Accurate analysis of patients' feedback on various medical aspects is of great importance for improving the quality of healthcare services. In this paper, we address the task of extracting aspects and opinions by ...
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Purpose:We attempt to find out whether OA or TA really affects the dissemination of scientific ***/methodology/approach:We design the indicators,hot-degree,and R-index to indicate a topic OA or TA ***,according to the...
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Purpose:We attempt to find out whether OA or TA really affects the dissemination of scientific ***/methodology/approach:We design the indicators,hot-degree,and R-index to indicate a topic OA or TA ***,according to the OA classification of the Web of Science(WoS),we collect data from the WoS by downloading OA and TA articles,letters,and reviews published in Nature and Science during 2010–*** papers are divided into three broad disciplines,namely biomedicine,physics,and ***,taking a discipline in a journal and using the classical Latent Dirichlet Allocation(LDA)to cluster 100 topics of OA and TA papers respectively,we apply the Pearson correlation coefficient to match the topics of OA and TA,and calculate the hot-degree and R-index of every OA-TA topic ***,characteristics of the discipline can be *** qualitative comparison,we choose some high-quality papers which belong to Nature remarkable papers or Science breakthroughs,and analyze the relations between OA/TA and citation ***:The result shows that OA hot-degree in biomedicine is significantly greater than that of TA,but significantly less than that of TA in *** on the R-index,it is found that OA advantages exist in biomedicine and TA advantages do in ***,the dissemination of average scientific discoveries in all fields is not necessarily affected by OA or ***,OA promotes the spread of important scientific discoveries in high-quality *** limitations:We lost some citations by ignoring other open sources such as arXiv and *** limitation came from that Nature employs some strong measures for access-promoting subscription-based articles,on which the boundary between OA and TA became *** implications:It is useful to select hot topics in a set of publications by the hotdegree *** finding comprehensively reflects the differences of OA and TA in different disciplines,which is a u
The existing vehicle-bridge coupled vibration analysis of the vehicle model cannot accurately consider the vehicle dynamic characteristics and the impact of flexible tires on the vehicle-bridge coupled vibration respo...
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This study aims to clarify the contours of artificial intelligence (AI) and present how it has evolved in different publication venues in the different stages of its development. Based on the noun phrases extracted fr...
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Journal discriminative capacity refers to the degree of difference between the journals in research subjects, and is of great significance for detecting the level of journal differentiation. Current research on journa...
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Topic shift detection aims to identify whether there is a change in the current topic of conversation or if a change is needed. The study found previous work did not evaluate the performance of large language models l...
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ISBN:
(数字)9798350376548
ISBN:
(纸本)9798350376555
Topic shift detection aims to identify whether there is a change in the current topic of conversation or if a change is needed. The study found previous work did not evaluate the performance of large language models like ChatGPT on the task of topic shift. Therefore, this paper's main task and innovation lie in analyzing ChatGPT's performance on topic shift detection. To provide a more comprehensive evaluation, we conducted topic shift detection tasks on ChatGPT from three aspects: single utterances, adjacent utterances, and contextual levels. Additionally, to gauge the performance of large language models, we conducted experiments on multiple small-scale models and compared the results of the two models. Experimental results on the publicly available English TIAGE dataset showed that small-scale models exhibited lower recall in all three aspects, while ChatGPT performed better in the recall. This suggests that compared to small-scale models, large models are more capable of accurately detecting topic shifts. However, large models also exhibited lower precision, indicating that while ChatGPT can recognize content differences in utterances, its judgment on whether these different contents belong to the same topic is poor.
We give a fast algorithm for sampling uniform solutions of general constraint satisfaction problems (CSPs) in a local lemma regime. Suppose that the CSP has n variables with domain size at most q, each constraint cont...
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Purpose:This study aims to explore the trend and status of international collaboration in the field of artificial intelligence(AI)and to understand the hot topics,core groups,and major collaboration patterns in global...
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Purpose:This study aims to explore the trend and status of international collaboration in the field of artificial intelligence(AI)and to understand the hot topics,core groups,and major collaboration patterns in global AI ***/methodology/approach:We selected 38,224 papers in the field of AI from 1985 to 2019 in the core collection database of Web of Science(WoS)and studied international collaboration from the perspectives of authors,institutions,and countries through bibliometric analysis and social network ***:The bibliometric results show that in the field of AI,the number of published papers is increasing every year,and 84.8%of them are cooperative *** with more than three authors,collaboration between two countries and collaboration within institutions are the three main levels of collaboration *** social network analysis,this study found that the US,the UK,France,and Spain led global collaboration research in the field of AI at the country level,while Vietnam,Saudi Arabia,and United Arab Emirates had a high degree of international *** at the institution level reflects obvious regional and economic *** are the Developing Countries Institution Collaboration Group led by Iran,China,and Vietnam,as well as the Developed Countries Institution Collaboration Group led by the US,Canada,the ***,the Chinese Academy of Sciences(China)plays an important,pivotal role in connecting the these institutional collaboration *** limitations:First,participant contributions in international collaboration may have varied,but in our research they are viewed equally when building collaboration ***,although the edge weight in the collaboration network is considered,it is only used to help reduce the network and does not reflect the strength of *** implications:The findings fill the current shortage of research on international collaboration in A
Social question and answer (Q&A) platforms offer a new way for identifying information needs of people with certain diseases. Taking Quora as an example, we examine which health topics are of interest to autistic ...
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Social question and answer (Q&A) platforms offer a new way for identifying information needs of people with certain diseases. Taking Quora as an example, we examine which health topics are of interest to autistic people and how these topics evolve over time. Experimental results reveal increasingly heavy and diverse attention to the condition, from diagnosis and treatment of autism itself to extended issues like social challenges, parenting, and education issues. We find that users tend to post clinical concerns about autism on Quora although traditionally such social Q&A platforms encourage more social and awareness-level questions. New concerns have appeared recently about autism's relations to other diseases like attention deficit hyperactivity disorder (ADHD) and obsessive–compulsive disorder (OCD). This study is beneficial for tracking and responding to autistic patients' and caregivers' information needs. Author(s) retain copyright, but ASIS&T receives an exclusive publication license
Next-POI recommendation aims to explore from user check-in sequence to predict the next possible location to be visited. Existing methods are often difficult to model the implicit association of multi-modal data with ...
Next-POI recommendation aims to explore from user check-in sequence to predict the next possible location to be visited. Existing methods are often difficult to model the implicit association of multi-modal data with user choices. Moreover, traditional methods struggle to fully explore the variation of user preferences at variable time intervals. To tackle these limitations, we propose a Multi-Modal Temporal knowledge Graph-aware Sub-graph Embedding approach (Mandari). We first construct a novel Multi-Modal Temporal knowledge Graph. Based on the proposed knowledge graph, we integrate multi-modal information and leverage the graph attention network to calculate sub-graph prediction probability. Next, we implement a temporal knowledge mining method to model the segmentation and periodicity of user check-in and obtain temporal prediction probability. Finally, we fuse temporal prediction probability with the previous sub-graph prediction probability to obtain the final result. Extensive experiments demonstrate that our approach outperforms existing state-of-the-art methods.
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