Online scientific publications are becoming more and more popular. The number of publications we can access almost instantaneously is rapidly increasing. This makes it more challenging for researchers to pursue a topic, review literature, track research history or follow research trends. Using online resources such as search engines and digital libraries is helpful to find scientific publications, however most of the time the user ends up with an overwhelming amount of linear results to go through. This thesis proposes an alternative system, which takes advantage of citation/reference relations between publications. This demonstrates better insight of the hierarchy distribution of publications around a given topic. We also utilize information visualization techniques to represent the publications as a network. Our system is designed to automatically retrieve publications from Google Scholar and visualize them as a 2-dimensional graph representation using the citation relations. In this, the nodes represent the documents while the links represent the citation/reference relations between them. Our visualization system provides a better view of publications, making it easier to identify the research flow, connect publications, and assess similarities/differences between them. It is an interactive web based system, which allows the users to get more information about any selected publication and calculate a similarity score between two selected publications. Traditionally, similar documents are found using Natural Language Processing (NLP), which compares documents based on matching their contents. In the proposed method, similar documents are found using the citation/reference relations which are iii represented by the relationship that was originally inputted by the authors. We propose a new path based metric for measuring the similarity scores between any pair of publications. This is based on both the number of paths and the length of each path. More paths and shorter lengths increase the similarity score. We compare our similarity score results with another similarity score from Scurtu’s Document Similarity [1] that uses the NLP method. We then use the average of the similarity scores collected from 15 users as a ground truth to validate the efficiency of our method. The results indicate that our Citation Network approach yielded better scores than Scurtu’s approach.

Link label prediction is the problem of predicting the missing labels or signs of all the unlabeled edges in a network. For signed networks, these labels can either be positive or negative. In recent years, different algorithms have been proposed such as using regression, trust propagation and matrix factorization. These approaches have tried to solve the problem of link label prediction by using ideas from social theories, where most of them predict a single missing label given that labels of other edges are known. However, in most real-world social graphs, the number of labeled edges is usually less than that of unlabeled edges. Therefore, predicting a single edge label at a time would require multiple runs and is more computationally demanding. In this thesis, we look at link label prediction problem on a signed citation network with missing edge labels. Our citation network consists of papers from three major machine learning and data mining conferences together with their references, and edges showing the relationship between them. An edge in our network is labeled either positive (dataset relevant) if the reference is based on the dataset used in the paper or negative otherwise. We present three approaches to predict the missing labels. The first approach converts the label prediction problem into a standard classification problem. We then, generate a set of features for each edge and then adopt Support Vector Machines in solving the classification problem. For the second approach, we formalize the graph such that the edges are represented as nodes with links showing similarities between them. We then adopt a label propagation method to propagate the labels on known nodes to those with unknown labels. In the third approach, we adopt a PageRank approach where we rank the nodes according to the number of incoming positive and negative edges, after which we set a threshold. Based on the ranks, we can infer an edge would be positive if it goes a node above the threshold. Experimental results on our citation network corroborate the efficacy of these approaches. With each edge having a label, we also performed additional network analysis where we extracted a subnetwork of the dataset relevant edges and nodes in our citation network, and then detected different communities from this extracted sub-network. To understand the different detected communities, we performed a case study on several dataset communities. The study shows a relationship between the major topic areas in a dataset community and the data sources in the community.

We investigate the applicability of network analysis to the problem of finding seminal publications in scientific publishing. In particular, we focus on the network measures betweenness centrality, the so-called backbone graph, and the burstiness of citations. The metrics are evaluated using precision-related scores with respect to gold standards based on fellow programmes and manual annotation. Citation counts, PageRank, and random selection are used as baselines. We find that the backbone graph provides us with a way to possibly discover seminal publications with low citation count, and combining betweenness and burstiness gives results on par with citation count. / I detta examensarbete undersöks det huruvida analys av citeringsgrafer kan användas för att finna betydelsefulla vetenskapliga publikationer. Framför allt studeras ”betweenness”-centralitet, den så kallade ”backbone”-grafen samt ”burstiness” av citeringar. Dessa mått utvärderas med hjälp av precisionsmått med avseende på guldstandarder baserade på ’fellow’-program samt via manuell annotering. Antal citeringar, PageRank, och slumpmässigt urval används som jämförelse. Resultaten visar att ”backbone”-grafen kan bidra till att eventuellt upptäcka betydelsefulla publikationer med ett lågt antal citeringar samt att en kombination av ”betweenness” och ”burstiness” ger resultat i nivå med de man får av att räkna antal citeringar.

