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IEEE Frontiers in Education Conference (FIE)

作者： Sekiya, Takayuki Matsuda, Yoshitatsu Yamaguchi, Kazunori Univ Tokyo Ctr Informat Technol 3-8-1 Komaba Tokyo Japan Seikei Univ Dept Comp & Informat Sci 3-3-1 Kichijojikitamachi Musashino Tokyo Japan Univ Tokyo Grad Sch Arts & Sci 3-8-1 Komaba Tokyo Japan

ISBN: (数字)9781665462440

ISBN: (纸本)9781665462440

This Research Full Paper proposes a new method to collect course syllabi. A syllabus is essential information about a course in a university. Students grasp the topics covered by a course through its syllabus, and faculties understand the curriculum offered by the university by a set of syllabi. Thus, a syllabus helps to analyze educational activities. Our previous work proposed a hybrid method that combines Google API as a general keyword search engine and linear support vector machine (SVM) as content-based classification models. We could find more computer science (CS) syllabus pages than using each method alone by employing the hybrid method. This paper extends the hybrid method for finding a directory page with many links to the syllabus pages. We use the hybrid method to collect candidate directory pages and select the true directory pages from the candidates by the three heuristics: (1) Hyperlink-Induced Topic Search (hits) score. (2) URL pattern, and (3) Content word. (1) hits score: The relation between directory pages and syllabus pages resembles the relation between the hits algorithm's hubs and authorities. We use hub scores to select directory pages. (2) URL pattern: Pages with similar contents and roles share a part of their URLs. We exploit this observation to select syllabus pages. (3) Content word: We expect a syllabus page to include words of the Body of Knowledge (BOK) 'Computing Science Curricula CS2013,' released by the ACM and IEEE Computer Society. We use the words extracted from the CS2013 BOK to measure how each candidate syllabus page is related to CS2013. With these three heuristics, we achieved 32%, the percentage of CS syllabus pages included on candidate pages.

关键词： Computer Science Curricula Syllabus Analysis Web Crawling Linear SVM hits algorithm

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Remote user experience data collection method for social networks under cloud visualisation layout

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL 2024年第2-3期45卷 120页

作者： Zhang, Yingchun Henan Logist Vocat Coll Coll Logist Informat Engn Zhengzhou 450012 Henan Peoples R China

A remote user experience data collection method for social networks based on cloud visualisation layout is proposed to address issues such as low efficiency in data collection. Firstly, determine the type of experience for remote users and calculate the weight to determine the key elements of the user experience;secondly, a directed graph structured social network is introduced to obtain experiential features, and interference is reduced through normalisation. hits algorithm is used to analyse experiential features;then, the experience data features are visualised and transformed, using TF-IDF algorithm to filter remote user experience features, and designing cloud visualisation layout. At the same time, consistency of difference values is processed, and all experience data is annotated;finally, the annotation objective function and constraint conditions are introduced to achieve the design of the collection method. The research results indicate that the proposed method can efficiently collect experience data and has certain feasibility.

关键词： cloud visualisation layout social networks remote users experience data collection hits algorithm

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Analysis of Leading Communities Contributing to arXiv Information Distribution on Twitter

Analysis of Leading Communities Contributing to arXiv Inform...

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IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

作者： Shimada, Kyosuke Kazama, Kazuhiro Yoshida, Mitsuo Ohmukai, Ikki Sato, Sho Wakayama Univ Wakayama Japan Univ Tsukuba Bunkyo Ku Tokyo Japan Doshisha Univ Kyoto Kyoto Japan

ISBN: (纸本)9781450391153

To analyze the impact that arXiv is having on the world, in this paper we propose an arXiv information distribution model on Twitter, which has a three-layer structure: arXiv papers, information spreaders, and information collectors. First, we use the hits algorithm to analyze the arXiv information diffusion network with users as nodes, which is created from three types of behavior on Twitter regarding arXiv papers: tweeting, retweeting, and liking. Next, we extract communities from the network of information spreaders with positive authority and hub degrees using the Louvain method, and analyze the relationship and roles of information spreaders in communities using research field, linguistic, and temporal characteristics. From our analysis using the tweet and arXiv datasets, we found that information about arXiv papers circulates on Twitter from information spreaders to information collectors, and that multiple communities of information spreaders are formed according to their research fields. It was also found that different communities were formed in the same research field, depending on the research or cultural background of the information spreaders. We were able to identify two types of key persons: information spreaders who lead the relevant field in the international community and information spreaders who bridge the regional and international communities using English and their native language. In addition, we found that it takes some time to gain trust as an information spreader.

