共查询到20条相似文献，搜索用时 31 毫秒
1.
《Information processing & management》2023,60(4):103412
Recently, phishing scams have become one of the most serious types of crime involved in Ethereum, the second-largest blockchain-based cryptocurrency platform. The existing phishing scams detection techniques for Ethereum mostly use traditional machine learning or network representation learning to mine the key information from the transaction network and identify phishing addresses. However, these methods typically crop the temporal transaction graph into snapshot sequences or construct temporal random wanderings to model the dynamic evolution of the topology of the transaction graph. In this paper, we propose PDTGA, a method that applies graph representation learning based on temporal graphs attention to improve the effectiveness of phishing scams detection in Ethereum. Specifically, we learn the functional representation of time directly and model the time signal through the interactions between the time encoding function and node features, edge features, and the topology of the graph. We collected a real-world Ethereum phishing scam dataset, containing over 250,000 transaction records between more than 100,000 account addresses, and divided them into three datasets of different sizes. Through data analysis, we first summarized the periodic pattern of Ethereum phishing scam activities. Then we constructed 14 kinds of account node features and 3 kinds of transaction edge features. Experimental evaluations based on the above three datasets demonstrate that PDTGA with 94.78% AUC score and 88.76% recall score outperforms the state-of-the-art methods. 相似文献
2.
文章通过研读合作研发领域代表性理论和实证研究文献,以合作研发建立过程为脉络,以交易成本理论、资源基础理论为阐述基础,梳理了合作研发领域的整体研究框架：对合作研发起源及其主要类型进行了系统的阐述;基于资源基础理论、交易成本理论和组织学习理论归结了合作研发的六种主要动机和获取竞争优势（利润）这一根本动机;从资源共同力量（collective strengthen） 和组织间冲突（inter-firm conflict）两个视角分析合作伙伴的相关特征及对合作绩效的影响;探讨了合作研发的组织管理,包括合作研发的基本组织类型及特征,梳理了企业实现有效知识溢出的专有性机制。最后,提炼研究结论及后续研究方向,旨在为后续的研究提供一个整体切入点,为合作研发实践活动的组织和评价提供参考。 相似文献
3.
Mohammad Tubishat Norisma Idris Mohammad A.M. Abushariah 《Information processing & management》2018,54(4):545-563
Sentiment analysis is a text classification branch, which is defined as the process of extracting sentiment terms (i.e. feature/aspect, or opinion) and determining their opinion semantic orientation. At aspect level, aspect extraction is the core task for sentiment analysis which can either be implicit or explicit aspects. The growth of sentiment analysis has resulted in the emergence of various techniques for both explicit and implicit aspect extraction. However, majority of the research attempts targeted explicit aspect extraction, which indicates that there is a lack of research on implicit aspect extraction. This research provides a review of implicit aspect/features extraction techniques from different perspectives. The first perspective is making a comparison analysis for the techniques available for implicit term extraction with a brief summary of each technique. The second perspective is classifying and comparing the performance, datasets, language used, and shortcomings of the available techniques. In this study, over 50 articles have been reviewed, however, only 45 articles on implicit aspect extraction that span from 2005 to 2016 were analyzed and discussed. Majority of the researchers on implicit aspects extraction rely heavily on unsupervised methods in their research, which makes about 64% of the 45 articles, followed by supervised methods of about 27%, and lastly semi-supervised of 9%. In addition, 25 articles conducted the research work solely on product reviews, and 5 articles conducted their research work using product reviews jointly with other types of data, which makes product review datasets the most frequently used data type compared to other types. Furthermore, research on implicit aspect features extraction has focused on English and Chinese languages compared to other languages. Finally, this review also provides recommendations for future research directions and open problems. 相似文献
4.