Submitted by Viviane Lima da Cunha (viviane@biblioteca.ufpb.br) on 2016-02-16T10:51:10Z No. of bitstreams: 1 arquivototal.pdf: 3174848 bytes, checksum: f060b5ac76aa0a5bf42f2a4e540f78ef (MD5) / Made available in DSpace on 2016-02-16T10:51:10Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 3174848 bytes, checksum: f060b5ac76aa0a5bf42f2a4e540f78ef (MD5) Previous issue date: 2015-02-13 / Scientific research is defined as a set of activities that are aimed at the discovery of new knowledge relevant to the solution of existing problems. Scientific knowledge is not just the discovery of new facts and laws, but also in its publication. This is to obtain and communicate results through forms of scientific production. To understand the complex scientific production system numerous analytical techniques have been applied in digital repositories. These techniques aim to identify relevant scientific productions based on indicators. In this sense the present work aims to create a methodology that facilitate the identification of publications that are relevant to specific areas of expertise. For this we used three contexts, the first on the area of social network analysis, the second on the records of 20 years from webmedia and finally on area of embedded systems. As a source of study our software tool achieved several results for the areas of knowledge between them we can mention the development of publications for the most relevant publication vehicles and the classification of network communities. / A pesquisa científica é definida como um conjunto de atividades que têm por objetivo a descoberta de novos conhecimentos de interesse para a solução de problemas existentes. O conhecimento científico não se resume na descoberta de fatos e leis novas, mas também em sua publicação. Trata-se de obter e comunicar resultados através de formas de produção científica. Visando compreender o complexo sistema de produção científica inúmeras técnicas de análise vêm sendo aplicadas em repositórios digitais. Essas técnicas objetivam a identificação de produções cientificas relevantes baseadas em indicadores. Neste sentido o presente trabalho de pesquisa tem como objetivo criar uma metodologia que facilite identificar publicações que são relevantes a determinadas áreas de conhecimento. Para isto utilizamos três contextos, o primeiro sobre a área de análise de redes sociais, o segundo sobre os anais dos 20 anos do webmedia e por último sobre área de sistemas embarcados. Como fonte de estudo nossa ferramenta de software conseguiu diversos resultados referentes às áreas de conhecimento, entre eles a evolução de publicações para os veículos de publicação mais relevantes, a classificação das comunidades pertencentes a rede, e entre outros resultados.

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In today's significant and rapidly increasing amount of scientific publications, exploring recent studies in a given research area and building an effective scientific collaboration has become more challenging than any time before. Scientific production growth has been increasing the difficulties for identifying the most relevant papers to cite or to find an appropriate conference or journal to submit a paper to publish. As a result, authors and publishers rely on different analytical approaches in order to measure the relationship among the citation network. Different parameters have been used such as the impact factor, number of citations, co-citation to assess the impact of the produced research publication. However, using one assessing factor considers only one level of relationship exploration, since it does not reflect the effect of the other factors. In this thesis, we propose an approach to measure the Academic Citation Impact that will help to identify the impact of articles, authors, and venues at their extended nearby citation network. We combine the content similarity with the bibliometric indices to evaluate the citation impact of articles, authors, and venues in their surrounding citation network. Using the article metadata, we calculate the semantic similarity between any two articles in the extended network. Then we use the similarity score and bibliometric indices to evaluate the impact of the articles, authors, and venues among their extended nearby citation network. Furthermore, we propose an academic recommendation model to identify the latent preferences among the citation network of the given article in order to expose the concealed connection between the academic objects (articles, authors, and venues) at the citation network of the given article. To reveal the degree of trust for collaboration between academic objects (articles, authors, and venues), we use the similarity learning to estimate the collaborative confidence score that represents the anticipation of a prospect relationship between the academic objects among a scientific community. We conducted an offline experiment to measure the accuracy of delivering personalized recommendations, based on the user’s selection preferences; real-world datasets were used. Our evaluation results show a potential improvement to the quality of the recommendation when compared to baseline recommendation algorithms that consider co-citation information.

