Crowdsourcing Argumentation Structures in Chinese Hotel Reviews

Argumentation mining aims at automatically extracting the premises-claim discourse structures in natural language texts. There is a great demand for argumentation corpora for customer reviews. However, due to the controversial nature of the argumentation annotation task, there exist very few large-scale argumentation corpora for customer reviews. In this work, we novelly use the crowdsourcing technique to collect argumentation annotations in Chinese hotel reviews. As the first Chinese argumentation dataset, our corpus includes 4814 argument component annotations and 411 argument relation annotations, and its annotations qualities are comparable to some widely used argumentation corpora in other languages.Comment: 6 pages,3 figures,This article has been submitted to "The 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC2017)

Using Argument-based Features to Predict and Analyse Review Helpfulness

We study the helpful product reviews identification problem in this paper. We observe that the evidence-conclusion discourse relations, also known as arguments, often appear in product reviews, and we hypothesise that some argument-based features, e.g. the percentage of argumentative sentences, the evidences-conclusions ratios, are good indicators of helpful reviews. To validate this hypothesis, we manually annotate arguments in 110 hotel reviews, and investigate the effectiveness of several combinations of argument-based features. Experiments suggest that, when being used together with the argument-based features, the state-of-the-art baseline features can enjoy a performance boost (in terms of F1) of 11.01\% in average.Comment: 6 pages, EMNLP201

Using Argument-based Features to Predict and Analyse Review Helpfulness

We study the helpful product reviews identification problem in this paper. We observe that the evidence-conclusion discourse relations, also known as arguments, often appear in product reviews, and we hypothesise that some argument-based features, e.g. the percentage of argumentative sentences, the evidences-conclusions ratios, are good indicators of helpful reviews. To validate this hypothesis, we manually annotate arguments in 110 hotel reviews, and investigate the effectiveness of several combinations of argument-based features. Experiments suggest that, when being used together with the argument-based features, the state-of-the-art baseline features can enjoy a performance boost (in terms of F1) of 11.01\% in average.Comment: 6 pages, EMNLP201

Anomaly Detection of Underwater Gliders Verified by Deployment Data

This paper utilizes an anomaly detection algorithm to check if underwater gliders are operating normally in the unknown ocean environment. Glider pilots can be warned of the detected glider anomaly in real time, thus taking over the glider appropriately and avoiding further damage to the glider. The adopted algorithm is validated by two valuable sets of data in real glider deployments, the University of South Florida (USF) glider Stella and the Skidaway Institute of Oceanography (SkIO) glider Angus.Comment: 10 pages, 16 figures, accepted by the International Symposium on Underwater Technology (UT23

Real-time Autonomous Glider Navigation Software

Underwater gliders are widely utilized for ocean sampling, surveillance, and other various oceanic applications. In the context of complex ocean environments, gliders may yield poor navigation performance due to strong ocean currents, thus requiring substantial human effort during the manual piloting process. To enhance navigation accuracy, we developed a real-time autonomous glider navigation software, named GENIoS Python, which generates waypoints based on flow predictions to assist human piloting. The software is designed to closely check glider status, provide customizable experiment settings, utilize lightweight computing resources, offer stably communicate with dockservers, robustly run for extended operation time, and quantitatively compare flow estimates, which add to its value as an autonomous tool for underwater glider navigation.Comment: OCEANS 2023 Limeric

Interpretable Math Word Problem Solution Generation Via Step-by-step Planning

Solutions to math word problems (MWPs) with step-by-step explanations are valuable, especially in education, to help students better comprehend problem-solving strategies. Most existing approaches only focus on obtaining the final correct answer. A few recent approaches leverage intermediate solution steps to improve final answer correctness but often cannot generate coherent steps with a clear solution strategy. Contrary to existing work, we focus on improving the correctness and coherence of the intermediate solutions steps. We propose a step-by-step planning approach for intermediate solution generation, which strategically plans the generation of the next solution step based on the MWP and the previous solution steps. Our approach first plans the next step by predicting the necessary math operation needed to proceed, given history steps, then generates the next step, token-by-token, by prompting a language model with the predicted math operation. Experiments on the GSM8K dataset demonstrate that our approach improves the accuracy and interpretability of the solution on both automatic metrics and human evaluation.Comment: Accepted to The 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023

A reading model of young EFL learners regarding attention, cognitive-load and auditory-assistance

Audio-assisted reading (reading-while-listening) was commonly used as a pedagogical method in English (L2) learning. Numerous studies had reported its efficacy in English (L2) reading. Its efficacy in reading comprehension has been inconclusive due to the lack of studies on the relationship among attention, cognitive load and L2 reading comprehension, with the possibility that the synchronous auditory input lessens attention to the visual input. We present a study of 41 Mandarin-speaking 8-year-old children reading English texts in three modes in a between-participants design. Data of cognitive load, comprehension scores and attention were fitted to a formal mathematical model, which confirmed that influences on L2 reading comprehension could be captured by interactions between attention and cognitive load. Based on the findings, three implications regarding how to appropriately apply auditory-assistant tools to L2 reading were generated

Multi-omics analysis of potential metabolic networks linking peripheral metabolic changes to inflammatory retinal conditions in STZ-induced early diabetic retinopathy

Background: Diabetic retinopathy (DR), a leading cause of blindness among working-age adults, lacks targeted therapies besides glucose management. Early retinal lesions are linked to serum metabolites, but the underlying peripheral regulatory networks is unclear. Methods: We first established a streptozotocin (STZ)-induced mouse model of early DR exhibiting retinal inflammation characteristics. This study employed an integrative approach, combining retinal and serum transcriptomic and metabolomic profiles with genome-wide association study (GWAS) data, to identify peripheral metabolites potentially linking early retinal lesions. Results: STZ-induced mice exhibited retinal inflammation and metabolic dysregulation. Metabolites including glucose, sorbitol, and mannitol were altered in both serum and retina, implicating their potential involvement in retinal inflammation. Utilizing GWAS data of diabetic patients, we further explore the potential the upstream regulation of shared metabolites and their peripheral pathways potentially instigating early retinal inflammation through metabolite-related genes correlated with single nucleotide polymorphisms. Key enzyme genes including HK1, HKDC1, AKR1B1 in hyperglycemic pathway, CEL and HMGCR in cholesterol pathway, and ACSL1, PPT2 in palmitic acid pathway, may connect the metabolic network of hyperglycemia, hyperfructosemia and disrupted lipid metabolism to retinopathy. Conclusion: This study elucidates the upstream regulatory network of peripheral serum metabolites associated with early retinal lesions. Specifically, the SNPs in key peripheral enzyme genes may exert remote effects on retinal inflammation in DR. This finding provides insights into the systemic metabolic management and offering peripheral precise early detection and treatment.</p