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14th International Space Syntax Symposium, SSS 2024

作者： Hacar, Müslüm Hacar, Özge Öztürk Altafini, Diego Pappalardo, Luca Gülgen, Fatih Cutini, Valerio Department of Geomatic Engineering Yildiz Technical University Turkey Department of Energy Systems Territory and Construction Engineering University of Pisa Italy Knowledge Discovery and Data Mining Laboratory ISTI-CNR Italy Welsh School of Architecture Cardiff University United Kingdom

ISBN: (纸本)9791256690329

The experiences of urban visitors are frequently captured and shared on various websites and social platforms through reviews and ratings. These "digital footprints" help us understand what visitors think about a certain place. High visitor traffic may stem from the urban layout and configuration, such as the importance of a street, the building characteristic, or the location of the place within an urban settlement. Hence, these digital footprints are shaped by a complex interplay of spatial, emotional, self-organizational, and socio-behavioural factors. This presents us with compelling research questions: To what extent does urban configuration influence these digital footprints? And how exactly does this dynamic play out? This research examines the intricate relationship between urban spatial characteristics and digital footprints in the realm of urban tourism. Our approach taps into Space Syntax metrics and associates them with places, extracted as points of interest from Google Maps API. This framework helps ascertain what is the linkage between urban configuration and visitors’ digital activities, to reveal another layer of social behaviour within the cities. Our research centred on the historic city of Sassi di Matera, Italy, distinguished by its cave dwellings and intricate pathways. Initial findings from our research present significant correlations between Space Syntax metrics and visitors’ reviewing activities at specific places. By correlating the configurational patterns with reviews and ratings, we observed that these places are influenced by surrounding space, and that this situation varies depending on the type of place. © 14th International Space Syntax Symposium, SSS 2024.

关键词： Syntactics

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Local anatomy for personalised privacy protection

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International Journal of Information and Computer Security 2021年第2-3期15卷 254-271页

作者： Li, Boyu Liu, Yanheng Wang, Minghai Sun, Geng Li, Bin College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun China Big Data and Network Management Center Jilin University Changchun China College of Mathematics Jilin University Changchun China

Anonymisation technique has been extensively studied and widely applied for privacy-preserving data publishing. However, most existing methods ignore personal anonymity requirements. In these approaches, the microdata consist of three categories of attribute: explicit-identifier, quasi-identifier and sensitive attribute. In fact, the data sensitivity should be determined by individuals. An attribute is semi-sensitive if it contains both QI and sensitive values. In this paper, we propose a novel anonymisation approach, called local anatomy, to address personalised privacy protection. Local anatomy partitions the tuples who consider the value as sensitive into buckets inside each attribute. We conduct some experiments to illustrate that local anatomy can protect all the sensitive values and preserve great information utility. Additionally, we also present the concept of intelligent anonymisation system as our direction of future work. © 2021 Inderscience Enterprises Ltd.

关键词： Sensitive data

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A Heuristic Sampling Method for Maintaining the Probability Distribution

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Journal of Computer Science & Technology 2021年第4期36卷 896-909页

作者： Jiao-Yun Yang Jun-Da Wang Yi-Fang Zhang Wen-Juan Cheng Lian Li Key Laboratory of Knowledge Engineering with Big Data of Ministry of Education Hefei University of Technology Hefei 230601China National Smart EldeTca/re International Science and Technology Coopemtion Base Hefei University of Technology Hefei 230601China School of Computer Science and Information Engirwering Hefei University of TechnologyHefei 230601China School of Mathematics Hefei University of TechnologyHefei 230601China

Sampling is a fundamental method for generating data *** many data analysis methods are developed based on probability distributions,maintaining distributions when sampling can help to ensure good data analysis ***,sampling a minimum subset while maintaining probability distributions is still a *** this paper,we decompose a joint probability distribution into a product of conditional probabilities based on Bayesian networks and use the chi-square test to formulate a sampling problem that requires that the sampled subset pass the distribution test to ensure the ***,a heuristic sampling algorithm is proposed to generate the required subset by designing two scoring functions:one based on the chi-square test and the other based on likelihood *** on four types of datasets with a size of 60000 show that when the significant difference level,a,is set to 0.05,the algorithm can exclude 99.9%,99.0%,93.1%and 96.7%of the samples based on their Bayesian networks-ASIA,ALARM,HEPAR2,and ANDES,*** subsets of the same size are sampled,the subset generated by our algorithm passes all the distribution tests and the average distribution difference is approximately 0.03;by contrast,the subsets generated by random sampling pass only 83.8%of the tests,and the average distribution difference is approximately 0.24.