战略采购的本质是采购企业在市场、网络和内部供应三种交易规则中进行动态选择,以获取交易成本和交易效率持续优化的过程。企业可以应用的一种战略采购模型——项目定位模型将企业的采购项目划分为四种类型:日常型、杠杆型、瓶颈型和关键型,企业应针对不同类型的项目制订不同的采购战略。 相似文献
5.
6.
《Information processing & management》2020,57(6):102303
Increased usage of bots through the Internet in general, and social networks in particular, has many implications related to influencing public opinion. Mechanisms to distinguish humans from machines span a broad spectrum of applications and hence vary in their nature and complexity. Here we use several public Twitter datasets to build a model that can predict whether or not an account is a bot account based on features extracted at the tweet or the account level. We then apply the model to Twitter's Russian Troll Tweets dataset. At the account level, we evaluate features related to how often Twitter accounts are tweeting, as previous research has shown that bots are very active at some account levels and very low at others. At the tweet level, we noticed that bot accounts tend to sound more formal or structured, whereas real user accounts tend to be more informal in that they contain more slang, slurs, cursing, and the like. We also noted that bots can be created for a range of different goals (e.g., marketing and politics) and that their behaviors vary based on those distinct goals. Ultimately, for high bot-prediction accuracy, models should consider and distinguish among the different goals for which bots are created. 相似文献
7.
中国土地市场化测度方法与实证研究 总被引：1，自引：0，他引：1
构建科学、客观、易判的土地市场化测度方法,有助于理解和分析我国土地资源配置的时空差异。本文在归纳总结已有测算方法的基础上,提出价款加权修正宗数比重测度法和实际-理想价款比值测度法,并以2000年-2009年中国土地市场化发展为实证,比较不同方法的特征、适用范围、结果的共性和差异。研究结果表明,2000年-2009年中国土地市场化指数呈现震荡上升的态势,2006年前后土地市场化指数较大幅度的增长;宗数比重测度法和面积比重测度法仅考虑了完全市场下的土地供应,不适用于土地市场化的专题研究;静态系数宗数比重测度法适用于短时间序列的研究,而价款加权修正宗数比重测度法适宜于较小尺度、土地供应类型趋于一致的区域研究。各供地类型的市场化权重需考虑历年供地类型的实际效果,从土地资本显化视角出发的实际-理想价款比值测度法可以更为客观、直接的反映土地市场化程度。 相似文献
8.
《Information processing & management》2023,60(2):103230
As a hot spot these years, cross-domain sentiment classification aims to learn a reliable classifier using labeled data from a source domain and evaluate the classifier on a target domain. In this vein, most approaches utilized domain adaptation that maps data from different domains into a common feature space. To further improve the model performance, several methods targeted to mine domain-specific information were proposed. However, most of them only utilized a limited part of domain-specific information. In this study, we first develop a method of extracting domain-specific words based on the topic information derived from topic models. Then, we propose a Topic Driven Adaptive Network (TDAN) for cross-domain sentiment classification. The network consists of two sub-networks: a semantics attention network and a domain-specific word attention network, the structures of which are based on transformers. These sub-networks take different forms of input and their outputs are fused as the feature vector. Experiments validate the effectiveness of our TDAN on sentiment classification across domains. Case studies also indicate that topic models have the potential to add value to cross-domain sentiment classification by discovering interpretable and low-dimensional subspaces. 相似文献
9.
组织合作网络结构对企业绩效的影响有两类相反的作用机制：网络闭合和网络开放。论文认为,哪种机制起作用取决于企业所面临的创新任务以及知识来源在网络中的位置。基于汤森路透、USPTO和Compustat三个数据库,论文构建1990-2001年生物技术和医药产业追踪数据,采用社会网络分析方法、固定效应和随机效应模型对此问题进行实证研究。结果发现,战略联盟网络密度增加和结构洞指标增加会负向影响企业技术创新数量,正向影响企业技术创新质量;网络结构调节着直接联盟关系和间接联盟关系对企业技术创新的影响。 相似文献
10.
