Thematische Bibliographien / Data mining – social aspects / Dissertationen
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Dissertationen zum Thema „Data mining – social aspects“

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Veröffentlicht am 26. Juli 2024
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1

Chen, Weidong. "Discovering communities by information diffusion and link density propagation." HKBU Institutional Repository, 2012. https://repository.hkbu.edu.hk/etd_ra/1422.

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Nguyen, Ngoc Buu Cat. "Data Mining in Knowledge Management Processes: Developing an Implementing Framework." Thesis, Umeå universitet, Institutionen för informatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149668.

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Analyzing a huge amount of data becomes a tricky challenge and an opportunity for data miners and businessmen today. Knowledge management processes can deal with big knowledge source to find tacit intelligence making businesses more agile and effective. Data mining is a powerful tool working with big data to create capabilities of forecasting and analysis. Yet there is a lack of research on where and how data mining can add value in knowledge management processes in organizations to maximize valuable knowledge for innovation and business management. The knowledge management processes of a psyc
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Yang, Shuang-Hong. "Predictive models for online human activities." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43689.

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The availability and scale of user generated data in online systems raises tremendous challenges and opportunities to analytic study of human activities. Effective modeling of online human activities is not only fundamental to the understanding of human behavior, but also important to the online industry. This thesis focuses on developing models and algorithms to predict human activities in online systems and to improve the algorithmic design of personalized/socialized systems (e.g., recommendation, advertising, Web search systems). We are particularly interested in three types of online user
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Cai, Zhongming. "Technical aspects of data mining." Thesis, Cardiff University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.395784.

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Eriksson, Jesper, and Samuel Björeqvist. "Datadriven Innovation : En komparativ studie om dataanalysmetoder och verktyg för små företag." Thesis, Umeå universitet, Institutionen för informatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149865.

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Businesses today are often operating in a highly competitive environment where information is a noticeably valuable asset. Businesses are therefore in need of powerful tools for extracting actionable business knowledge. Research show that SME companies are lagging behind large companies in the use of data analytics; even though they know the potential benefits. We want to study and compare different tools for data analytics and how they can be used by small companies. Our research questions are therefore: what analytical tools are today available on the market, and what are their possibilities
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Wang, Guan. "Graph-Based Approach on Social Data Mining." Thesis, University of Illinois at Chicago, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3668648.

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<p> Powered by big data infrastructures, social network platforms are gathering data on many aspects of our daily lives. The online social world is reflecting our physical world in an increasingly detailed way by collecting people's individual biographies and their various of relationships with other people. Although massive amount of social data has been gathered, an urgent challenge remain unsolved, which is to discover meaningful knowledge that can empower the social platforms to really understand their users from different perspectives. </p><p> Motivated by this trend, my research addres
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Ip, Lai Cheng. "Mining on social network community for marketing." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950661.

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Costa, Alceu Ferraz. "Mining User Activity Data in Social Media Services." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-11092017-151000/.

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Social media services have a growing impact in our society. Individuals often rely on social media to get their news, decide which products to buy or to communicate with their friends. As consequence of the widespread adoption of social media, a large volume of data on how users behave is created every day and stored into large databases. Learning how to analyze and extract useful knowledge from this data has a number of potential applications. For instance, a deeper understanding on how legitimate users interact with social media services could be explored to design more accurate spam and fra
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Meneghello, James. "A scalable framework for integrated social data mining." Thesis, Meneghello, James (2017) A scalable framework for integrated social data mining. PhD thesis, Murdoch University, 2017. https://researchrepository.murdoch.edu.au/id/eprint/36690/.

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Social Networking Sites (SNS) are ubiquitous within modern society, forming communications networks that span across cultural and geographical boundaries. The information posted to these sites provide useful insights into individuals, but can also provide a wealth of information that can be used for further analysis into the surrounding environment. Three main challenges limit the use of this information in applications: the quantity of data is often unmanageable, there is a significant amount of data unavailable for use due to a lack of generic interfaces for access, and there is difficulty i
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Alsaleh, Slah. "Recommending people in social networks using data mining." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/61736/1/Slah_Alsaleh_Thesis.pdf.

