Mining User Interest in Microblogs with a User-Topic Model

Microblogs have become an important platform for people to publish,transform information and acquire knowledge.This paper focuses on the problem of discovering user interest in microblogs.In this paper,we propose a topic mining model based on Latent Dirichlet Allocation(LDA) named user-topic model.For each user,the interests are divided into two parts by different ways to generate the microblogs:original interest and retweet interest.We represent a Gibbs sampling implementation for inference the parameters of our model,and discover not only user's original interest,but also retweet interest.Then we combine original interest and retweet interest to compute interest words for users.Experiments on a dataset of Sina microblogs demonstrate that our model is able to discover user interest effectively and outperforms existing topic models in this task.And we find that original interest and retweet interest are similar and the topics of interest contain user labels.The interest words discovered by our model reflect user labels,but range is much broader.

Analyzing topics in social media for improving digital twinning based product development

Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product development.Previous efforts of digital twinning neglect the decisive consumer feedback in product development stages,failing to cover the gap between physical and digital spaces.This work mines real-world consumer feedbacks through social media topics,which is significant to product development.We specifically analyze the prevalent time of a product topic,giving an insight into both consumer attention and the widely-discussed time of a product.The primary body of current studies regards the prevalent time prediction as an accompanying task or assumes the existence of a preset distribution.Therefore,these proposed solutions are either biased in focused objectives and underlying patterns or weak in the capability of generalization towards diverse topics.To this end,this work combines deep learning and survival analysis to predict the prevalent time of topics.We propose a specialized deep survival model which consists of two modules.The first module enriches input covariates by incorporating latent features of the time-varying text,and the second module fully captures the temporal pattern of a rumor by a recurrent network structure.Moreover,a specific loss function different from regular survival models is proposed to achieve a more reasonable prediction.Extensive experiments on real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods.

A Video Captioning Method by Semantic Topic-Guided Generation

In the video captioning methods based on an encoder-decoder,limited visual features are extracted by an encoder,and a natural sentence of the video content is generated using a decoder.However,this kind ofmethod is dependent on a single video input source and few visual labels,and there is a problem with semantic alignment between video contents and generated natural sentences,which are not suitable for accurately comprehending and describing the video contents.To address this issue,this paper proposes a video captioning method by semantic topic-guided generation.First,a 3D convolutional neural network is utilized to extract the spatiotemporal features of videos during the encoding.Then,the semantic topics of video data are extracted using the visual labels retrieved from similar video data.In the decoding,a decoder is constructed by combining a novel Enhance-TopK sampling algorithm with a Generative Pre-trained Transformer-2 deep neural network,which decreases the influence of“deviation”in the semantic mapping process between videos and texts by jointly decoding a baseline and semantic topics of video contents.During this process,the designed Enhance-TopK sampling algorithm can alleviate a long-tail problem by dynamically adjusting the probability distribution of the predicted words.Finally,the experiments are conducted on two publicly used Microsoft Research Video Description andMicrosoft Research-Video to Text datasets.The experimental results demonstrate that the proposed method outperforms several state-of-art approaches.Specifically,the performance indicators Bilingual Evaluation Understudy,Metric for Evaluation of Translation with Explicit Ordering,Recall Oriented Understudy for Gisting Evaluation-longest common subsequence,and Consensus-based Image Description Evaluation of the proposed method are improved by 1.2%,0.1%,0.3%,and 2.4% on the Microsoft Research Video Description dataset,and 0.1%,1.0%,0.1%,and 2.8% on the Microsoft Research-Video to Text dataset,respectively,compared with the existing video captioning methods.As a result,the proposed method can generate video captioning that is more closely aligned with human natural language expression habits.

Pain perception enhancement in consecutive secondeye phacoemulsification cataract surgeries under topical anesthesia

Cataract is the main cause of visual impairment and blindness worldwide while the only effective cure for cataract is still surgery.Consecutive phacoemulsification under topical anesthesia has been the routine procedure for cataract surgery.However,patients often grumbled that they felt more painful during the second-eye surgery compared to the first-eye surgery.The intraoperative pain experience has negative influence on satisfaction and willingness for second-eye cataract surgery of patients with bilateral cataracts.Intraoperative ocular pain is a complicated process induced by the nociceptors activation in the peripheral nervous system.Immunological,neuropsychological,and pharmacological factors work together in the enhancement of intraoperative pain.Accumulating published literatures have focused on the pain enhancement during the secondeye phacoemulsification surgeries.In this review,we searched PubMed database for articles associated with pain perception differences between consecutive cataract surgeries published up to Feb.1,2024.We summarized the recent research progress in mechanisms and interventions for pain perception enhancement in consecutive secondeye phacoemulsification cataract surgeries.This review aimed to provide novel insights into strategies for improving patients’intraoperative experience in second-eye cataract surgeries.