关键词： Bayesian network chi-square test sampling probability distribution

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Review of graph construction and graph learning in stock price prediction 9th

Review of graph construction and graph learning in stock pri...

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9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Wang, Yunong Qu, Yi Chen, Zhensong Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China School of Management and Engineering Capital University of Economics and Business Beijing100070 China

Precise prediction of stock prices leads to more profits and more effective risk prevention, which is of great significance to both investors and regulators. Recent years, various kinds of information not directly-relevant with stock prices have received more attention, such as texts, images or connections. These external information has the potential of reflecting or influencing fluctuations, and thus, given the utilization of advanced analyzing techniques, the forecasting performance of stock prices could be promoted substantially. For instance, graph neural network models have expanded into many other disciplines including stock price prediction, and exhibited impressive representation learning ability. However, in stock markets, well-defined graphs are rarely seen and how to formulate the graph structures needed remains a challenging problem. Towards this end, this article presents a comprehensive overview of graph construction and graph learning in stock price prediction, by reviewing the existing studies, summarizing its general paradigm, special cases and proposing possible prospects. Our research not only systematically reveals the feasible ways of constructing graphs in financial markets, but also provides insights for further implementations of graph learning models into stock prediction tasks. © 2022 The Authors. Published by Elsevier B.V.

关键词： Financial markets

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Controlled and collaborative presentation via tablet PCs for classroom and meeting room uses

Controlled and collaborative presentation via tablet PCs for...

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International Joint Conference on Computer Science and Software engineering (JCSSE)

作者： Prissadang Suta Pornchai Mongkolnam Wichai Eamsinvattana Data and Knowledge Engineering Laboratory King Mongkut's University of Technology Thonburi Bangkok Thailand

We propose a simple yet effective controlled and collaborative presentation system using tablet PCs for a classroom or meeting room use. The system does not require the Internet to be functioning, but simply needs a local Wi-Fi connection via an access point. This makes our system invaluably suitable for the classroom uses, especially in some rural parts of the world where the Internet accesses are impossible. It allows a presenter to synchronously change presentation slides of viewers in the control mode where the presenter has the control of a current page. The viewers, on the other hand, can get out of the control mode and be in the edit mode where they can add annotations or choose to view other pages asynchronously different from the presenter. The viewers could choose some or all of their annotations to be shared and shown to public through the presenter. The presenter could select and allow any annotations from the viewers to be shown on a projector's screen. This would help facilitate collaboration among the viewers. Each viewer can save the presenter's annotations, allowable other viewers' annotations and his annotations altogether in one file for a further review or later use. The system had been evaluated on three key aspects, including usefulness, user interface, and performance, by 26 participants. On the usefulness, 81 percent of the users agreed or strongly agreed with the system. On the user interface, only 56 percent agreed or strongly agreed, while 64 percent agreed or strongly agreed on the system performance.

关键词： Tablet computers Collaboration Browsers Internet Servers User interfaces Portable computers

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Factors Affecting Student's Intention to Choose IT Program

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Procedia Computer Science 2012年 13卷 60-67页

作者： Sunisa Sathapornvajana Bunthit Watanapa Requirements Engineering Laboratory (R-Lab) Data and Knowledge Engineering Laboratory (D-Lab) School of Information Technology King Mongkut's University of Technology Thonburi Bangkok 10140 Thailand

This paper proposes a two-fold study: (1) to find the factors affecting attitude of Thai students for choosing Information Technology (IT) program and (2) to investigate the existence of gender gap in behavioral intention. The study is based on the Theory of Reasoned Action (TRA) as a theoretical framework. The factors that may affect students’ behavioral intention to choose IT program are categorized into two dimensions: attitudes toward choosing IT program and subjective norm. The web-based questionnaire is employed to collect data from a sample of 67 local Thai Grade 12 students of both genders who have intention to study in IT undergraduate program at School of Information Technology (SIT), King Mongkut's University of Technology Thonburi (KMUTT). The result of statistical analysis shows that TRA is effective for explaining the behavioral intention. Male and female students hold the same set of attitudinal attributes when deciding to enter IT program, hence, an IT school shall implement common strategies to grasp intention from both genders. The most effective strategy to gain students intention is to build up the reputation of IT program.