The article focuses on the social workers’ workarounds aka their own alternative strategies for defeating the various types of obstacles in information interaction in a client information system (CIS). Data consists of semi-structured interviews and social workers’ observations with their verbal accounts while they used CIS in their daily work. The workarounds were analyzed from the process perspective when antecedent conditions, actual workarounds and their consequences were taken into account. The design flaws and external demands in work generated the workarounds. The social workers used small scale tricks within CIS to maintain continuum in a client’s trajectory; they relied on shadow systems to manage their whole clientele; and took shortcuts in production of statistical information. The workarounds offered a better grip on information and saved time. However, some of the workarounds were tensional in a child protection context. The analysis of workarounds provided valuable secondary design suggestions to remedy CIS. 相似文献
11.
Hao Zhang Frank Boons Riza Batista-Navarro 《Information processing & management》2019,56(5):1837-1848
Narratives are comprised of stories that provide insight into social processes. To facilitate the analysis of narratives in a more efficient manner, natural language processing (NLP) methods have been employed in order to automatically extract information from textual sources, e.g., newspaper articles. Existing work on automatic narrative extraction, however, has ignored the nested character of narratives. In this work, we argue that a narrative may contain multiple accounts given by different actors. Each individual account provides insight into the beliefs and desires underpinning an actor’s actions. We present a pipeline for automatically extracting accounts, consisting of NLP methods for: (1) named entity recognition, (2) event extraction, and (3) attribution extraction. Machine learning-based models for named entity recognition were trained based on a state-of-the-art neural network architecture for sequence labelling. For event extraction, we developed a hybrid approach combining the use of semantic role labelling tools, the FrameNet repository of semantic frames, and a lexicon of event nouns. Meanwhile, attribution extraction was addressed with the aid of a dependency parser and Levin’s verb classes. To facilitate the development and evaluation of these methods, we constructed a new corpus of news articles, in which named entities, events and attributions have been manually marked up following a novel annotation scheme that covers over 20 event types relating to socio-economic phenomena. Evaluation results show that relative to a baseline method underpinned solely by semantic role labelling tools, our event extraction approach optimises recall by 12.22–14.20 percentage points (reaching as high as 92.60% on one data set). Meanwhile, the use of Levin’s verb classes in attribution extraction obtains optimal performance in terms of F-score, outperforming a baseline method by 7.64–11.96 percentage points. Our proposed approach was applied on news articles focused on industrial regeneration cases. This facilitated the generation of accounts of events that are attributed to specific actors. 相似文献
12.
《Information processing & management》2020,57(6):102323
With the fast growth of e-commerce and the emerging new retail trend—online and offline integration—it is important to recognize the target market and satisfy customers with different needs by analyzing their online search behaviors. Accordingly, we propose sequential search pattern analysis and clustering to analyze consumers’ search behavior throughout the entire shopping process from the perspective of consumer need-states. We seek to understand how recommendation functions (RFs) or popular non-RF web features help consumers to shop online from a need-state perspective. We adopt maximal repeat patterns (MRPs) and lag sequential analysis (LSA) to analyze the sequence of search paths and identify significant repeated search patterns. Furthermore, to investigate the behaviors of customers with different types of need-states, we analyze webpages related to RFs and non-RF features using clustering to connect the evaluation results of search patterns with page traversal behaviors. This yields four groups of consumers who browse for information, adopt recommendations, consult reviews, and conduct searches with different levels of goal-oriented or exploratory-based need-states. The results show that consumers with strong goal-oriented need-states have the simplest search paths compared to other groups, whereas exploratory-based consumers have the most complicated search paths. Furthermore, consumers with higher need-states tend to search directly, consult reviews carefully, and have stored sequential search patterns, whereas consumers with exploratory-based need-states tend to explore the categories of products and adopt product classification hierarchy as a pivot to explore web features and then adopt specific types of RFs. Interestingly, consumers in the review-consulting group all belong to the goal-oriented need-states type with strong knowledge-building behaviors compared to others. The results reveal that each group employs its own particular web features to facilitate the shopping process and we can identify consumer types based on shopping behavior in the early stage of shopping. This suggests that e-store sellers can refine web features and deploy marketing strategies tailored to the search patterns for different levels of need-states. 相似文献
13.