每一項學術研究進行，其理論基礎都必需要建立於過去已完成的研究之上，因此文獻尋找與探討是進行研究過程非常重要的一個步驟。在數位時代與網際網路的加乘效益之下，改變了過去研究者必需為參考文獻東奔西跑的文獻資料尋找方式，但是卻會造成研究者被許多數位文獻淹沒。借用自網頁分析技術而設計的Google學術搜尋網路工具，能透過已經計算好的文獻權重PaperRank排序使用者所尋找的文獻集合，讓使用者能在數位文獻之中依單篇文獻被引用次數為原則而理出頭緒，但其順序式的排列仍然不能夠揭露出搜尋到的文獻集合裡彼此之間的關聯，其中包括了文獻所使用的關鍵字、作者與參考文獻。為了處理了解文獻中多維度的複雜資料關聯，最好的方式還是依賴人類的視覺化資訊處理能力，特別是當資料量大並且需要在短時間內決策時。 此外使用在文獻分析研究中，學者們使用共同引用(co-citation)、共同作者(co-work)、共同作者引用(co-author)等分析方式，配合延伸自社會網路分析理論中的社會密度(social distance)、關聯層級(social degree)、群(clique)等參數概念，試將複雜的文獻資料有脈絡地按排供參考。僅管此是工作難以機械化且消耗時間的(Börner, Chen , Boyack, 2003)，但是卻能將某一特定領域的發展直覺地呈現出來，如此若能將這些分析方式配合視覺化的呈現，則研究學者便能更進一步了進行大量文獻資料視覺化的分析、探索。 本研究試提出一個新的協助文獻探索平台系統架構，將傳統的文字搜尋轉變為視覺化的資料探索。使用者能透過三種不同的層級的資料：知識本體與關鍵字層、引文網路層及人員網路層，並與呈現的資料互動進一步了解資料間的關聯方式。最後實作視覺化雛型平台，並使用在國家圖書館所提供的博、碩士論文網所提供的論文資料，提供給研究人員探索特定知識領域中新研究方向的探索工具，並能協助研究者能在尚未完瞭解的專業領域之前，能快速地瞭解在該其領域重要文獻的導引平台。 / Paper survey is the most important task for building earnest theories, while researchers conducting academic researches. One must touches the fundamental detail of each theory and track down the develop-path of what achievement have been established by previous researches. Benefit from synergy of information age and document digitalized, it not only reduces the cost of finding reference documents, but also makes researchers suffer from information overwhelming after click single “search it” bottom. Stand in for traditional paper web search methods, new academic paper search technology borrowing from the idea of web search engine calculates the importance of each paper by cited number, and recommends users the most important papers by serial listing. However, serial listing does never spell the relationships of suggesting papers out, but only those results match some specific criteria. Those relationships of papers can be classified into 3 different types: the relations of keywords and references that author used and social relationship of authors like co-author and author co-citation which have been developed to explain the complex citation network structures. Those multi-dimensional relationships are extremely abundant and complex, so there is no better way to deal with but depending on visual data processing within human nature. In this paper, we try to propose a new platform to transform paper search in serial listing, into a visualized explore platform by demonstrating 3 different types of relationship: ontology-keywords, papers-references and personnel-references. End users can fallow the relationships between each difference nodes to explore considerable references, as well as change into different view and interact with existing information by using interactive mechanizes. In order to bring this idea to practical application usage, we build a proto-type platform to show our idea by using data from ETDS (electronic theses and dissertations system) of Ministry of education. We hope sincerely by using this proto-type platform, users can catch the major ideas of specific knowledge domain and researchers can explore acceptable references and even conduct new search topic.