关键词： Twitter arXiv academic information distribution hits algorithm betweenness centrality

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The attack efficiency of PageRank and hits algorithms on complex networks

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INTERNATIONAL JOURNAL OF EMBEDDED SYSTEMS 2019年第3期11卷 306-314页

作者： Su, Yangqian Yi, Yunfei Qin, Jun Guangxi Teachers Educ Univ Coll Comp & Informat Engn Nanning 530023 Peoples R China Hechi Univ Coll Comp & Informat Engn Yizhou 546300 Peoples R China South Cent Univ Nationalities Coll Comp Sci Wuhan 430074 Hubei Peoples R China

With the growing scale of networks, network attack strategies with high attack efficiency and computational efficiency are becoming more and more important. Various attack strategies with various sorting methods have been proposed. However most of them neglected the computational efficiency. Inspired by the high computational efficiency of PageRank and hits algorithms that used in web pages network, this paper introduces those two algorithms to the network attack separately and explores the feasibility of those two new strategies. The initial experiments choose degree and BC attack as the contrast group, and compare the attack efficiency in six virtual networks. The results indicate that considering the computational efficiency and attack efficiency simultaneously, PageRank strategy has a better attack performance than other compared strategies. Initial discussions about the results are also given.

关键词： PageRank algorithm hits algorithm attack strategy

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TGSM: Towards trustworthy group-based service management for social IoT

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INTERNET OF THINGS 2021年 13卷

作者： Farahbakhsh, Bahareh Fanian, Ali Manshaei, Mohammad Hossein Isfahan Univ Technol Dept Elect & Comp Engn Esfahan *** Iran

The Social Internet of Things has been introduced as a social oriented approach to deal with IoT challenges. A service discovery process is also transformed by this paradigm. Since the Social Internet of Things includes millions of services across the network, the question arises that to what extent can we trust service providers? The appropriate selection of trustworthy service provider plays a key role in successful deployment of the SIoT. In this work, we address this issue by proposing a trustworthy group-based service management model (TGSM). The proposed discovery and selection process of an appropriate service provider relies on both trustworthiness measurement and performance assessment. In the trustworthiness measurement case, a punishment mechanism is adopted in trustworthiness evaluation to deal with objects' selfish behavior. Likewise, we employed the hits algorithm to propose a global dynamic reputation evaluation approach. We propose a service-based grouping approach as a novel architecture for SIoT network. We also consider the dynamic evolving of social relationships among the SIoT devices. Our SIoT paradigm, due to its intrinsically multilayered nature, is modeled upon a multiplex network. In the performance measurement case, some metrics are used to asses objects' performance. To evaluate the proposed trust model, we extend the CRAWDAD dataset, and the objects in the dataset are categorized into five types. The simulation results show that the proportions of four selfish types of objects are dominated by completely trustworthy objects, which proves the effectiveness of our proposed TGSM model. Moreover, the results demonstrate hits centrality measurement's effectiveness, which leads the proportion of trustworthy service providers to nearly double in comparison with degree and eigenvector centrality in this context. (C) 2020 Published by Elsevier B.V.

关键词： Social internet of things Trust Punishment mechanism hits algorithm Service based grouping Multiplex network

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Reputation Evaluation with Malicious Feedback Prevention Using a hits-Based Model 26

Reputation Evaluation with Malicious Feedback Prevention Usi...

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IEEE International Conference on Web Services (IEEE ICWS) part of the IEEE World Congress on Services

作者： Tibermacine, Okba Tibermacine, Chouki Kerdoudi, Mohamed Lamine Biskra Univ Biskra Algeria Jouf Univ Sakakah Saudi Arabia CNRS LIRMM Paris France Montpellier Univ Montpellier France Biskra Univ Comp Sci Dept Biskra Algeria

ISBN: (纸本)9781728127170

The reputation of web services is calculated by aggregating user feedback ratings. Though reputation is a subjective metric, it can be considered as a good indicator about services Quality of Experience, and henceforth, it can be used for recommending services in an open ecosystem. In this work, we propose a three-phase process for evaluating web service reputation by aggregating user feedback ratings. The relationship between users and services is modeled as a bipartite graph where an adapted hits (Hypertext Induced Topic Search) algorithm is employed to distinguish between honest and malicious users in Phase I. Then, this model is used to evaluate, in Phase III, the reputation of web services from user ratings after punishing malicious users in Phase II. An experiment on a dataset of real Web services was conducted to validate the effectiveness of the proposed model in evaluating Web service reputation.

关键词： Web services Reputation hits algorithm User credibility evaluation

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User's Centrality Analysis for Home Location Estimation 19

User's Centrality Analysis for Home Location Estimation

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19th IEEE/WIC/ACM International Conference on Web Intelligence (WI)

作者： Hironaka, Shiori Yoshida, Mitsuo Umemura, Kyoji Toyohashi Univ Technol Toyohashi Aichi Japan

ISBN: (纸本)9781450369886

User attributes, such as home location, are useful for many applications. Many researchers have been tackling how to estimate users' home locations using relationships among users. It is known that the home locations of certain users, such as celebrities, are hard to estimate using relationships. However, because estimating the home locations of all celebrities is not actually hard, it is important to clarify the characteristics of users whose home locations are hard to estimate. We analyze whether centralities, which represent users' characteristics, and the tendency to have the same home locations as friends are related. The results indicate that PageRank and hits scores are related to whether users have the same home location as friends, and that users with higher hits scores have the same home location as their friends less often. This result indicates that there are two types of users whose home locations are difficult to estimate: hub users who follow many celebrities and authority users who are celebrities.