Achieving the anticipated business benefits of a social medium is important as organizations diligently invest in different social media platforms. While much previous research assumes that social media helps organizations to communicate with customers, less is known about whether customers embrace using social media to interact with organizations. It is important to understand the role of social media for business communication from the customers’ perspective, as this may significantly deviate from the organizations’ own communicative intentions. In this exploratory case study of the Moon Struck hotel in China, we investigate both how customers interpret the hotel’s use of WeChat official account for business communication and how customers respond to messages received from Moon Struck’s WeChat account. Adopting a symbolic interactionism perspective, we surprisingly find that WeChat personal accounts and Moon Struck’s official account offer radically different meanings to followers. Specifically, WeChat personal account symbolizes a sociality-oriented meaning (e.g., relationship and image building), while Moon Struck’s WeChat official account symbolizes information broadcasting-related meaning (e.g., selling, advertising, and branding). Both technological features and the distance of relationships among users contribute to the constructed symbolic meaning of technology, subsequently affecting users’ WeChat use patterns. The theoretical implications of this study are discussed and recommendations are made for future research and practice. 相似文献
14.
Ekrem Duman 《Journal of The Franklin Institute》2007,344(5):672-683
This study is based on an actual simulation application project carried out for a parcel transportation company. In its current system, the company has a wide network of branches throughout the country. Although, it is good to have a large network in terms of accessibility and increasing the business volume, performing the same operations in almost every branch is costly ineffective. Consequently, the company managers considered merging several branches in the same neighborhood and carrying out most of the tasks in these central branches. As they consulted us to see if this idea is feasible or not, we decided to use simulation modeling. After carefully investigating the details of the system we developed a comprehensive model of this dynamic and complicated system and looked at the feasibility and also the limitations of their approach. After getting the results, we noticed that what they planned would not work out and developed another central branch design that could work out. Using design of experiments we obtained the behavior of the suggested system under different business scenarios. In this study, we describe the details of this interesting application of simulation modeling. 相似文献
15.
【目的/意义】随着互联网在社会中的影响力逐渐增大,面对网络群体性事件对社会生活的冲击,需把握网
络群体性事件的演化规律,确定事件类别,提炼事件特征,基于不同类别的网络群体性事件,提出有针对性的应对
措施。【方法/过程】通过LDA主题模型与K-means算法相结合,利用LDA模型实现文本潜在语义的识别,最终运用
SVM算法进行网络群体性事件聚类分析,得到五类网络群体性事件。【结果/结论】构建的网络群体性事件动态识别
模型,通过大量的文本训练,在事件聚类数为5时具有良好的解释性,完成了网络群体性事件的客观分类,分别为：
经济型、社会型、文化型、民族型和环境型,为政府分类应对策略提供依据。【创新/局限】利用 LDA主题模型和 Kmeans算法,减少了模型的迭代次数,确定最佳主题数,提高了网络群体性事件识别结果的准确性,但是运用慧科新
闻数据库搜集到的文本数据范围有限,且分类结果反应的事件特征具有一定局限性,后续研究可进一步扩大动态
文本数据库,对分类算法进行改进和深化。 相似文献
16.