Submitted by Joaquim Heck (joaquimheck@uol.com.br) on 2018-03-06T23:24:07Z No. of bitstreams: 1 PDF_CDAE_Tese_Joaquim_Heck.pdf: 10473820 bytes, checksum: ad23dda74b39a1cdacaf8ac5345e3c9d (MD5) / Approved for entry into archive by Debora Nunes Ferreira (debora.nunes@fgv.br) on 2018-03-07T12:33:18Z (GMT) No. of bitstreams: 1 PDF_CDAE_Tese_Joaquim_Heck.pdf: 10473820 bytes, checksum: ad23dda74b39a1cdacaf8ac5345e3c9d (MD5) / Made available in DSpace on 2018-03-07T12:39:47Z (GMT). No. of bitstreams: 1 PDF_CDAE_Tese_Joaquim_Heck.pdf: 10473820 bytes, checksum: ad23dda74b39a1cdacaf8ac5345e3c9d (MD5) Previous issue date: 2018-02-23 / Esta tese apresenta os resultados de um estudo em metodologia que estabeleceu um novo método específico de análise documental e histórica, denominado cartografia estrutural para revisão de literatura, e que foi aplicado de forma experimental no estudo histórico de um tema da área de Pesquisa Operacional, os Problem Structuring Methods (PSMs). A cartografia estrutural para revisão de literatura é um método rigoroso e interdisciplinar que revela a estrutura subjacente à uma literatura por meio dos conceitos metodológicos encontrados em pesquisa documental, pesquisa histórica, Teoria dos Grafos, Análise de redes de citações e Cartografia. Verificou-se, a partir dessa interdisciplinaridade, que as relações entre diferentes autores, de diferentes épocas e que publicaram em diferentes periódicos são essenciais para aprofundar a compreensão e familiarizar o pesquisador com uma determinada área do conhecimento. Depois de introduzir a natureza básica da indexação de citações e da análise de rede, esse estudo apresenta a elaboração de um atlas bibliográfico, formado por mapas visuais e diagramas. A aplicação desse método resultou na composição do atlas bibliográfico sobre os PSMs no período de 1950 a 1989. O mapeamento de ideias e conceitos em um arranjo organizado, obtido pela análise exploratória de uma rede de citações longitudinal, assegura familiaridade com os conceitos constitutivos dos PSMs. O atlas bibliográfico é constituído por três análises principais: a exploração da abrangência panorâmica, a das referências e a dos periódicos. Esse estudo fornece subsídios para uma reflexão importante sobre a noção de unidade dos PSMs e a coesão de seus conceitos constituintes encontrada em seus precedentes teóricos. Finalmente, o método de cartografia estrutural possibilita realizar uma revisão de literatura sofisticada, bem como identificar temas fundamentais para futuras pesquisas mais produtivas. / This thesis presents the results of a methodological study that has established a specific method of historical and documental investigation, denominated structural cartography for literature review, which was experimentally applied in the study of Problem Structuring Methods (PSMs) history. Structural cartography for literature review is a rigorous and interdisciplinary method that reveals the underlying structure of a field literature through the methodological notions found in historical research, documental investigation, Graph Theory, and its subfield of citation network analysis, and Cartography. Due to its interdisciplinarity, it becomes clear that the relations between different authors, from different periods of time and from different media are essential to familiarize scholars with their fields of knowledge. After introducing the basic concepts of citation indexing and network analysis, this study shows how to build a bibliographic atlas composed of visual maps and diagrams. The application of this method resulted in the bibliographic atlas on the PSMs from 1950 to 1989. The mapping of ideas and concepts in an organized arrangement, which is obtained by the analysis of a longitudinal exploratory citation network, ensures familiarity with primitive concepts. The bibliographic atlas is composed by three main analysis: the exploration of coverage, of sources and of media. Moreover, this study provided insights for an important reflection on the notion of PSMs unity and the cohesion of their constituent concepts found in their theoretical precedents. Finally, the method of structural cartography for literature review made possible to conduct sophisticate literature review and has provided substantial themes for future research.