关键词： Home location estimation Centrality PageRank hits algorithm

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Finding high quality documents through link and click graphs 7

Finding high quality documents through link and click graphs

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7th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)

作者： Yu, Linfeng Iwaihara, Mizuho Waseda Univ Grad Sch Informat Prod & Syst Fukuoka Fukuoka Japan

ISBN: (纸本)9781538674475

Link graphs of web pages have been utilized to evaluate importance of each page. Existing link analysis algorithms, including hits and PageRank, exploit static link connectivity between pages. On the other hand, service providers often record HTTP requests that contain the resource and referrer of each request, from which we can construct a click graph that has edge weights representing the times of clicks on each link, or link traffic. Click graphs reflect users' choices of interesting links, thus the graphs are useful for evaluating importance of pages. However, clicks are often skewed onto highly popular links, so that click graphs only could not properly evaluate less clicked pages. In this paper, we propose an algorithm called click count-weighted hits algorithm, which integrates hits algorithm with click graphs, for finding high quality documents. Our evaluations on finding featured articles of English Wikipedia show that our click count-weighted hits algorithm shows better performance on a large Wikipedia corpus than algorithms that utilize link graphs or click graphs only.

关键词： link analysis document ranking click graph hits algorithm quality Wikipedia

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Measuring Evolvability and Accessibility using the Hyperlink-Induced Topic Search algorithm 18

Measuring Evolvability and Accessibility using the Hyperlink...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Nickerson, Kyle L. Chen, Yuanzhu Wang, Feng Hu, Ting Mem Univ Dept Comp Sci St John NF Canada Wuhan Univ Sch Comp Sci Wuhan Hubei Peoples R China

ISBN: (纸本)9781450356183

The redundant mapping from genotype to phenotype is common in evolutionary algorithms, where multiple genotypes can map to the same phenotype. Such a redundancy has been suggested to make an evolutionary system robust as well as evolvable. However, the impact of the redundant genotype-to-phenotype mapping and its resulted robustness and evolvability have not been well characterized quantitatively. In this article, we used a Boolean linear genetic programming system to construct a weighted and directed pheno-type network, where vertices are phenotypes and a weighted link represents the number of possible point mutations that can transition genotypes from one phenotype to another. The direction of the links ensures moving from less fit phenotypes to fitter or equally fit ones. We used two fitness functions to investigate how it influences the network structure. Then we employed the Hyperlink-Induced Topic Search (hits) algorithm to quantitatively characterize the evolvability and accessibility of phenotypes in the network. We found more robust phenotypes are both more evolvable and accessible. Our results help elucidate the effects of redundant mapping and the relationship of robustness, evolvability, and accessibility.

关键词： Genotype-to-phenotype mapping phenotype network redundancy hits algorithm evolvability accessibility

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Construction and Analysis of Opinion Leader Network in Micro-blog Topic Communication

Construction and Analysis of Opinion Leader Network in Micro...

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作者： Zhang Dan Li Xin Xiong Tao He Yue Business School of Sichuan University

[Purpose/Significance] The rapid growth of micro-blog users and the popularity of mobile Internet make Micro-blog an increasingly important channel for information dissemination. As a result of shortening the distance between ordinary users and opinion leaders, opinion leaders on the micro-blog platform have become more prominent. Therefore, it is very important to identify opinion leaders in micro-blog and study their role in the process of information dissemination. [Method/Process] This article first identifies opinion leaders through the improved hits algorithm;Then build opinion leader network to analyze the role of opinion leader in the process of information dissemination;Finally, using emotion recognition technology, the ability of opinion leaders to infect other users is analyzed in depth. [Result/Conclusion] The study found that the role of media users as a source of information was weakened in micro-blog platforms, but that media opinion leaders were involved in topics and information dissemination capabilities were stronger. The authority of users is more related to the quality of information, and many users with fewer fans can also become opinion leaders. In terms of degree distribution, no user can have a high monopoly on authoritative information sources. But the channel of information dissemination is more concentrated, and the channel of communication of a topic is often controlled by a few users. Through emotional recognition analysis of the appeal of opinion leaders, it was found that other users tend to be more inclined to non-negative emotions when forwarding opinion leaders 'microblogs. The appeal of opinion leaders is generally strong.

关键词： Micro-blog topic Information dissemination hits algorithm Opinion leader network Emotion recognition

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