从产业和区域两层面,对碳基能源资源流动节点要素进行分析,阐述了当前研究中节点类型划分及其依据,分别确定节点要素为生产节点、中转节点和消费节点这一类型体系以及抽象节点体系等两大节点类型体系。通过解析各类型节点的功能和职能,可知碳基能源资源流动中,节点不仅履行基本的业务职能而且还发挥着流动体系效能和社会经济溢出功能的作用。通过梳理节点研究的内容,从节点功能、节点系统和节点关系三个方面解析了不同类型节点研究的关注点和主要方法。基于以上研究分析认为,碳基能源资源流动节点分析中,节点类型是多样的,既有产业链条中的企业节点研究,也有以区域视角的节点分析,相关研究蕴含于诸如资源科学、物流学、地理学、生态学等多学科之中;不同类型节点研究内容特色鲜明,产业层面的节点研究多以物流学供给链和供给网络以及生态学节点能源利用研究为主,而区域层面的节点研究多为探讨节点空间结构、等级结构和交流关系等。最后,根据碳基能源资源流动节点研究现状指出当前研究不足,并提出加强流动节点理论研究和方法集成研究的学术建议。 相似文献
17.
拥有互补性专利的双寡头厂商可以进行三种方式的专利交易,分别是无专利授权、交叉许可授权和专利联盟授权.通过构建两阶段动态博弈模型计算不同专利交易方式的市场绩效,并从企业和社会两个角度分析三种专利交易方式的优劣.结果表明:从企业层面来说,专利联盟授权是企业最优的专利交易方式,因为专利联盟授权使企业获得最大的生产者剩余;而从社会层面来说,政府应该认真审核积极引导专利联盟的组建,因为专利联盟授权有可能降低消费者剩余,损害消费者利益. 相似文献
18.
Arkaitz Zubiaga Elena Kochkina Maria Liakata Rob Procter Michal Lukasik Kalina Bontcheva Trevor Cohn Isabelle Augenstein 《Information processing & management》2018,54(2):273-290
Rumour stance classification, defined as classifying the stance of specific social media posts into one of supporting, denying, querying or commenting on an earlier post, is becoming of increasing interest to researchers. While most previous work has focused on using individual tweets as classifier inputs, here we report on the performance of sequential classifiers that exploit the discourse features inherent in social media interactions or ‘conversational threads’. Testing the effectiveness of four sequential classifiers – Hawkes Processes, Linear-Chain Conditional Random Fields (Linear CRF), Tree-Structured Conditional Random Fields (Tree CRF) and Long Short Term Memory networks (LSTM) – on eight datasets associated with breaking news stories, and looking at different types of local and contextual features, our work sheds new light on the development of accurate stance classifiers. We show that sequential classifiers that exploit the use of discourse properties in social media conversations while using only local features, outperform non-sequential classifiers. Furthermore, we show that LSTM using a reduced set of features can outperform the other sequential classifiers; this performance is consistent across datasets and across types of stances. To conclude, our work also analyses the different features under study, identifying those that best help characterise and distinguish between stances, such as supporting tweets being more likely to be accompanied by evidence than denying tweets. We also set forth a number of directions for future research. 相似文献
19.
20.
【目的/意义】在线健康社区用户规模庞大,信息量浩如烟海,如何帮助社区管理者和用户判别有用信息,提
高决策效率是亟待解决的问题。【方法/过程】在复杂网络视角下,提出一个新的评论有用性分析框架。首先,采集
在线健康社区患者评论数据,采用文本分析法分析有用评论、非有用评论以及所有评论的主题分布和情感分布,初
步分析各类评论文本的有用性特征;其次,将各类评论文本分别转换为文本关联网络,使用社会网络分析方法进一
步分析其有用性特征;最后,分析评论有用性及其特征与患者发表评论、用户对评论的有用性投票以及文本关联网
络结构特征的关联性,实现基于文本关联网络的评论有用性分析。【结果/结论】有用评论和非有用评论文本关联网
络结构具有一定差异,在线健康社区用户就诊前后的信息需求和经验输出的重点有所不同。【创新/局限】基于复杂
网络视角研究在线健康社区评论有用性,但仅使用了好大夫在线的数据,未来可对更多数量和种类的在线健康社
区信息内容有用性进行研究。 相似文献