基于Citation Topic的领域期刊主题演化研究——以行为医学为例

基于论文层面的Citation Topic分类体系,通过测度行为医学领域SCI及SSCI期刊引文主题变动情况,展现国际行为医学领域研究重点以及相关支撑学科的演化。

Enhancing BERTopic with Pre-Clustered Knowledge: Reducing Feature Sparsity in Short Text Topic Modeling

Modeling topics in short texts presents significant challenges due to feature sparsity, particularly when analyzing content generated by large-scale online users. This sparsity can substantially impair semantic capture accuracy. We propose a novel approach that incorporates pre-clustered knowledge into the BERTopic model while reducing the l2 norm for low-frequency words. Our method effectively mitigates feature sparsity during cluster mapping. Empirical evaluation on the StackOverflow dataset demonstrates that our approach outperforms baseline models, achieving superior Macro-F1 scores. These results validate the effectiveness of our proposed feature sparsity reduction technique for short-text topic modeling.

Fuzzy c-means text clustering based on topic concept sub-space

To improve the accuracy of text clustering, fuzzy c-means clustering based on topic concept sub-space （TCS2FCM） is introduced for classifying texts. Five evaluation functions are combined to extract key phrases. Concept phrases, as well as the descriptions of final clusters, are presented using WordNet origin from key phrases. Initial centers and membership matrix are the most important factors affecting clustering performance. Orthogonal concept topic sub-spaces are built with the topic concept phrases representing topics of the texts and the initialization of centers and the membership matrix depend on the concept vectors in sub-spaces. The results show that, different from random initialization of traditional fuzzy c-means clustering, the initialization related to text content contributions can improve clustering precision.

Topic PageRank——一种基于主题的搜索引擎

通过研究传统的超链分析算法PageRank及其改进算法Hilltop和TSPR的不足,提出了一种新的改进的方法Topic PageRank。这种算法是对每一个页面进行页面分类,然后根据分类的结果分别对每一个主题进行页面等级计算,因此,每一个页面对不同的主题将呈现出不同的页面等级得分,能更加准确地反映出页面的重要性。

CICS环境下基于网络图的Topic Maps知识平台研究

在对CICS环境下知识管理的需求和网络图能力的分析基础上,提出了利用Topic Maps技术构造CIS环境下统一、独立的知识平台的思想.围绕工程网络图中的知识转换问题,提出了T和M两阶段变换方法.同时,提出了TM与DBMS系统集成方案,通过TM数据的动态更新来适应CICS生产知识的时变性.该方案可用于CICS环境下的其他领域,从而构造覆盖整个CICS的统一的TM平台.

基于Topic Signature的动态文摘更新方法

目前针对动态文摘的研究关注对象主要是多文档集合,其中内容随时间而更新演化,但动态文摘中存在高冗余、新颖信息丢失等问题,会影响文摘提取质量。为此,研究Topic Signature模型,并在其基础上提出一种新的整数规划动态文摘更新方法。根据句间相似度对每条语句的主题代表性和信息多样性进行评分,利用Topic Signature模型评估语句的新颖性,以提取事件中的更新演进信息。在此基础上,依据摘要生成策略,缩小解的可行域,以保证在短时间内生成高质量的文摘。实验结果表明,该方法无需进行模型训练和语言匹配,能够有效降低时间复杂度,提高文摘提取效率。

基于“Topic”的语义信息组织技术研究——以DITA和Topic Maps为中心

基于“Topic”的语义信息组织与图书馆学的经典Subject理论密不可分，可将其视为较为抽象化的Subject理论在语义Web环境下的一种“演化”和实用化的主题技术。文章首先解读Subject和Topic的概念，并概述两种基于Topic的国际标准技术，即TopicMaps和DITA；其次，简要描述TopicMaps的技术和应用，并重点介绍在图书馆界鲜为人知的DITA技术及其应用；再次，对基于“Topic”的语义信息组织方法予以总结。

Topic Maps与学科知识管理

提出了用主题地图(TopicMaps)来管理学科知识的思想,分析了利用主题地图来建立学科知识结构的优越性。以软件工程专业的几个知识单元为实例,说明了用主题地图导航软件工程知识库的具体方法。用主题地图处理器Omnigator实现了软件工程学科知识的在线索引字典。

Topic Presentation在工程建设法规教学中的应用

CDIO是目前高等工程教育人才培养的一种全新理念和实施体系,目的在于提高学生的综合素质。而Topic Presentation(主题演讲)在欧美教学中是一种常用的教学方法,该方法有助于提高学生的独立思考能力、解决问题能力和交流表达能力。本文作者将Topic Presentation方法运用在工程建设法规课程中,在课程体系的设置中贯穿CDIO理念,通过四年的实践,取得了较好的效果。

工科本科TOPIC企业实习模式探讨

企业实习容易出现一些错误的倾向,如实习过程成为一个走马观花的参观,或实习生成为企业的临时打杂工等,因此,需要一套科学的实习模式.通过理论分析及与企业的合作实践,提出了工科专业本科生进行企业实习的TOPIC模式,即全方位培训、在岗实习、项目载体锻炼、智力援助和企业文化灌输五位一体的实习模式.该模式的采用,为教学与企业零距离链接提供了依据,提高了学生的可雇用技能和就业能力,实现了实习与就业的无缝对接,降低了企业的用工风险.

