Random Walks on the Reputation Graph

Ribas, Sabir; Ribeiro-Neto, Berthier; Santos, Rodrygo L. T.; Silva, Edmundo de Souza e; Ueda, Alberto; Ziviani, Nívio

doi:10.1145/2808194.2809462

Cited by 6 publications

(5 citation statements)

References 70 publications

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“…Another direction is to study approaches to address ranking ties, specially how to break ties between papers with no information on citations. Using reputation-based metrics [8,9] seems to be a reasonable approach to address these issues.…”

Section: Discussionmentioning

confidence: 99%

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Simplified Relative Citation Ratio for Static Paper Ranking: UFMG/LATIN at WSDM Cup 2016

Ribas,

Ueda,

Santos

et al. 2016

Preprint

Self Cite

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Static rankings of papers play a key role in the academic search setting. Many features are commonly used in the literature to produce such rankings, some examples are citationbased metrics, distinct applications of PageRank, among others. More recently, learning to rank techniques have been successfully applied to combine sets of features producing effective results. In this work, we propose the metric S-RCR, which is a simplified version of a metric called Relative Citation Ratio -both based on the idea of a co-citation network. When compared to the classical version, our simplification S-RCR leads to improved efficiency with a reasonable effectiveness. We use S-RCR to rank over 120 million papers in the Microsoft Academic Graph dataset. By using this single feature, which has no parameters and does not need to be tuned, our team was able to reach the 3rd position in the first phase of the WSDM Cup 2016.

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Section: Discussionmentioning

confidence: 99%

“…However, some authors also apply random walks in heterogeneous graphs. In [9], for example, the authors propose a novel random walk model to identify the most reputable entities of a domain based on a conceptual framework of reputation flows.…”

Section: Literature On Paper Rankingsmentioning

confidence: 99%

Simplified Relative Citation Ratio for Static Paper Ranking: UFMG/LATIN at WSDM Cup 2016

Ribas,

Ueda,

Santos

et al. 2016

Preprint

Self Cite

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show abstract

“…The identification of reputable entities is important in business, education, and many other fields. In [119], we propose to exploit the transference of reputation among entities to identify the most reputable ones. We instantiate our model in an academic search setting, by modeling research groups as reputation sources and publication venues as reputation targets.…”

Section: Effective Information Retrievalmentioning

confidence: 99%

Information and data management at PUC-rio and UFMG

Furtado

Ziviani

2018

Proc. VLDB Endow.

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“…Examples of graph‐based methods using generic citation relations include Baez, Mirylenka, and Parra (), He, Pei, Kifer, Mitra, and Giles (), Liang, Li, and Qian (), Woodruff, Gossweiler, Pitkow, Chi, and Card (), and Zhou et al (). More recently, a cocitation‐based metric was successfully applied to the challenge of ranking a large number of papers (120M) with respect to their query independent importance (Ribas, Ueda, Santos, Ribeiro‐Neto, & Ziviani, ). A few contributions that specifically use cocitations and full‐text relatedness in the context of recommendation systems (Gipp & Beel, ; Eto, ; Schwarzer et al, ) will be discussed below.…”

Section: Related Workmentioning

confidence: 99%

The Closer the Better: Similarity of Publication Pairs at Different Cocitation Levels

Colavizza

Boyack

Waltman

2017

Asso for Info Science & Tech

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We investigate the similarities of pairs of articles which are co-cited at the different cocitation levels of the journal, article, section, paragraph, sentence and bracket. Our results indicate that textual similarity, intellectual overlap (shared references), author overlap (shared authors), proximity in publication time all rise monotonically as the co-citation level gets lower (from journal to bracket). While the main gain in similarity happens when moving from journal to article co-citation, all level changes entail an increase in similarity, especially section to paragraph and paragraph to sentence/bracket levels. We compare results from four journals over the years 2010-2015: Cell, the European Journal of Operational Research, Physics Letters B and Research Policy, with consistent general outcomes and some interesting differences. Our findings motivate the use of granular co-citation information as defined by meaningful units of text, with implications for, among others, the elaboration of maps of science and the retrieval of scholarly literature. IntroductionThe co-citation relation is used extensively in bibliometrics, and has received some recent attention in information retrieval. Applications include the identification of topically-related publications for search engines and clustering of publications to understand the structure of science. If two or more publications are co-cited by a third one, they are generally assumed to be related to some extent, from the viewpoint of their citing authors (Small 1973). Normally, this assumption is considered to be valid already at a relatively coarse co-citation level, most often at the publication (e.g. article) level. In addition, recent work suggests that the relatedness of co-cited publications might increase with increasing proximity of two publications within the full text of the citing publication (e.g. Gipp & Beel 2009), and that improvements in maps of science or document retrieval can be obtained by taking textual proximity into account (e.g. Boyack et al. 2013). Indeed, it makes sense to assume that if two publications are co-cited within the same sentence or bracket in a publication, they typically will be in some way more related than two publications co-cited only at the more general section or publication levels. Yet open questions remain. We know little about the ways in which related, co-cited publications are similar over different dimensions. Furthermore, to what extent do different notions of similarity, such as textual and intellectual, depend on the level of the co-citation? This study was designed to provide answers to these questions.

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Random Walks on the Reputation Graph

Cited by 6 publications

References 70 publications

Simplified Relative Citation Ratio for Static Paper Ranking: UFMG/LATIN at WSDM Cup 2016

Simplified Relative Citation Ratio for Static Paper Ranking: UFMG/LATIN at WSDM Cup 2016

Information and data management at PUC-rio and UFMG

The Closer the Better: Similarity of Publication Pairs at Different Cocitation Levels

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