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This thesis improves the process of recommending people to people in social networks using new clustering algorithms and ranking methods. The proposed system and methods are evaluated on the data collected from a real life social network. The empirical analysis of this research confirms that the proposed system and methods achieved improvements in the accuracy and efficiency of matching and recommending people, and overcome some of the problems that social matching systems usually suffer.
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Isah, Haruna. "Social Data Mining for Crime Intelligence: Contributions to Social Data Quality Assessment and Prediction Methods." Thesis, University of Bradford, 2017. http://hdl.handle.net/10454/16066.

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With the advancement of the Internet and related technologies, many traditional crimes have made the leap to digital environments. The successes of data mining in a wide variety of disciplines have given birth to crime analysis. Traditional crime analysis is mainly focused on understanding crime patterns, however, it is unsuitable for identifying and monitoring emerging crimes. The true nature of crime remains buried in unstructured content that represents the hidden story behind the data. User feedback leaves valuable traces that can be utilised to measure the quality of various aspects of pr
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Liu, Lian. "PRIVACY PRESERVING DATA MINING FOR NUMERICAL MATRICES, SOCIAL NETWORKS, AND BIG DATA." UKnowledge, 2015. http://uknowledge.uky.edu/cs_etds/31.

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Motivated by increasing public awareness of possible abuse of confidential information, which is considered as a significant hindrance to the development of e-society, medical and financial markets, a privacy preserving data mining framework is presented so that data owners can carefully process data in order to preserve confidential information and guarantee information functionality within an acceptable boundary. First, among many privacy-preserving methodologies, as a group of popular techniques for achieving a balance between data utility and information privacy, a class of data perturbati
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Wang, Yan. "Student Modeling From Different Aspects." Digital WPI, 2016. https://digitalcommons.wpi.edu/etd-theses/205.

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With the wide usage of online tutoring systems, researchers become interested in mining data from logged files of these systems, so as to get better understanding of students. Varieties of aspects of students’ learning have become focus of studies, such as modeling students’ mastery status and affects. On the other hand, Randomized Controlled Trial (RCT), which is an unbiased method for getting insights of education, finds its way in Intelligent Tutoring System. Firstly, people are curious about what kind of settings would work better. Secondly, such a tutoring system, with lots of student
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Bergami, Giacomo. "Hypergraph Mining for Social Networks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/7106/.

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Nowadays, more and more data is collected in large amounts, such that the need of studying it both efficiently and profitably is arising; we want to acheive new and significant informations that weren't known before the analysis. At this time many graph mining algorithms have been developed, but an algebra that could systematically define how to generalize such operations is missing. In order to propel the development of a such automatic analysis of an algebra, We propose for the first time (to the best of my knowledge) some primitive operators that may be the prelude to the systemati
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Nhlabano, Valentine Velaphi. "Fast Data Analysis Methods For Social Media Data." Diss., University of Pretoria, 2018. http://hdl.handle.net/2263/72546.

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The advent of Web 2.0 technologies which supports the creation and publishing of various social media content in a collaborative and participatory way by all users in the form of user generated content and social networks has led to the creation of vast amounts of structured, semi-structured and unstructured data. The sudden rise of social media has led to their wide adoption by organisations of various sizes worldwide in order to take advantage of this new way of communication and engaging with their stakeholders in ways that was unimaginable before. Data generated from social media is highly
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Li, Jingxuan. "Mining the Online Social Network Data: Influence, Summarization, and Organization." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1241.

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Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation fo
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Jiang, Fan. "Efficient frequent pattern mining from big data and its applications." Springer, 2014. http://hdl.handle.net/1993/32083.

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Frequent pattern mining is an important research areas in data mining. Since its introduction, it has drawn attention of many researchers. Consequently, many algorithms have been proposed. Popular algorithms include level-wise Apriori based algorithms, tree based algorithms, and hyperlinked array structure based algorithms. While these algorithms are popular and beneficial due to some nice properties, they also suffer from some drawbacks such as multiple database scans, recursive tree constructions, or multiple hyperlink adjustments. In the current era of big data, high volumes of a wide varie
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Chen, Nai Chun. "Urban data mining : social media data analysis as a complementary tool for urban design." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106414.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 70-71).<br>The emergence of "big data" has resulted in a large amount of information documenting daily events, perceptions, thoughts, and emotions of citizens, all annotated with the location and time that they were recorded. This data presents an unprecedented opportunity to help identify and solve urban problems. This thesis aimed to explore the potential of machine learning and data mining in finding patterns in "big" u
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Akay, Altug. "A Novel Method to Intelligently Mine Social Media to Assess Consumer Sentiment of Pharmaceutical Drugs." Doctoral thesis, KTH, Systemsäkerhet och organisation, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-203119.