The Topical Use of Aprotinin in Cardiac Surgery with Cardiopulmonary Bypass

Objective To investigate the effects of the topical use of aprotinin on thebasis of comprehensive blood conservations in cardiopulmonary bypass (CPB). Methods In a prospectiveclinical trial, 20 patients were randomly divided into 2 groups. Control group: placebo was usedtopically. Aprotinin group: aprotinin was poured into the pericardial cavity before closure of thesternotomy. Before and 24h after surgery, hemoglobin (Hb), hematocrit (Hct), bleeding time (BT),clotting time (CT) and prothrombin time (PT) were measured. Meanwhile, amounts of the mediastinaldrainage and the hemoglobin loss were observed at 0, 2, 6 and 24h after operation. The samples fromthe mediastinal drainage were also collected to measure D-Dimer (D-D), tissue type plasminogenactivator (t-PA) activity, plasminogen activator inhibitor (PAI) activity and protein C (PC).Results In Aprotinin group, D-D, t-PA activity and PC were significantly reduced, compared withthose in Control group (P<0.05, P<0.05, P<0.01). On the contrary, PAI activity was significantlyincreased, compared with that in Control group. Amounts of the mediastinal drainage and thehemoglobin loss were decreased by 43% and 52%, compared with those in Control group. Conclusion Ourresults suggest that the topical use of aprotinin can have better effects on the basis ofcomprehensive moderate blood conservation.

Optimization Analysis of Campus Topic Space in Colleges and Universities——A Case Study of the Colleges and Universities in Lishui, Zhejiang Province

University campus is the most important place for life, study, activity and experience of contemporary college students. It is helpful for students to survive and develop to create the topic space of campus. Taking the topic space of college campuses in Lishui City of Zhejiang Province as an example, the current situations are analyzed through questionnaire survey and field visit. The results show that uni- versity campus space needs a clear topic; the demands are generally large for the topics of exchange and communication, learning and thinking, sports and leisure in all kinds of space; the creation of these types of topic spaces should focus on the peaceful environment, beautiful scenery, privacy of the space and WlFI coverage.

A Syntactic Contrast of English and Chinese——Subject-Prominent vs.Topic-Prominent

English and Chinese belong to different language families,employing two distinct syntactic systems.English is subject-prominent,following the pattern of subject first,then predicate;while Chinese is topic-prominent,showing much flexibility in word arrangement as well as the necessity of subject and predicate.

An investigation of the effect of L2 proficiency and topic familiarity on L2 Incidental Vocabulary Acquisition： An empirical study based on theory of interactive reading

Based on the interactive theory of reading, this study mainly explored the etlects ot topic familiarity and second language proficiency on IVA （Incidental Vocabulary Acquisition） of second language through reading. By using two different measures （translation production and selection）, this study found： （1） Vocabulary can be acquired incidentally in reading passages; （2） There are no significant interactive effects of topic familiarity and second language proficiency on vocabulary acquisition, but the two independent variables of topic familiarity and second language proficiency exerted their positively significant effect on incidental vocabulary acquisition, and （3） As for the two vocabulary measures, learners can acquire more words in translation selection than in translation production.

Graffiti in College:Topic Analysis and Linguistic Features

This paper explores how the Chinese college students' life is represented in some graffiti collected in campus.The article analyzes and compares the topics of graffiti from different settings and the linguistic features they manifest.The findings show that fewer graffiti from female toilet and classroom in this university pay attention to political issues compared with the graffiti abroad.Graffiti in female toilet mainly focus on the theme of love,and are found to be more interactive in discourse.Whereas graffiti on desks tend to cover mixed themes and be less interactive.There are more graphic graffiti and exam answers on the undergraduate students' desk than on the postgraduates'.Graffiti have some linguistic features as thematization,repetition and salience,etc.

基于Topic Circle的大学英语口语教学实践

Topic Circle是一种口语合作学习形式,它可以帮助学生在短时间的口语交际中,提高口语表达的流利性,获取大量未知信息,从而丰富口语表达的信息量。Topic Circle能深化学生口语表达的内容,从而充分调动学生口语表达的积极性,而且它的覆盖面广,是一种有效的大班口语教学形式。