关键词： IT program Gender differences Attitudes IT education Theory of reasoned action (TRA)

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Computing Degree of Association Based on Different Semantic Relationships

Computing Degree of Association Based on Different Semantic ...

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International Workshop on database and Expert Systems Applications

作者： Xuan Tian Xiaoyong Du Haihua Li School of Information Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing China

In domain ontologies, there is usually no weight assigned to the link between two concepts. This has been considered as one of main obstacles in using ontologies. Semantic Association (SA) is to depict the correlation of two concepts, and can be measured as the weight of the link. In this paper, we defined Degree of Association (DOA) to measure SA from a concept to its direct-related concept in domain ontology, and proposed a Language-Model-Based Method (LMBM) to compute DOA. Our idea comes from the intuition that the semantic relationship between two concepts implies certain semantic association of them. We took probabilistic model for computing DOA, and used Maximum Likelihood Estimation to estimate parameters. We tested the proposed method on two different domain ontologies, and applied it in experiments of semantic query expansion. Experimental results show the benefit of our approach and demonstrate the promising effectiveness over semantic query expansion.

关键词： Ontologies Information retrieval Direction of arrival estimation Parameter estimation data mining databases Expert systems Computer applications Laboratories data engineering

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AN EXTENDED MODEL FOR PROJECT PORTFOLIO SELECTION WITH PROJECT DIVISIBILITY AND INTERDEPENDENCY

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Journal of Systems Science and Systems engineering 2016年第1期25卷 119-138页

作者： Xingmei Li Shu-Cherng Fang Xiaoling Guo Zhibin Deng Jianxun Qi School of Economics and Management North China Electric Power University Beijing 102206 China Industrial and Systems Engineering Department North Carolina State University Raleigh NC 27695 USA College of Engineering andlnformation Technology University of Chinese Academy of Sciences Beijing100049 China School of Management University of Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China

In this paper, we develop an extended model for the project portfolio selection problem over a planning horizon with multiple time periods. The model incorporates the factors of project divisibility and interdependency at the same time for real-life applications. The project divisibility is considered as a strategy, not an unfortunate event as in the literature, in choosing the best execution schedule for the projects, and the classical concept of＂project interdependencies＂ among fully executed projects is then extended to the portions of executed projects. Additional constraints of reinvestment consideration, setup cost, cardinality restriction, precedence relationship and scheduling are also included in the model. For efficient computations, an equivalent mixed integer linear programming representation of the proposed model is derived. Numerical examples under four scenarios are presented to highlight the characteristics of the proposed model. In particular, the positive effects of project divisibility are shown for the first time.

关键词： Project management project portfolio selection problem project divisibility project interdependency

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Advances in Web and Network Technologies and Information Management 2009

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丛书名： Lecture Notes in Computer Science

2009年

作者： Lei Chen Chengfei Liu Xiao Zhang Shan Wang Darijus Strasunskas Stein L. Tomassen Jinghai Rao Wen-Syan Li K. Selçuk Candan Dickson K. W. Chiu Yi Zhuang

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Web Log Analysis in Genealogy System

Web Log Analysis in Genealogy System

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IEEE International Conference on Big knowledge (ICBK)

作者： Xiaojian Liu Yi Zhu Shengwei Ji Ministry of Education Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) China

ISBN: (数字)9781728181561

ISBN: (纸本)9781728181578

A large amount of log data is generated every moment in many real-world applications. System logs, mobile application logs, web logs etc., all of which contain rich information and can be analyzed for valuable information. At the same time, genealogy attracts more and more attention in recent decades, especially for Chinese. People utilize the genealogy system to seek roots, find source of family, build a family tree and so on. Due to the complexity of genealogy data and specific features of genealogy system, how to extract and analyze the valued genealogy information effectively is a huge challenge. Motivated by this, we propose a novel analysis method using web logs in genealogy system for drawing user profile and providing personalized recommendations. More specifically, firstly, all web logs are extracted from genealogy system based on the enhanced logs which record the behaviors and data of user. Secondly, the extracted logs are formatted for analysis, and we analyze the logs to extract various user-related attributes for drawing user profile. Finally, personalized recommendations like interested people and family tree are provided for each user in system. The high availability and effectiveness of our proposed method is verified on genealogy system-Huapu system.

关键词： data mining databases data visualization Tools Big data Feature extraction knowledge engineering

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