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This thesis focuses on the development of novel data mining techniques that convert user interactions in social media networks into readable data that would benefit users, companies, and governments. The readable data can either warn of dangerous side effects of pharmaceutical drugs or improve intervention strategies. A weighted model enabled us to represent user activity in the network, that allowed us to reflect user sentiment of a pharmaceutical drug and/or service. The result is an accurate representation of user sentiment. This approach, when modified for specific diseases, drugs, and ser
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Goyal, Amit. "Social influence and its applications : an algorithmic and data mining study." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/43935.

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Social influence occurs when one's actions are affected by others. If leveraged carefully, social influence can be exploited in many applications like viral marketing (or targeted advertising in general), recommender systems, social network analysis, events detection, experts finding, link prediction, ranking of feeds etc. One of the fundamental problems in this fascinating field is the problem of influence maximization, primarily motivated by the application of viral marketing. The objective is to identify a small set of users in a social network, who when convinced to adopt a product will i
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Pochet, Gilberto Flores. "Analysis of online virtual environments using Data Mining and social networks." reponame:Repositório Institucional da UFABC, 2015.

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Corley, Courtney D. Mikler Armin. "Social network simulation and mining social media to advance epidemiology." [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/permalink/meta-dc-11053.

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GRIMAUDO, LUIGI. "Data Mining Algorithms for Internet Data: from Transport to Application Layer." Doctoral thesis, Politecnico di Torino, 2014. http://hdl.handle.net/11583/2537089.

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Nowadays we live in a data-driven world. Advances in data generation, collection and storage technology have enabled organizations to gather data sets of massive size. Data mining is a discipline that blends traditional data analysis methods with sophisticated algorithms to handle the challenges posed by these new types of data sets. The Internet is a complex and dynamic system with new protocols and applications that arise at a constant pace. All these characteristics designate the Internet a valuable and challenging data source and application domain for a research activity, both looking at
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Mengwe, Moses Seargent. "Towards social impact assessment of copper-nickel mining in Botswana." Thesis, Nelson Mandela Metropolitan University, 2010. http://hdl.handle.net/10948/1443.

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This research study is more of an initiative towards Social Impact Assessment of copper-nickel mining in Botswana. The specific objectives of the study were centred on the assessment of the social impacts of copper-nickel mining in Botswana from the initial mining stage of exploration, surveying and mine site development to mine closure. The study was carried out under the broad hypotheses that mining influences population movement that impact on areas of mining; mining activities have both economic benefits and deleterious social impacts on the local communities found in the areas where minin
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ATTANASIO, ANTONIO. "Mining Heterogeneous Urban Data at Multiple Granularity Layers." Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2709888.

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The recent development of urban areas and of the new advanced services supported by digital technologies has generated big challenges for people and city administrators, like air pollution, high energy consumption, traffic congestion, management of public events. Moreover, understanding the perception of citizens about the provided services and other relevant topics can help devising targeted actions in the management. With the large diffusion of sensing technologies and user devices, the capability to generate data of public interest within the urban area has rapidly grown. For instance, diff
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Degnen, Cathrine. "Mining experience : the ageing self, narrative, and social memory in Dodworth, England." Thesis, McGill University, 2003. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=19487.

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In response to the anthropological literature on old age and ageing that remains largely isolated from more contemporary anthropological theory, this thesis re-focuses anthropological attention on the experiences of ageing. Towards this end, I examine the way macro- (history, politics, economics) and micro-level processes (social relations, intergenerational relations, local contexts, individual histories) intersect to frame the cultural construction of old age, personal experiences of "being old", and the self. A central point of intersection between these processes comes from the recent hist
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Fan, Xiaoguang, and 樊晓光. "Study of social-network-based information propagation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50899600.

