. Along with the designed generating rules according to 4 causal structures, we adopted gpt-4-0314 and Chat Completion api to commence dialogue generation. Below is an example dialogue of the Chain IV from our dataset:
1. Have you seen a dog around here recently?
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MR is a textual dataset of movie reviews for binary sentiment classification, where each review contains only one sentence. The corpus has 5,331 positive and 5,331 negative reviews with an average length of 20.39 tokens. SST-2 is a subset of the Stanford Sentiment Treebank, where the data are labeled positive or negative, and contains 9,613 utterances with an average length of 20.32 tokens.
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BIOKG is a medical Knowledge Graph (KG) constructed using data from numerous biomedical data repositories. It encompasses various types of entities, including diseases, proteins, drugs, side effects, and protein functions. The KG consists of 51 types of directed relations that connect different pairs of entity types. These relations encompass diverse aspects such as drug-drug interactions (39 types), protein-protein interactions (8 types), as well as drug-protein, drug-side effect, and drug-protein function relations.
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This dataset comprises detailed evaluations of web accessibility features across 20 major MOOC platforms, based on the Web Content Accessibility Guidelines (WCAG) 2.1. It is intended for researchers, educators, web developers, and policymakers interested in understanding and improving the accessibility of online learning environments. Despite the ongoing advancements in this field, MOOCs platforms still present considerable accessibility challenges for users with disabilities.
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Over the past few years YouTube has became a popular site for video broadcasting and earning money by publishing various different skills in the form of videos. For some people it has become a main source to earn money. Getting the videos trending among the viewers is one of the major tasks which each and every content creator wants. Popularity of any video and its reach to the audience is completely based on YouTube's Recommendation algorithm. This document is a dataset descriptor for the dataset collected over the time span of about 45 days during the Israel-Hamas War
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The purpose of the present study is to examine the influence of big five personality traits viz., extraversion, agreeableness, neuroticism, conscientiousness, openness on impulse buying behaviour of consumers and investigate the mediating role of shopping enjoyment tendency. Employing structural equation modelling empirical data was collected from 326 consumers in India that revealed a statistically significant impact of four of five personality traits viz., extraversion, agreeableness, neuroticism, conscientiousness.
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The alignment between the implemented database application systems and their data specification standard description files significantly affects the accuracy of enterprises' estimation of data assets based on data standard files. In this study, we proposed an automated approach for discovering and aligning these consistent fields, greatly reducing the cost of manual evaluation. We frame the field's alignment problem as an entity matching computation on two distinct graphs, respectively constructed from the database of application systems and its data specification standard.
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This dataset contains the test instances used in the numerical experiment section of the paper "Scheduling Unrelated Parallel Batch Processing Machines Under Time-of-Use Electricity Prices".
Folder "time slot length = 30 mins" and "time slot length = 1 min" contains the test instances with the two different time slot lengths described in the paper.
In each folder, there are five subfolders named "TestInstance1", "TestInstance2",..., and "TestInstance5", which correspond to the five instances we generated for each parameter combination.
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This survey dataset delves into the diverse experiences and perspectives of individuals, focusing on key aspects of their educational journey and subsequent career choices. Comprising more than 60 questions or attributes,respondents were asked to share insights into their personal background, educational history, university preferences, and current professional status. The questionnaire covers a range of topics, including high school experiences, university decision-making criteria, major selection influences, and post-graduation outcomes.
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For this experiment, data were collected from December 1, 2022 to January 15, 2023 across all Starlink satellites that were in the main operational shell of approximately 53 deg. inclination and 550 km altitude. In total, data were collected from the two CMOS Image Sensors (CIS) onboard 2,914 Starlink satellites for a total of 5,828 CIS. Data were filtered to exclude satellites with CIS faults causing out-of-family measurements during the time period. An algorithm to detect bright spots was developed for the CIS and data were stored on-board each respective Starlink satellite.
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