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Information propagation has attracted increasing attention from sociologists, marketing researchers and Information Technology entrepreneurs. With the rapid developments in online and mobile social applications like Facebook, Twitter, and LinkedIn, large-scale, high-speed and instantaneous information dissemination becomes possible, spawning tremendous opportunities for electronic commerce. It is non-trivial to make an accurate analysis on how information is propagated due to the uncertainty of human behavior and the complexity of the social environment. This dissertation is concerned with ex
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Jonathan, Joan. "Prediction of Factors Influencing Rats Tuberculosis Detection Performance Using Data Mining Techniques." Thesis, Uppsala universitet, Institutionen för informatik och media, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385471.

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This thesis aimed to predict the factors that influence rats TB detection performance using data mining techniques. A rats TB detection performance dataset was given from APOPO TB training and research center in Morogoro, Tanzania. After data preprocessing, the size of the dataset was 471,133 rats TB detection performance observations and a sample size of 4 female rats. However, in the analysis, only 200,000 data observations were used. Based on the CRISP-DM methodology, this thesis used R language as a data mining tool to analyze the given data. To build the predictive model the classificatio
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Epstein, Greg. "Harnessing User Data to Improve Facebook Features." Thesis, Boston College, 2010. http://hdl.handle.net/2345/1211.

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Thesis advisor: Sergio Alvarez<br>The recent explosion of online social networking through sites like Twitter, MySpace, Facebook has millions of users spending hours a day sorting through information on their friends, coworkers and other contacts. These networks also house massive amounts of user activity information that is often used for advertising purposes but can be utilized for other activities as well. Facebook, now the most popular in terms of registered users, active users and page rank, has a sparse offering of built-in filtering and predictive tools such as ``suggesting a friend'' o
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Hassanzadeh, Reza. "Anomaly detection in online social networks : using data-mining techniques and fuzzy logic." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/78679/1/Reza_Hassanzadeh_Thesis.pdf.

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This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.
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Malliaros, Fragkiskos. "Mining Social and Information Networks: Dynamics and Applications." Palaiseau, Ecole polytechnique, 2015. https://theses.hal.science/tel-01245134/document.

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Networks (or graphs) have become ubiquitous as data from diverse disciplines can naturally be mapped to graph structures. The problem of extracting meaningful information from large scale graph data in an efficient and effective way has become crucial and challenging with several important applications and towards this end, graph mining and analysis methods constitute prominent tools. This dissertation contributes models, tools and observations to problems that arise in the area of mining social and information networks. We built upon computationally efficient graph mining methods in order to:
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Casas, Roma Jordi. "Privacy-preserving and data utility in graph mining." Doctoral thesis, Universitat Autònoma de Barcelona, 2014. http://hdl.handle.net/10803/285566.

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En los últimos años, ha sido puesto a disposición del público una gran cantidad de los datos con formato de grafo. Incrustado en estos datos hay información privada acerca de los usuarios que aparecen en ella. Por lo tanto, los propietarios de datos deben respetar la privacidad de los usuarios antes de liberar los conjuntos de datos a terceros. En este escenario, los procesos de anonimización se convierten en un proceso muy importante. Sin embargo, los procesos de anonimización introducen, generalmente, algún tipo de ruido en los datos anónimos y también en sus resultados en procesos de mine
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Straub, Kayla Marie. "Data Mining Academic Emails to Model Employee Behaviors and Analyze Organizational Structure." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71320.

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Email correspondence has become the predominant method of communication for businesses. If not for the inherent privacy concerns, this electronically searchable data could be used to better understand how employees interact. After the Enron dataset was made available, researchers were able to provide great insight into employee behaviors based on the available data despite the many challenges with that dataset. The work in this thesis demonstrates a suite of methods to an appropriately anonymized academic email dataset created from volunteers' email metadata. This new dataset, from an int
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Velichety, Srikar, and Srikar Velichety. "Essays on Data Driven Insights from Crowd Sourcing, Social Media and Social Networks." Diss., The University of Arizona, 2016. http://hdl.handle.net/10150/620677.

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The beginning of this decade has seen a phenomenal raise in the amount of data generated in the world. While this increase provides us with opportunities to understand various aspects of human behavior and mechanisms behind new phenomena, the technologies, statistical techniques and theories required to gain an in depth and comprehensive understanding haven't progressed at an equal pace. As little as 5 years back, we used to deal with problems where there is insufficient prior social science or economic theory and the interest is only in prediction of the outcome or where there is an appropri
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Spomer, Judith E. "Latent semantic analysis and classification modeling in applications for social movement theory /." Abstract Full Text (HTML) Full Text (PDF), 2008. http://eprints.ccsu.edu/archive/00000552/02/1996FT.htm.

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Thesis (M.S.) -- Central Connecticut State University, 2008.<br>Thesis advisor: Roger Bilisoly. "... in partial fulfillment of the requirements for the degree of Master of Science in Data Mining." Includes bibliographical references (leaves 122-127). Also available via the World Wide Web.
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Rossi, Maria. "Graph Mining for Influence Maximization in Social Networks." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLX083/document.

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La science moderne des graphes est apparue ces dernières années comme un domaine d'intérêt et a apporté des progrès significatifs à notre connaissance des réseaux. Jusqu'à récemment, les algorithmes d'exploration de données existants étaient destinés à des données structurées / relationnelles, alors que de nombreux ensembles de données nécessitent une représentation graphique, comme les réseaux sociaux, les réseaux générés par des données textuelles, les structures protéiques 3D ou encore les composés chimiques. Il est donc crucial de pouvoir extraire des informations pertinantes à partir de c
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Soni, Swapnil. "Domain-Specific Document Retrieval Framework for Near Real-time Social Health Data." Wright State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1440954750.

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MY, DO TRA. "Apply data mining to segment retail market based on purchasing portfolios." Thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-20774.

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Market segmentation is becoming very familiar and essential to every marketer in the process of designing and implementing an effective target-marketing strategy. It is confirmed in the grocery retail industry about the importance of appropriate market segmentation. In this industry, customer purchasing behavior needs to be acknowledged not only in specific products, but also the interaction among the whole range of products. Therefore, the motivation for this thesis is to discover a segmentation based on this purchasing behavior among whole range of products, which is called purchasing patter
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Zulfiqar, Omer. "Detecting Public Transit Service Disruptions Using Social Media Mining and Graph Convolution." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/103745.

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In recent years we have seen an increase in the number of public transit service disruptions due to aging infrastructure, system failures and the regular need for maintenance. With the fleeting growth in the usage of these transit networks there has been an increase in the need for the timely detection of such disruptions. Any types of disruptions in these transit networks can lead to delays which can have major implications on the daily passengers. Most current disruption detection systems either do not operate in real-time or lack transit network coverage. The theme of this thesis was to lev
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Michel, Pablo Anaxágoras. "Análise explorátoria de dados sócio-econômicos de vestibulandos." Florianópolis, SC, 2002. http://repositorio.ufsc.br/xmlui/handle/123456789/83690.

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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Produção.<br>Made available in DSpace on 2012-10-20T02:25:29Z (GMT). No. of bitstreams: 0<br>Ao longo dos anos, as mais variadas organizações acumularam milhares de informações que ajudaram as empresas a evoluir e conquistar mercado, permitindo que os administradores, baseados nelas, de diferentes formas, tomassem decisões. Novas e avançadas ferramentas automatizadas de apoio a decisão têm sido desenvolvidas para auxiliar o administrador a decidir os rumos de seu negó
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Corley, Courtney David. "Social Network Simulation and Mining Social Media to Advance Epidemiology." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc11053/.

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Traditional Public Health decision-support can benefit from the Web and social media revolution. This dissertation presents approaches to mining social media benefiting public health epidemiology. Through discovery and analysis of trends in Influenza related blogs, a correlation to Centers for Disease Control and Prevention (CDC) influenza-like-illness patient reporting at sentinel health-care providers is verified. A second approach considers personal beliefs of vaccination in social media. A vaccine for human papillomavirus (HPV) was approved by the Food and Drug Administration in May 2006.
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Torres, Alvarez Hernán. "Mineral exploration, junior mining companies and aspects to be considered for its promotion." IUS ET VERITAS, 2016. http://repositorio.pucp.edu.pe/index/handle/123456789/122605.

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The author makes an analysis of the measures to be taken into account to promote mining activities, with special emphasis in the area of exploration as the main activity in the mining industry. Therefore, the present article focuses on everything that made such activity from its main actors to the considerations to take into account in its regulation and the effectiveness of it. Finally the author presents his conclusions focusing on the importance of generating investment and therefore expedition to implement the best mechanisms in the mining sector.<br>El autor hace un análisis acerca de las
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Deller, Yannick. "Raw Data for Peace and Security - The Extraction and Mining of People's Behaviour." Thesis, Malmö universitet, Fakulteten för kultur och samhälle (KS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-22599.

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In 2015, the United Nations Global Pulse launched an experimentation process assessing the viability of big data and artificial intelligence analysis to support peace and security. The proposition of using such analysis, and thereby creating early warning systems based on real-time monitoring, warrants a critical assessment. This thesis engages in an explanatory critique of the discursive (re-)definitions of peace and security as well as big data and artificial intelligence in the United Nations Global Pulse Lab Kampala report Experimenting with Big Data and Artificial Intelligence to Support
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Kumar, Arun. "Ground control ramifications and economic impact of retreat mining on room and pillar coal mines." Diss., Virginia Polytechnic Institute and State University, 1986. http://hdl.handle.net/10919/49815.

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As the coal reserves at shallow depths become exhausted companies have to develop deeper deposits and increase percentage extraction to maintain production levels. Total extraction for room and pillar mines can only be achieved by pillar extraction. The unsupported roof increases during pillar extraction and hence the cost of ground control also increases. Nevertheless, pillar extraction where possible has many potential advantages such as decreased operating cost, increased utilization of reserves, and extended life of the mine. There are several variables such as depth, mining height, rock s
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Franzke, Maximilian [Verfasser], and Matthias [Akademischer Betreuer] Renz. "Querying and mining heterogeneous spatial, social, and temporal data / Maximilian Franzke ; Betreuer: Matthias Renz." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2019. http://d-nb.info/1190563630/34.

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"Algorithmic aspects of social network mining." 2013. http://library.cuhk.edu.hk/record=b5884351.

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Li, Ronghua = 社会网络挖掘的算法问题研究 / 李荣华.<br>Thesis (Ph.D.)--Chinese University of Hong Kong, 2013.<br>Includes bibliographical references (leaves 157-171).<br>Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.<br>Abstract also in Chinese.<br>Li, Ronghua = She hui wang luo wa jue de suan fa wen ti yan jiu / Li Ronghua.
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Miskelly, Kenna Jill. "Exploring ethical issues in data mining: the role of collective privacy." Thesis, 2006. http://hdl.handle.net/1828/2302.

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Data mining and other information technologies cause ethical concerns when they are used to categorize and discriminate. Even though there is an intuitive connection between privacy and personal information, it is hard to conceptualize the troubling issues raised by certain data mining applications in terms of privacy. This is largely due to the emphasis that traditional privacy definitions place on the value and protection that privacy provides to the individual. A notion of "collective privacy" emphasizes the broader social importance of privacy and provides philosophical clarity to the priv
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Nkosi, Lolah. "Social impact of mining." Thesis, 2015. http://hdl.handle.net/10210/13886.

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LL.M. (International Law)<br>Mining is an activity which contributes greatly and positively to a country’s economic development by creating job opportunities, development of roads, health care centres and educational facilities. However, mining in certain instances can also have a long lasting negative environmental and social impact on communities. The focus of this dissertation will be to address those instances where mining has a negative social impact on the communities where such mining projects are taking place. The negative social impact of mining in certain cases is regarded as a unive
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Sigodi, Mzontsundu Gugulethu. "Corporate social investment by mining companies." Thesis, 2014. http://hdl.handle.net/10210/11865.

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M.Com. (Business Management)<br>Corporate social investment (CSI) does not have a universal definition, but corporations tend to interpret it according to the extent of their activity in community social programmes of development. It is of particular importance in South Africa given the fact that South Africa is still a developing country that struggles with high unemployment and inequality. This dissertation explores this concept of CSI in research that was conducted in the community of Letswaleng (Embalenhle), in Mpumalanga, in order to establish whether there is a relationship between the m
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LIN, YUNG-JIE, and 林勇傑. "Data Mining For Social Medlia Marketing Application." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/8hyrvq.

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碩士<br>國立勤益科技大學<br>資訊工程系<br>107<br>With the development of the Internet, a platform for consumers to share their products on the Internet, but less to discuss the platform of food, in order to understand the satisfaction of consumers, traditional catering companies can only Using paper to let customers fill in, this method additionally increases the printing cost of paper, and cannot give feedback immediately. In this thesis, we use web crawler technology to capture webpage comments of social media to collect data and understand consumers’ degree of satisfaction through text analysis. By resear
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